Available models - Weights & Biases Documentation (original) (raw)

Serverless Inference provides access to several open source foundation models. Each model has different strengths and use cases.

Generally available models

The following models are generally available:

Model Model ID (for API usage) Type Context Window Parameters Description
DeepSeek V4-Flash deepseek-ai/DeepSeek-V4-Flash Text 1049k 13B-284B (Active-Total) DeepSeek V4-Flash is an MoE model with 1M context length great for coding, reasoning, and agentic workloads.
DeepSeek V4-Pro deepseek-ai/DeepSeek-V4-Pro Text 1049k 49B-1.6T (Active-Total) DeepSeek V4-Pro is a 1.6T-parameter MoE model with 49B active parameters excelling at advanced reasoning, coding, and complex agentic workloads.
DeepSeek V3.1 deepseek-ai/DeepSeek-V3.1 Text 161k 37B-671B (Active-Total) A large hybrid model that supports both thinking and non-thinking modes via prompt templates.
Google Gemma 4 31B google/gemma-4-31B-it Text, Vision 262k 31B (Total) Gemma 4 31B Dense is designed for advanced reasoning, agentic workflows, and longer context and is natively trained on 140+ languages.
IBM Granite 4.1 8B ibm-granite/granite-4.1-8b Text 131k 8B (Total) Granite 4.1 8B is a long-context instruct model capable of enhanced tool calling, instruction following, and chat capabilities.
JetBrains Mellum2 12B A2.5B JetBrains/Mellum2-12B-A2.5B-Instruct Text 131k 2.5B-12B (Active-Total) Mellum2-12B-A2.5B-Instruct is a fast MoE model with 131K context built for coding, tool use, and low-latency AI workflows.
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 3.1 70B meta-llama/Llama-3.1-70B-Instruct Text 128k 70B (Total) Efficient conversational model optimized for responsive multilingual chatbot interactions.
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.
Microsoft Phi 4 Mini 3.8B microsoft/Phi-4-mini-instruct Text 128k 3.8B (Total) Compact, efficient model ideal for fast responses in resource-constrained environments.
MiniMax M2.5 MiniMaxAI/MiniMax-M2.5 Text 197k 10B-230B (Active-Total) MoE model with a highly sparse architecture designed for high-throughput and low latency with strong coding capabilities.
Moonshot AI Kimi K2.6 moonshotai/Kimi-K2.6 Text, Vision 262k 32B-1T (Active-Total) Kimi K2.6 is a multimodal Mixture-of-Experts language model featuring 32 billion activated parameters and a total of 1 trillion parameters.
Moonshot AI Kimi K2.5 moonshotai/Kimi-K2.5 Text, Vision 262k 32B-1T (Active-Total) Kimi K2.5 is a multimodal Mixture-of-Experts language model featuring 32 billion activated parameters and a total of 1 trillion parameters.
NVIDIA Nemotron 3 Super 120B nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-FP8 Text 262k 12B-120B (Active-Total) Nemotron 3 is a LatentMoE model designed to deliver strong agentic, reasoning, and conversational capabilities.
NVIDIA Nemotron 3 Ultra nvidia/NVIDIA-Nemotron-3-Ultra-550B-A55B Text 262k 55B-550B (Active-Total) Nemotron 3 Ultra is a powerful MoE model designed for long-running agents across coding, deep research, and enterprise automation.
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.
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.
OpenPipe Qwen3 14B Instruct OpenPipe/Qwen3-14B-Instruct Text 32.8k 14.8B (Total) An efficient multilingual, dense, instruction-tuned model, optimized by OpenPipe for building agents with finetuning.
Qwen3.6 35B A3B Qwen/Qwen3.6-35B-A3B Text, Vision 262k 3B-35B (Active-Total) Qwen3.6-35B-A3B is an MoE multimodal model with 262K context optimized for agentic coding workflows.
Qwen3.6 27B Qwen/Qwen3.6-27B Text, Vision 262k 27B (Total) Qwen3.6-27B is a 27B dense multimodal model with 262K context built for flagship-level agentic coding.
Qwen3.5 35B A3B Qwen/Qwen3.5-35B-A3B Text, Vision 262k 3B-35B (Active-Total) Qwen3.5-35B-A3B is an open-weights multimodal MoE model built for efficient, high-throughput inference across chat, reasoning, and agentic tasks.
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 30B A3B Qwen/Qwen3-30B-A3B-Instruct-2507 Text 262k 3.3B-30.5B (Active-Total) Qwen3-30B-A3B-Instruct-2507 is a 30.5B MoE instruction-tuned model with enhanced reasoning, coding, and long-context understanding.
Qwen3 Coder 480B A35B Qwen/Qwen3-Coder-480B-A35B-Instruct Text 262k 35B-480B (Active-Total) Mixture-of-Experts model optimized for agentic coding tasks such as function calling, tool use, and long-context reasoning.
Z.AI GLM 5.1 zai-org/GLM-5.1 Text 203k 40B-744B (Active-Total) Powerful MoE model for long-horizon agentic engineering and advanced reasoning.

Experimental models

The following models are experimental:

Model Model ID (for API usage) Type Context Window Parameters Description
Qwen3.5 27B Qwen/Qwen3.5-27B Text, Vision 262k 27B (Total) Qwen3.5-27B is a dense model from the Qwen3.5 family built for high performance across a large range of benchmarks.

Deprecated models

The following models are deprecated: None currently

Use model IDs

To specify a model when calling the API, use its Model ID from the preceding tables. For example:

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

Next steps

After you’ve chosen a model, continue with one of the following resources: