NVIDIA80 GB VRAM3,350 GB/s$2.5/hr

Qwen 3 30B-A3B (MoE) on H100 SXM5 80GB: Does It Fit, How Fast, What It Costs

Qwen 3 30B-A3B (MoE) at FP8 (E4M3) needs 30.0 GB for its weights and 36.4 GB in total at 8K context with 8 concurrent users. That means it fits on a single H100 SXM5 80GB. Every figure is computed by tokcalc's open-source capacity model.

Fits?
Yes, 1 GPU
36.4 GB needed / 80 GB available
Decode speed
1089
tok/s per stream
Aggregate
13065
tok/s @ 8 concurrent
Cost / 1M tokens
$0.0532
1× H100 SXM5 80GB
What changes as you add H100 SXM5 80GBs
Tensor-parallel degree vs VRAM, throughput, and cost. Cost scales linearly with GPU count; decode throughput scales near-linearly too, so cost per token stays roughly flat.
GPUsTotal VRAMVRAM neededDecode tok/sAggregate tok/sTTFTCost / 1M tokFits?
1× H10080 GB36.4 GB108913065130.2 ms$0.0532✓
2× H100160 GB36.4 GB18514442180.2 ms$0.0313✓
4× H100320 GB36.4 GB370217768455.1 ms$0.0156✓
8× H100640 GB36.4 GB740471073642.5 ms$0.007817✓
Concurrency vs context length
On 1× H100 SXM5 80GB at FP8 (E4M3). KV cache scales linearly with context, so this is the number of users your GPUs can actually serve.
ContextConcurrent usersKV per requestFits?
4K124412.3 MB✓ fits
8K62824.6 MB✓ fits
33K153.22 GB✓ fits
66K76.44 GB✓ fits
131K312.88 GB✓ fits
Other GPUs that run Qwen 3 30B-A3B (MoE)
Same workload, same quantization — ranked by value (tokens per dollar-hour).
GPUGPUsAggregate tok/sCost / 1M tok
RTX 5090 32GB2×23762$0.0117
AMD MI300X 192GB1×20670$0.0336
A100 40GB SXM41×6045$0.0414
AMD MI325X 288GB1×23400$0.0415
A100 80GB SXM41×7800$0.0427
Intel Gaudi 3 128GB1×12870$0.0432
Frequently asked questions

Can Qwen 3 30B-A3B (MoE) run on H100 SXM5 80GB?

Yes. Qwen 3 30B-A3B (MoE) at FP8 (E4M3) needs 36.4 GB including the KV cache, and H100 SXM5 80GB has 80 GB — so it fits on a single GPU.

How fast is Qwen 3 30B-A3B (MoE) on H100 SXM5 80GB?

1089 tokens/sec per stream and 13065 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 130.2 ms, and inter-token latency is 918.5 µs.

What does Qwen 3 30B-A3B (MoE) on H100 SXM5 80GB cost per million tokens?

$0.0532 per 1M output tokens at 1× H100 SXM5 80GB ($2.50/hr). That is the marginal hardware cost — add idle capacity, ops, and egress for the real figure.

How much VRAM does Qwen 3 30B-A3B (MoE) need on H100 SXM5 80GB?

30.0 GB for the weights at FP8 (E4M3), plus 6.4 GB of KV cache for 8 concurrent requests at 8K context — 36.4 GB total. Every extra concurrent user at long context costs more, so leave headroom.

Is H100 SXM5 80GB the right choice for Qwen 3 30B-A3B (MoE)?

It works. Compare $0.0532 per 1M tokens against the alternatives below — the cheapest option that fits the same workload is 4× RTX 3080 10GB at $0.005513, and the fastest is 1× Cerebras CS-3 (WSE-3) at 78000 tok/s.

Adjust the workload yourself

Same formulas, your context length, concurrency, and quantisation.

Open in calculator