Free LLM Models Directory
Discover free and open-source large language models for text generation, code completion, and embeddings.
The Ultimate Free LLM Models Directory
Welcome to the most comprehensive directory of free and open-source LLM models. Whether you're a developer, researcher, or AI enthusiast, our curated collection helps you discover powerful language models that you can run locally, fine-tune, or integrate into your applications.
Our directory features models from leading providers including Meta's Llama 2, Mistral AI, Microsoft's Phi, and hundreds more on Hugging Face. All models are verified to have permissive licenses allowing commercial use.
From text generation and code completion to embeddings and multimodal models - find everything you need to build the next generation of AI applications!
Showing 529-576 of 576 models
firefunction-v2
LLM Models
firefunction-v2 is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
wizard-vicuna
LLM Models
wizard-vicuna is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
open-orca-platypus2
LLM Models
open-orca-platypus2 is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
codebooga
LLM Models
codebooga is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
rnj-1
LLM Models
rnj-1 is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
nemotron-3-nano
LLM Models
nemotron-3-nano is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
goliath
LLM Models
goliath is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
deepseek-ocr
LLM Models
deepseek-ocr is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
granite3.2
LLM Models
granite3.2 is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
olmo-3
LLM Models
olmo-3 is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
r1-1776
LLM Models
r1-1776 is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
snowflake-arctic-embed2
LLM Models
snowflake-arctic-embed2 is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
sailor2
LLM Models
sailor2 is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
tulu3
LLM Models
tulu3 is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
granite-embedding
LLM Models
granite-embedding is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
granite3-guardian
LLM Models
granite3-guardian is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
kimi-k2.5
LLM Models
kimi-k2.5 is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
dbrx
LLM Models
dbrx is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
llava-phi3
LLM Models
llava-phi3 is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
kimi-k2.6
LLM Models
kimi-k2.6 is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
nomic-embed-text-v2-moe
LLM Models
nomic-embed-text-v2-moe is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
deepseek-v2.5
LLM Models
deepseek-v2.5 is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
olmo-3.1
LLM Models
olmo-3.1 is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
phi4-mini-reasoning
LLM Models
phi4-mini-reasoning is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
bge-large
LLM Models
bge-large is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
command-r7b
LLM Models
command-r7b is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
smallthinker
LLM Models
smallthinker is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
devstral-2
LLM Models
devstral-2 is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
alfred
LLM Models
alfred is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
command-a
LLM Models
command-a is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
marco-o1
LLM Models
marco-o1 is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
cogito-2.1
LLM Models
cogito-2.1 is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
command-r7b-arabic
LLM Models
command-r7b-arabic is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
functiongemma
LLM Models
functiongemma is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
gpt-oss-safeguard
LLM Models
gpt-oss-safeguard is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
granite4.1
LLM Models
granite4.1 is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
nemotron-cascade-2
LLM Models
nemotron-cascade-2 is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
deepseek-v4-flash
LLM Models
deepseek-v4-flash is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
deepseek-v4-pro
LLM Models
deepseek-v4-pro is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
kimi-k2
LLM Models
kimi-k2 is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
mistral-large-3
LLM Models
mistral-large-3 is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
medgemma
LLM Models
medgemma is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
mistral-medium-3.5
LLM Models
mistral-medium-3.5 is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
minimax-m3
LLM Models
minimax-m3 is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
medgemma1.5
LLM Models
medgemma1.5 is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
laguna-xs.2
LLM Models
laguna-xs.2 is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
lfm2.5
LLM Models
lfm2.5 is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
nemotron-3-ultra
LLM Models
nemotron-3-ultra is a model entry associated with Ollama. This listing is intended to help developers, researchers, students, and AI application builders discover and organize available language or generative AI models for experimentation, prototyping, model comparison, and software integration. The supplied dataset does not include a model-specific capability description for this record, so capabilities such as reasoning, coding, instruction following, multilingual support, vision or audio processing, tool use, structured outputs, and long-context processing should not be assumed from the model name alone. Before using this model in an application, review the linked provider or model documentation for its architecture or model family, supported modalities, context window, input and output formats, API requirements, licensing terms, pricing or free-tier conditions, rate limits, safety constraints, and current availability. Production deployments should additionally test model quality, latency, reliability, privacy requirements, and workload-specific performance using representative data from the intended application.
Frequently Asked Questions About LLM Models
What are LLM models and how do they work?
Large Language Models (LLMs) are AI models trained on vast amounts of text data to understand and generate human-like text. They use transformer architecture and can perform tasks like text generation, translation, summarization, and code completion.
Which LLM models are free to use?
Many LLM models are freely available including Llama 2, Mistral, Mixtral, Phi-2, and various models on Hugging Face. Our directory features only models with permissive licenses that allow commercial use.
How do I run LLM models locally?
You can run LLMs locally using tools like Ollama, LM Studio, or text-generation-webui. Most models require significant GPU memory (8GB+ VRAM recommended). Smaller models like Phi-2 and Llama 2 7B can run on consumer hardware.
What's the difference between open-source and proprietary LLMs?
Open-source LLMs like Llama 2 and Mistral have publicly available weights and can be run locally or fine-tuned. Proprietary models like GPT-4 are only accessible via API. Open-source models offer more control and privacy.
Can I use these LLM models for commercial projects?
Most models in our directory have permissive licenses (Apache 2.0, MIT) allowing commercial use. Always check the specific model's license on Hugging Face or the provider's website before using in production.