AMD192 GB VRAM5,300 GB/s$2.5/hr

Codestral 25.08 on AMD MI300X 192GB: 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 AMD MI300X 192GB. Every figure is computed by tokcalc's open-source capacity model.

Fits?
Yes, 1 GPU
37.0 GB needed / 192 GB available
Decode speed
234.9
tok/s per stream
Aggregate
2819
tok/s @ 8 concurrent
Cost / 1M tokens
$0.2464
1× AMD MI300X 192GB
What changes as you add AMD MI300X 192GBs
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× AMD192 GB37.0 GB234.92819585.8 ms$0.2464✓
2× AMD384 GB37.0 GB399.39583308.3 ms$0.1449✓
4× AMD768 GB37.0 GB798.638333169.1 ms$0.0725✓
8× AMD1536 GB37.0 GB159715333499.6 ms$0.0362✓
Concurrency vs context length
On 1× AMD MI300X 192GB 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?
4K180962.1 MB✓ fits
8K901.88 GB✓ fits
33K227.52 GB✓ fits
66K1115.03 GB✓ fits
131K530.06 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
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
H100 SXM5 80GB1×1782$0.3898
Frequently asked questions

Can Codestral 25.08 run on AMD MI300X 192GB?

Yes. Codestral 25.08 at FP8 (E4M3) needs 37.0 GB including the KV cache, and AMD MI300X 192GB has 192 GB — so it fits on a single GPU.

How fast is Codestral 25.08 on AMD MI300X 192GB?

234.9 tokens/sec per stream and 2819 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 585.8 ms, and inter-token latency is 4.3 ms.

What does Codestral 25.08 on AMD MI300X 192GB cost per million tokens?

$0.2464 per 1M output tokens at 1× AMD MI300X 192GB ($2.50/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 AMD MI300X 192GB?

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 AMD MI300X 192GB the right choice for Codestral 25.08?

It works. Compare $0.2464 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