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 MI325X 288GB. Every figure is computed by tokcalc's open-source capacity model.
| GPUs | Total VRAM | VRAM needed | Decode tok/s | Aggregate tok/s | TTFT | Cost / 1M tok | Fits? |
|---|---|---|---|---|---|---|---|
| 1× AMD | 288 GB | 37.0 GB | 265.9 | 3191 | 585.3 ms | $0.3047 | ✓ |
| 2× AMD | 576 GB | 37.0 GB | 452.0 | 10849 | 308.0 ms | $0.1792 | ✓ |
| 4× AMD | 1152 GB | 37.0 GB | 904.1 | 43396 | 169.0 ms | $0.0896 | ✓ |
| 8× AMD | 2304 GB | 37.0 GB | 1808 | 173585 | 99.5 ms | $0.0448 | ✓ |
| Context | Concurrent users | KV per request | Fits? |
|---|---|---|---|
| 4K | 283 | 962.1 MB | ✓ fits |
| 8K | 141 | 1.88 GB | ✓ fits |
| 33K | 35 | 7.52 GB | ✓ fits |
| 66K | 17 | 15.03 GB | ✓ fits |
| 131K | 8 | 30.06 GB | ✓ fits |
| GPU | GPUs | Aggregate tok/s | Cost / 1M tok |
|---|---|---|---|
| RTX 5090 32GB | 2× | 3240 | $0.0857 |
| AMD MI300X 192GB | 1× | 2819 | $0.2464 |
| A100 40GB SXM4 | 1× | 824.3 | $0.3033 |
| A100 80GB SXM4 | 1× | 1064 | $0.3134 |
| Intel Gaudi 3 128GB | 1× | 1755 | $0.3166 |
| H100 SXM5 80GB | 1× | 1782 | $0.3898 |
Yes. Codestral 25.08 at FP8 (E4M3) needs 37.0 GB including the KV cache, and AMD MI325X 288GB has 288 GB — so it fits on a single GPU.
265.9 tokens/sec per stream and 3191 tok/s aggregate with continuous batching at 8 concurrent users. Time to first token is 585.3 ms, and inter-token latency is 3.8 ms.
$0.3047 per 1M output tokens at 1× AMD MI325X 288GB ($3.50/hr). That is the marginal hardware cost — add idle capacity, ops, and egress for the real figure.
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.
It works. Compare $0.3047 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.
Same formulas, your context length, concurrency, and quantisation.