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A high-throughput and memory-efficient inference and serving engine for LLMs

Mirrored from https://github.com/tduncan-lum/Nvidia-Optimization-Stack---VLLM.git

Synced Nov 14, 05:30 UTC

[BugFix] Disable fp8 kv-cache by default for DeepSeek V3.2 (#27121)

Signed-off-by: Lucas Wilkinson <lwilkins@redhat.com> Signed-off-by: Lucas Wilkinson <LucasWilkinson@users.noreply.github.com> Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>

Lucas Wilkinson committed Oct 18, 2025 at 18:05 UTC c2bba690658823be5ec6f1742eb10294d4fa2479
1 file changed +2 -5
vllm/model_executor/models/config.py
+2 -5
@@ -481,12 +481,9 @@ class DeepseekV32ForCausalLM(VerifyAndUpdateConfig):
481 is_v32 = hasattr(hf_config, "index_topk")
482 assert is_v32
483
484 - # For DeepSeekV3.2, we use a custom fp8 format as default (i.e.
485 - # "auto")
484 + # For DeepSeekV3.2, a custom fp8 format is used when fp8 kv-cache is enabled.
485 cache_config = vllm_config.cache_config
487 - if cache_config.cache_dtype == "auto" or cache_config.cache_dtype.startswith(
488 - "fp8"
489 - ):
486 + if cache_config.cache_dtype.startswith("fp8"):
487 cache_config.cache_dtype = "fp8_ds_mla"
488 logger.info("Using custom fp8 kv-cache format for DeepSeekV3.2")
489 if cache_config.cache_dtype == "bfloat16":