NVIDIA80 GB VRAM2,000 GB/s$2/hr

Codestral 25.08 on H100 PCIe 80GB: Does It Fit, How Fast, What It Costs

Codestral 25.08 at FP8 (E4M3) needs 22.0 GB for its weights and 37.0 GB in total at 8K context with 8 concurrent users. That means it fits on a single H100 PCIe 80GB. Every figure is computed by tokcalc's open-source capacity model.

Fits?
Yes, 1 GPU
37.0 GB needed / 80 GB available
Decode speed
88.64
tok/s per stream
Aggregate
1064
tok/s @ 8 concurrent
Cost / 1M tokens
$0.5223
1× H100 PCIe 80GB
What changes as you add H100 PCIe 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 GB37.0 GB88.641064994.8 ms$0.5223✓
2× H100160 GB37.0 GB150.73616513.4 ms$0.3072✓
4× H100320 GB37.0 GB301.414465271.7 ms$0.1536✓
8× H100640 GB37.0 GB602.757862150.9 ms$0.0768✓
Concurrency vs context length
On 1× H100 PCIe 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?
4K61962.1 MB✓ fits
8K301.88 GB✓ fits
33K77.52 GB✓ fits
66K315.03 GB✓ fits
131K130.06 GB✓ fits
Other GPUs that run Codestral 25.08
Same workload, same quantization — ranked by value (tokens per dollar-hour).
GPUGPUsAggregate tok/sCost / 1M tok
RTX 5090 32GB2×3240$0.0857
AMD MI300X 192GB1×2819$0.2464
A100 40GB SXM41×824.3$0.3033
AMD MI325X 288GB1×3191$0.3047
A100 80GB SXM41×1064$0.3134
Intel Gaudi 3 128GB1×1755$0.3166
Frequently asked questions

Can Codestral 25.08 run on H100 PCIe 80GB?

Yes. Codestral 25.08 at FP8 (E4M3) needs 37.0 GB including the KV cache, and H100 PCIe 80GB has 80 GB — so it fits on a single GPU.

How fast is Codestral 25.08 on H100 PCIe 80GB?

88.64 tokens/sec per stream and 1064 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 994.8 ms, and inter-token latency is 11.3 ms.

What does Codestral 25.08 on H100 PCIe 80GB cost per million tokens?

$0.5223 per 1M output tokens at 1× H100 PCIe 80GB ($2.00/hr). That is the marginal hardware cost — add idle capacity, ops, and egress for the real figure.

How much VRAM does Codestral 25.08 need on H100 PCIe 80GB?

22.0 GB for the weights at FP8 (E4M3), plus 15.0 GB of KV cache for 8 concurrent requests at 8K context — 37.0 GB total. Every extra concurrent user at long context costs more, so leave headroom.

Is H100 PCIe 80GB the right choice for Codestral 25.08?

It works. Compare $0.5223 per 1M tokens against the alternatives below — the cheapest option that fits the same workload is 4× RTX 3080 10GB at $0.0404, and the fastest is 1× Cerebras CS-3 (WSE-3) at 10636 tok/s.

Adjust the workload yourself

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

Open in calculator