vllm - 💡(How to fix) Fix [Bug]: Deepseek V4 vllm not response when using with claude code [2 comments, 2 participants]

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vllm-project/vllm#40854Fetched 2026-04-26 05:06:25
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Code Example

Your output of `python collect_env.py` here
RAW_BUFFERClick to expand / collapse

Your current environment

docker run --gpus all
--privileged --ipc=host -p 8077:8000
-v ~/.cache/huggingface:/root/.cache/huggingface
-v /data/models:/data/models
-e VLLM_ENGINE_READY_TIMEOUT_S=3600
vllm/vllm-openai:deepseekv4-cu130 /data/models/DeepseekV4-pro
--trust-remote-code
--kv-cache-dtype fp8
--block-size 256
--enable-expert-parallel
--data-parallel-size 8
--compilation-config '{"cudagraph_mode":"FULL_AND_PIECEWISE", "custom_ops":["all"]}'
--attention_config.use_fp4_indexer_cache=True
--tokenizer-mode deepseek_v4
--tool-call-parser deepseek_v4
--enable-auto-tool-choice
--reasoning-parser deepseek_v4
--speculative_config '{"method":"mtp","num_speculative_tokens":2}'

<details> <summary>The output of <code>python collect_env.py</code></summary>
Your output of `python collect_env.py` here
</details>

🐛 Describe the bug

Send request reply is OK , but when using claude code is very slow and even not response , other model didn't have this issue .

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extent analysis

TL;DR

The issue might be related to the specific model or configuration used, and adjusting the --block-size or --data-parallel-size parameters could potentially improve performance.

Guidance

  • Verify if the issue persists with other models to isolate the problem to the "claude" model or a specific configuration.
  • Experiment with reducing the --block-size (e.g., from 256 to 128) to see if it improves performance.
  • Consider adjusting the --data-parallel-size (e.g., from 8 to 4) to balance parallel processing and memory usage.
  • Check if the --compilation-config and --speculative_config settings are optimized for the "claude" model.

Example

No specific code snippet can be provided without more context, but the command used to run the model can be modified to test different configurations.

Notes

The provided information does not specify the exact version of the model or the environment, which could be relevant for troubleshooting. The issue might be specific to the "claude" model or the particular configuration used.

Recommendation

Apply workaround: Adjust the --block-size and --data-parallel-size parameters to find an optimal balance for the "claude" model, as the current configuration might be causing performance issues.

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