Mistral AI · Code · 24B parameters · apache-2.0
Devstral Small 2 24B Instruct 2512
Needs 31 GB at FP8 / INT8. The smallest real configuration today is 1× Tesla V100 32GB at Vast.ai, $0.07 per hour, about $50 a month at 730 hours.
Parameters24Bdense
Context384k tokensmaximum published
Checkpoint26 GBFP8, as published
Licenseapache-2.0check before commercial use
Released—documented date
Smallest configuration · FP8 / INT8
1× Tesla V100 32GB32 GB VRAM · 97% used
- Per hour
- $0.07
- Per month
- $50
- Cheapest at
Vast.ai
How much VRAM it needs
Weights plus runtime overhead, then the KV cache that grows with the context you serve.
| Precision | Weights | Weights + headroom | 4k context | 32k context | 128k context | 256k context | 384k context |
|---|---|---|---|---|---|---|---|
| FP8published checkpoint | 26 GB | 31 GB | 32 GB | 37 GB | 53 GB | 74 GB | 96 GB |
| INT4 / MXFP4estimated | 14 GB | 18 GB | 18 GB | 23 GB | 39 GB | 61 GB | 82 GB |
| KV cacheone sequence, FP16 cache, included above | — | — | 1 GB | 6 GB | 22 GB | 43 GB | 65 GB |
Cross-checked on Hugging Face Oct 28, 2026: 24.0B parameters in the safetensors headers, 25.8 GB of weight files, attention layout from config.json (40 layers, 8 KV heads × 128). Method: weights as published at the native precision, verified on Hugging Face 2026-10-28; other precisions estimated at 1 (8-bit) and 0.6 (4-bit) bytes per parameter; × 1.2 runtime headroom; KV cache = 4096 bytes per token per layer × 40 full-attention layers (FP16 cache, one sequence).config.json ↗
What it costs to run, GPU by GPU
The fewest GPUs of one type whose total memory fits the model at short context, priced from the cheapest eligible on-demand offer for exactly that count (45-day window, newest reading per provider), with the next providers beside it. Monthly = 730 hours.
| GPU | Smallest config | VRAM used | $ / hour | $ / month | Cheapest at |
|---|---|---|---|---|---|
| Tesla V100 32GBBest fit | 1× 32 GB32 GB total | 97% tight | $0.07 | $50 | |
| T4 | 2× 16 GB32 GB total | 97% tight | $0.08 | $59 | |
| Tesla P100 | 2× 16 GB32 GB total | 97% tight | $0.10 | $70 | |
| RTX A4000 | 2× 16 GB32 GB total | 97% tight | $0.14 | $105 | |
| RTX PRO 2000 | 2× 16 GB32 GB total | 97% tight | $0.15 | $106 | |
| Tesla V100 16GB | 2× 16 GB32 GB total | 97% tight | $0.16 | $118 | |
| RTX 3060 | 4× 12 GB48 GB total | 65% | $0.16 | $119 | |
| RTX 5060 Ti | 2× 16 GB32 GB total | 97% tight | $0.19 | $137 | |
| Quadro RTX 5000 | 2× 16 GB32 GB total | 97% tight | $0.20 | $148 | |
| RTX 3090 | 2× 24 GB48 GB total | 65% | $0.21 | $157 | |
| GTX 1080 | 4× 8 GB32 GB total | 97% tight | $0.22 | $157 | |
| RTX 2070 | 4× 8 GB32 GB total | 97% tight | $0.22 | $157 | |
| RTX 3060 Ti | 4× 8 GB32 GB total | 97% tight | $0.22 | $159 | |
| GTX 1070 Ti | 4× 8 GB32 GB total | 97% tight | $0.23 | $169 | |
| RTX 5090 | 1× 32 GB32 GB total | 97% tight | $0.24 | $172 | |
| RTX 2070 Super | 4× 8 GB32 GB total | 97% tight | $0.24 | $177 | |
| Quadro RTX 8000 | 1× 48 GB48 GB total | 65% | $0.25 | $186 | |
| RTX 6000 | 2× 24 GB48 GB total | 65% | $0.27 | $196 | |
| Titan RTX | 2× 24 GB48 GB total | 65% | $0.27 | $196 | |
| Titan Xp | 4× 12 GB48 GB total | 65% | $0.27 | $196 | |
| L40 | 1× 48 GB48 GB total | 65% | $0.27 | $196 | |
| RTX 2080 Ti | 4× 11 GB44 GB total | 70% | $0.28 | $202 | |
| RTX 3070 | 4× 8 GB32 GB total | 97% tight | $0.29 | $213 | |
| RTX 4070 Ti Super | 2× 16 GB32 GB total | 97% tight | $0.30 | $216 | |
| The 24 cheapest of 83 GPU types that fit. Every GPU, any precision and context, in the finder | |||||
Tokens per second, and what a million costs
Code. Speed estimated from memory bandwidth and model size, never measured. The cost per 1M output tokens is an estimate at the prices read on Oct 4, 2026; it is not recomputed here.
| GPU | Cards | Precision | tok/s per user | per 1M output tokens · estimate |
|---|---|---|---|---|
| MI300X | 1 | FP8 | 90.3 | $0.193 |
| RTX 4090 | 2 | FP8 | 36.1 | $0.206 |
| H100 SXM | 1 | FP8 | 77.1 | $0.245 |
| B200 | 1 | FP8 | 156 | $0.253 |
| RTX 5090 | 2 | FP8 | 57.5 | $0.253 |
| H100 PCIe | 1 | FP8 | 49.1 | $0.265 |
| L40S | 1 | FP8 | 22.7 | $0.277 |
| H200 | 1 | FP8 | 103 | $0.280 |
| RTX PRO 6000 | 1 | FP8 | 44.7 | $0.282 |
| A100 80GB | 1 | FP8 | 49.7 | $0.457 |
cards, precision and speed estimated from memory bandwidth and model size; cost recomputed by the site from verified prices · cheapest per output at the prices of Oct 4, 2026: MI300XWhy estimates, and their limits →
