Model Catalog
Pick a model from our selection, or deploy a previously fine-tuned model.
DeepSeek V4.1 Flash
New DeepSeek V4.1 Flash is a Mixture-of-Experts model built for efficient reasoning, tool use, and agentic workloads.
DeepSeek V4 Flash 0731
New DeepSeek V4 Flash 0731 is an updated release of the 284B-parameter MoE model with 13B activated parameters, built for efficient long-context intelligence.
Gemma 4 31B IT FP8 Dynamic
RedHatAI's gemma-4-31B-it-FP8-dynamic was obtained by quantizing the weights and activations of google/gemma-4-31B-it to FP8 data type using dynamic per-token quantization.
GLM 5.2 FP8
GLM 5.2 FP8 is the FP8 checkpoint of Z.ai's 753B-parameter flagship MoE model for long-horizon tasks, with a solid 1M-token context.
GLM 5.1 FP8
GLM 5.1 FP8 is the FP8 checkpoint of Z.ai's 754B-parameter flagship MoE model for agentic engineering and long-horizon coding.
Kimi K2.6
Kimi K2.6 is a native multimodal 1T-parameter MoE model with 32B activated parameters, aimed at long-horizon coding, agentic workflows, and autonomous task orchestration.
MiniMax M2.7
MiniMax M2.7 is a 229B-parameter MoE model for software engineering, agentic tool use, productivity workflows, and long-context reasoning.
GPT OSS 120B
GPT OSS is the latest OpenAI open-model designed for powerful reasoning, agentic tasks, and versatile developer use cases. GPT OSS 120B is intended for production, general purpose, and high reasoning use cases.
GPT OSS 20B
GPT OSS is the latest OpenAI open-model designed for powerful reasoning, agentic tasks, and versatile developer use cases. GPT OSS 20B is intended for lower latency, and local or specialized use cases.
IBM Granite 4.0 H Micro
Deprecated Granite-4.0-H-Micro is a 3B parameter long-context instruct model finetuned from Granite-4.0-H-Micro-Base. Granite 4.0 instruct models feature improved instruction following (IF) and tool-calling capabilities, making them more effective in enterprise applications.
IBM Granite 4.0 H Tiny
Deprecated Granite-4.0-H-Tiny is a 7B parameter long-context instruct model finetuned from Granite-4.0-H-Tiny-Base. Granite 4.0 instruct models feature improved instruction following (IF) and tool-calling capabilities, making them more effective in enterprise applications.
IBM Granite 4.0 H Small
Deprecated Granite-4.0-H-Small is a 32B parameter long-context instruct model finetuned from Granite-4.0-H-Small-Base. Granite 4.0 instruct models feature improved instruction following (IF) and tool-calling capabilities, making them more effective in enterprise applications.
Llama 4 Maverick 17B 128E Instruct
Deprecated The Llama 4 collection of models are natively multimodal AI models that enable text and multimodal experiences. These models leverage a mixture-of-experts architecture to offer industry-leading performance in text and image understanding.
Llama 4 Scout 17B 16E Instruct
Deprecated The Llama 4 collection of models are natively multimodal AI models that enable text and multimodal experiences. These models leverage a mixture-of-experts architecture to offer industry-leading performance in text and image understanding.
deepseek r1
Deprecated DeepSeek-R1 is an advanced reasoning system using reinforcement learning with cold-start initialization, achieving performance comparable to OpenAI-o1 across math, code, and reasoning tasks.
deepseek r1 distill qwen 32b
Deprecated DeepSeek-R1 is an advanced reasoning system using reinforcement learning with cold-start initialization, achieving performance comparable to leading proprietary models. The release includes distilled variants like DeepSeek-R1-Distill-Qwen-32B, which outperforms OpenAI's GPT-4-mini across mathematical reasoning (92.3% MATH) and coding benchmarks while maintaining commercial usability. This 32B-parameter model sets new state-of-the-art results for dense models in its class through optimized knowledge distillation from the R1 framework.
deepseek r1 distill llama 70b
Deprecated DeepSeek-R1 is an advanced reasoning model using reinforcement learning with cold-start initialization, matching top-tier systems in math and coding performance. The release includes distilled variants like DeepSeek-R1-Distill-Llama-70B, which preserves 94.5% MATH accuracy in the efficient Llama-70B architecture while supporting commercial applications.
Llama 3.2 11B Vision Instruct
Deprecated The Llama-3.2-11B-Vision-Instruct is a multimodal large language model optimized for visual recognition, image reasoning, captioning, and answering questions about images, trained on 6 billion image-text pairs, with 11 billion parameters, and supported for commercial and research use in English.
Llama 3.2 90B Vision Instruct
Deprecated The Llama-3.2-90B-Vision-Instruct is a multimodal large language model optimized for visual recognition, image reasoning, captioning, and answering questions about images, trained on 6 billion image-text pairs, with 90 billion parameters, and supported for commercial and research use in English.
Llama 3.3 70B Instruct
Deprecated The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out).
meta llama 3.1 70b instruct
Deprecated The Meta Llama 3.1 collection of multilingual large language models (LLMs) is a collection of pretrained and instruction tuned generative models in 8B, 70B and 405B sizes (text in/text out)
Meta Llama 3.1 8b Instruct
Deprecated The Meta Llama 3.1 collection of multilingual large language models (LLMs) is a collection of pretrained and instruction tuned generative models in 8B, 70B and 405B sizes (text in/text out)
Mixtral 8x22B Instruct v0.1
Deprecated The Mixtral-8x22B-Instruct-v0.1 LLM, a fine-tuned version of the high-efficiency, sparse Mixture-of-Experts Mixtral-8x22B model, excels in multilingual fluency, advanced math, coding skills, and scalable tech application development.