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ai/qwen3.6

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Multimodal AI model with 35B MoE architecture for coding agents, reasoning, and vision tasks

ai/kimi-k2.6

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1T MoE multimodal agentic model with long-horizon coding, swarm orchestration, and native vision

ai/mistral-small4-safetensors

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119B MoE model with switchable reasoning mode, multimodal vision, and 256k context window

ai/mistral-small4

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119B parameter hybrid model with reasoning, vision, and code capabilities (1M token context)

ai/qwen3.6-safetensors

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Multimodal LLM with 35B parameters for coding, agentic tasks, and vision-language understanding

ai/gemma4

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Gemma 4: multimodal open AI models by Google, optimized for reasoning, coding, and long context.

ai/gemma4-safetensors

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Gemma 4: multimodal open AI models by Google, optimized for reasoning, coding, and long context.

ai/qwen3.5

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397B MoE model with 17B activation for reasoning, coding, agents, and multimodal understanding

ai/qwen3.5-safetensors

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397B-parameter MoE multimodal LLM with 17B active params, 262K context, 201 languages

ai/qwen3-coder

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Qwen3-Coder is Qwen’s new series of coding agent models.

ai/glm-5-safetensors

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744B MoE language model with 40B active params for reasoning, coding, and agentic tasks (FP8)

ai/qwen3-coder-next-vllm

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Advanced coding agent model with 80B params (3B active MoE) for code generation and debugging

ai/qwen3-coder-next

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Efficient 80B MoE coding model with 3B activated params, 256K context, and agentic capabilities

ai/stable-diffusion

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Image generation model, uses a base latent diffusion model plus a refiner.

ai/glm-4.7-flash

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GLM-4.7-Flash is a top 30B-A3B MoE, balancing strong performance with efficient deployment.

ai/glm-4.7-flash-vllm

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GLM-4.7-Flash is a top 30B-A3B MoE, balancing strong performance with efficient deployment.

ai/devstral-small-2

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Devstral Small 2 is an FP8 instruct LLM for agentic SWE tasks, codebase tooling, and SWE-bench.

ai/functiongemma-vllm

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FunctionGemma is a 270M open model for fine-tuned, offline function-calling agents on small devices.

ai/functiongemma

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FunctionGemma is a 270M open model for fine-tuned, offline function-calling agents on small devices.

ai/kimi-k2

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Kimi K2 Thinking: open-source agent with deep reasoning, stable tool use, fast INT4, 256k context.

ai/kimi-k2-vllm

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Kimi K2 Thinking: open-source agent with deep reasoning, stable tool use, fast INT4, 256k context.

ai/deepseek-v3.2-vllm

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DeepSeek-V3.2 boosts efficiency and reasoning with DSA, scalable RL, agentic data—IMO/IOI wins.

ai/ministral3-vllm

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Ministral 3: compact vision-enabled model with near-24B performance, optimized for local edge use

ai/ministral3

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Ministral 3: compact vision-enabled model with near-24B performance, optimized for local edge use

ai/qwen3-reranker-vllm

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Multilingual reranking model for text retrieval, scoring document relevance across 119 languages.

ai/qwen3-reranker

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Multilingual reranking model for text retrieval, scoring document relevance across 119 languages.

ai/snowflake-arctic-embed-l-v2-vllm

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Snowflake’s Arctic-Embed v2.0 boosts multilingual retrieval and efficiency

ai/qwen3-embedding-vllm

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Qwen3 Embedding: multilingual models for advanced text/ranking tasks like retrieval & clustering.

ai/qwen3-embedding

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Qwen3 Embedding: multilingual models for advanced text/ranking tasks like retrieval & clustering.

ai/gpt-oss

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OpenAI’s open-weight models designed for powerful reasoning, agentic tasks