Available Models

Browse the foundation models available through W&B Inference

  2 minute read  

W&B Inference provides access to several open-source foundation models. Each model has different strengths and use cases.

Model catalog

Model Model ID (for API usage) Type Context Window Parameters Description
DeepSeek R1-0528 deepseek-ai/DeepSeek-R1-0528 Text 161K 37B-680B (Active-Total) Optimized for precise reasoning tasks including complex coding, math, and structured document analysis
DeepSeek V3-0324 deepseek-ai/DeepSeek-V3-0324 Text 161K 37B-680B (Active-Total) Robust Mixture-of-Experts model tailored for high-complexity language processing and comprehensive document analysis
DeepSeek V3.1 deepseek-ai/DeepSeek-V3.1 Text 128K 37B-671B (Active-Total) A large hybrid model that supports both thinking and non-thinking modes via prompt templates
Meta Llama 3.1 8B meta-llama/Llama-3.1-8B-Instruct Text 128K 8B (Total) Efficient conversational model optimized for responsive multilingual chatbot interactions
Meta Llama 3.3 70B meta-llama/Llama-3.3-70B-Instruct Text 128K 70B (Total) Multilingual model excelling in conversational tasks, detailed instruction-following, and coding
Meta Llama 4 Scout meta-llama/Llama-4-Scout-17B-16E-Instruct Text, Vision 64K 17B-109B (Active-Total) Multi-modal model integrating text and image understanding, ideal for visual tasks and combined analysis
Microsoft Phi 4 Mini 3.8B microsoft/Phi-4-mini-instruct Text 128K 3.8B (Active-Total) Compact, efficient model ideal for fast responses in resource-constrained environments
MoonshotAI Kimi K2 moonshotai/Kimi-K2-Instruct Text 128K 32B-1T (Active-Total) Mixture-of-Experts model optimized for complex tool use, reasoning, and code synthesis
OpenAI GPT OSS 20B openai/gpt-oss-20b Text 131K 3.6B-20B (Active-Total) Lower latency Mixture-of-Experts model trained on OpenAI’s Harmony response format with reasoning capabilities.
OpenAI GPT OSS 120B openai/gpt-oss-120b Text 131K 5.1B-117B (Active-Total) Efficient Mixture-of-Experts model designed for high-reasoning, agentic and general-purpose use cases.
Qwen3 235B A22B Thinking-2507 Qwen/Qwen3-235B-A22B-Thinking-2507 Text 262K 22B-235B (Active-Total) High-performance Mixture-of-Experts model optimized for structured reasoning, math, and long-form generation
Qwen3 235B A22B-2507 Qwen/Qwen3-235B-A22B-Instruct-2507 Text 262K 22B-235B (Active-Total) Efficient multilingual, Mixture-of-Experts, instruction-tuned model, optimized for logical reasoning
Qwen3 Coder 480B A35B Qwen/Qwen3-Coder-480B-A35B-Instruct Text 262K 35B-480B (Active-Total) Mixture-of-Experts model optimized for coding tasks such as function calling, tooling use, and long-context reasoning

Using model IDs

When using the API, specify the model using its ID from the table above. For example:

response = client.chat.completions.create(
    model="meta-llama/Llama-3.1-8B-Instruct",
    messages=[...]
)

Next steps


Last modified August 26, 2025