NVIDIA141 GB VRAM4,800 GB/s$4/hr

GPT-OSS 120B (MoE) on H200 SXM5 141GB: Does It Fit, How Fast, What It Costs

GPT-OSS 120B (MoE) at AWQ 4-bit needs 64.3 GB for its weights and 66.7 GB in total at 8K context with 8 concurrent users. That means it fits on a single H200 SXM5 141GB. Every figure is computed by tokcalc's open-source capacity model.

Fits?
Yes, 1 GPU
66.7 GB needed / 141 GB available
Decode speed
978.8
tok/s per stream
Aggregate
11746
tok/s @ 8 concurrent
Cost / 1M tokens
$0.0946
1× H200 SXM5 141GB
What changes as you add H200 SXM5 141GBs
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× H200141 GB66.7 GB978.811746199.8 ms$0.0946✓
2× H200282 GB66.7 GB166439936115.0 ms$0.0556✓
4× H200564 GB66.7 GB332815974472.5 ms$0.0278✓
8× H2001128 GB66.7 GB665663897651.3 ms$0.0139✓
Concurrency vs context length
On 1× H200 SXM5 141GB at AWQ 4-bit. KV cache scales linearly with context, so this is the number of users your GPUs can actually serve.
ContextConcurrent usersKV per requestFits?
4K492309.2 MB✓ fits
8K250618.5 MB✓ fits
33K632.42 GB✓ fits
66K314.83 GB✓ fits
131K159.66 GB✓ fits
Other GPUs that run GPT-OSS 120B (MoE)
Same workload, same quantization — ranked by value (tokens per dollar-hour).
GPUGPUsAggregate tok/sCost / 1M tok
RTX 5090 32GB4×59638$0.009316
AMD MI300X 192GB1×12969$0.0535
L40S 48GB2×7188$0.0541
AMD MI325X 288GB1×14682$0.0662
A100 80GB SXM41×4894$0.0681
Intel Gaudi 3 128GB1×8075$0.0688
Frequently asked questions

Can GPT-OSS 120B (MoE) run on H200 SXM5 141GB?

Yes. GPT-OSS 120B (MoE) at AWQ 4-bit needs 66.7 GB including the KV cache, and H200 SXM5 141GB has 141 GB — so it fits on a single GPU.

How fast is GPT-OSS 120B (MoE) on H200 SXM5 141GB?

978.8 tokens/sec per stream and 11746 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 199.8 ms, and inter-token latency is 1.0 ms.

What does GPT-OSS 120B (MoE) on H200 SXM5 141GB cost per million tokens?

$0.0946 per 1M output tokens at 1× H200 SXM5 141GB ($4.00/hr). That is the marginal hardware cost — add idle capacity, ops, and egress for the real figure.

How much VRAM does GPT-OSS 120B (MoE) need on H200 SXM5 141GB?

64.3 GB for the weights at AWQ 4-bit, plus 2.5 GB of KV cache for 8 concurrent requests at 8K context — 66.7 GB total. Every extra concurrent user at long context costs more, so leave headroom.

Is H200 SXM5 141GB the right choice for GPT-OSS 120B (MoE)?

It works. Compare $0.0946 per 1M tokens against the alternatives below — the cheapest option that fits the same workload is 8× RTX 3080 10GB at $0.004393, and the fastest is 2× Cerebras CS-3 (WSE-3) at 166400 tok/s.

Adjust the workload yourself

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

Open in calculator