Model ID
Qwen/Qwen3-235B-A22B-Instruct-2507
Capabilities
Qwen3 235B A22B Instruct 2507
The Qwen3 235B A22B Instruct 2507 is the premier flagship Mixture-of-Experts (MoE) Causal Language Model in the Qwen3 family, built with 235B total parameters and 22B activated per forward pass. This version is optimized for high-quality instruction following, logical reasoning, and preference-aligned text generation, with substantial improvements in multilingual long-tail knowledge coverage and subjective task alignment. It supports a native 262,144-token context window and can be extended up to approximately 1,010,000 tokens, enabling large-scale document analysis, extended conversational sessions, and complex multi-source workflows.
About this model
The Qwen3 235B A22B Instruct 2507 is the premier flagship Mixture-of-Experts (MoE) Causal Language Model in the Qwen3 family, built with 235B total parameters and 22B activated per forward pass. This version is optimized for high-quality instruction following, logical reasoning, and preference-aligned text generation, with substantial improvements in multilingual long-tail knowledge coverage and subjective task alignment. It supports a native 262,144-token context window and can be extended up to approximately 1,010,000 tokens, enabling large-scale document analysis, extended conversational sessions, and complex multi-source workflows.
Model specifications and capabilities are published by the model author and reproduced here from HF Model Card (Qwen/Qwen3-235B-A22B-Instruct-2507). Released under Apache 2.0. Further reading: Paper · Blog
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Hardware
B200
1,440 GB
Engine
vLLM
SGLang
Deployment code
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Performance under load
Tokens/s (total)
Benchmarks measured by Vultr on B200 · vLLM. Throughput and latency vary with concurrency, input length and engine configuration, so treat these as a comparison baseline, not a service guarantee.
NVIDIA HGX B200
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