Compatibility check
Can you run Qwen2.5 32B Instruct on the H200 141GB?
Yes. Qwen2.5 32B Instruct fits on the H200 141GB (141 GB) in full FP16/BF16 precision, using about 76.4 GB including a 1 GB KV cache at 4,096 tokens. You have comfortable headroom for longer prompts and modest batching.
Memory breakdown
Weights plus a 1 GB KV cache at 4,096tokens, against the card's 141 GB. Verdicts leave ~10% headroom for activations and fragmentation.
| Precision | Weights | KV cache | Total | % of 141 GB | Fit |
|---|---|---|---|---|---|
| FP16 / BF16full quality | 75.4 GB | 1 GB | 76.4 GB | 54% | Fits |
| INT8 (8-bit)near-full quality | 37.7 GB | 1 GB | 38.7 GB | 27% | Fits |
| INT4 (4-bit)GPTQ / AWQ / GGUF Q4 | 18.9 GB | 1 GB | 19.9 GB | 14% | Fits |
Planning estimates, not a substitute for profiling. Real usage varies with the inference runtime, batch size, and how much context you actually use — the KV cache grows linearly with prompt length.
GPUs that run Qwen2.5 32B Instruct
Cards where this model fits (at its best precision):
Models that fit the H200 141GB
Other popular models that run on this card:
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Frequently asked questions
Can the H200 141GB run Qwen2.5 32B Instruct?
Yes. In FP16 it uses about 76.4 GB, which fits the H200 141GB's 141 GB.
How much VRAM does Qwen2.5 32B Instruct need?
Approximately 75.4 GB in FP16, 37.7 GB in INT8, and 18.9 GB in 4-bit for the weights, plus a KV cache of about 1 GB at 4,096 tokens.
Does quantization let Qwen2.5 32B Instruct fit on the H200 141GB?
Yes. Dropping to FP16 / BF16 brings total usage to about 76.4 GB, which fits the 141 GB card with headroom for the KV cache.
What happens to memory with longer context?
The KV cache grows linearly with prompt length. At 4,096 tokens it is about 1 GB here; doubling the context roughly doubles that term, so long-context use can push a tight fit over the edge.