Can Qwen3-32B run on NVIDIA H100 80GB SXM?

Conditional memory judgement for one configuration. Change context, quant, or engine and the conclusion can change.

32B BF16 plus long context on H100 80GB.

Configuration used on this page: bf16, 32,768 cached tokens, 1 sequence, engine vllm.

Status: Tight. Software: Documented support.

Weights 61.02 GiB · raw KV 8.00 GiB · total 69.65 GiB–71.76 GiB.

Available budget 78.00 GiB after the default reserve.

This page is an estimate unless a matching runtime-resident measurement is attached.

Full-resident weight estimates use total parameters, including inactive MoE experts.
Weight bytes come from the selected weight files only, not from every file in the repository.
Download file size is not peak GPU memory. Runtime layout, allocator padding, and KV are extra.
Counted files: model.safetensors.index.json metadata.total_size.
Context budget is the number of cached tokens per sequence (prompt plus reserved generation).
Concurrent sequences share one model replica; weights are not multiplied by sequence count.
KV dtype is independent of weight quantization unless you change it.
Using 8 KV heads, not 64 query heads.

Pick one model and one device for a conditional judgement.

ModelHardwareQuantizationContext length (cached tokens)Concurrent sequences

Advanced settings

KV cache typeEngineDeploymentDevice countOverhead scenarioSystem / display reserve

GiB (2^30 bytes)

Budget already excludes system reserveExtra safety marginCustom bits per weight Include heavier prefill workspaceDisplay unit

Import local config.json

Parsed in the browser. The file is not uploaded.

Public Hugging Face repoRevision

Only huggingface.co, config.json, no token. Private repos are rejected.

Total parametersActive parametersLayersQuery headsKV headsHead dimension

Estimate

Tight

The estimate is close to the budget, or the range crosses it. Small setting changes can overflow.

Estimated memory range: 69.65 GiB – 71.76 GiB

Weights use selected file metadata. Runtime extras are still estimated.

Weights61.02 GiB

KV cache (raw)8.00 GiB

KV extras (quant metadata / packing)0.00 GiB

Activation / workspace0.13 GiB

Engine reserve0.50 GiB

Safety margin0.00 GiB

Available budget: 78.00 GiB · Remaining after estimate: 6.24 GiB – 8.35 GiB

Documented support. Enough memory does not mean this engine, quant, and OS will run. Support does not mean it will be fast.

Full-resident weight estimates use total parameters, including inactive MoE experts.
Weight bytes come from the selected weight files only, not from every file in the repository.
Download file size is not peak GPU memory. Runtime layout, allocator padding, and KV are extra.
Counted files: model.safetensors.index.json metadata.total_size.
Context budget is the number of cached tokens per sequence (prompt plus reserved generation).
Concurrent sequences share one model replica; weights are not multiplied by sequence count.
KV dtype is independent of weight quantization unless you change it.
Using 8 KV heads, not 64 query heads.
Prefill peak and steady decode occupancy are not the same. The high scenario is closer to prefill/workspace pressure.
Engine reserve is not the same as bytes the model actually uses for weights and KV.
vLLM often preallocates KV from remaining GPU memory. This estimate reports needed KV plus CUDA/graph extras, not the allocator leftover grab.
PagedAttention block alignment can add a small amount above the raw KV payload.
Host RAM is not added to discrete GPU VRAM.