Mistral AI · Code · 125B parameters · Modified MIT
Devstral 2 123B Instruct 2512
Needs 154 GB at FP8 / INT8. The smallest real configuration today is 8× Tesla V100 32GB at Vast.ai, $0.54 per hour, about $391 a month at 730 hours.
Parameters125Bdense
Context256k tokensmaximum published
Checkpoint128 GBFP8, as published
LicenseModified MITcheck before commercial use
Released—documented date
Smallest configuration · FP8 / INT8
8× Tesla V100 32GB256 GB VRAM · 60% used
- Per hour
- $0.54
- Per month
- $391
- 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 |
|---|---|---|---|---|---|---|
| FP8published checkpoint | 128 GB | 154 GB | 156 GB | 166 GB | 202 GB | 249 GB |
| INT4 / MXFP4estimated | 75 GB | 90 GB | 92 GB | 102 GB | 138 GB | 185 GB |
| KV cacheone sequence, FP16 cache, included above | — | — | 2 GB | 12 GB | 48 GB | 95 GB |
Cross-checked on Hugging Face Oct 28, 2026: 125.0B parameters in the safetensors headers, 128.3 GB of weight files, attention layout from config.json (88 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 × 88 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 | 8× 32 GB256 GB total | 60% | $0.54 | $391 | |
| A800 80GB PCIe | 2× 80 GB160 GB total | 96% tight | $0.96 | $702 | |
| Quadro RTX 8000 | 4× 48 GB192 GB total | 80% | $1.01 | $741 | |
| RTX 3090 | 8× 24 GB192 GB total | 80% | $1.17 | $851 | |
| A100 80GB | 2× 80 GB160 GB total | 96% tight | $1.20 | $878 | |
| L40S | 4× 48 GB192 GB total | 80% | $1.52 | $1,110 | |
| A100 40GB | 4× 40 GB160 GB total | 96% tight | $1.60 | $1,170 | |
| MI300X | 1× 192 GB192 GB total | 80% | $1.65 | $1,205 | |
| RTX PRO 6000 | 2× 96 GB192 GB total | 80% | $1.67 | $1,218 | |
| RTX A6000 | 4× 48 GB192 GB total | 80% | $1.68 | $1,226 | |
| RTX PRO 5000 | 4× 48 GB192 GB total | 80% | $1.92 | $1,403 | |
| RTX PRO 4000 | 8× 24 GB192 GB total | 80% | $1.93 | $1,406 | |
| H100 NVL | 2× 94 GB188 GB total | 82% | $2.08 | $1,521 | |
| Gaudi 2 | 2× 96 GB192 GB total | 80% | $2.11 | $1,538 | |
| RTX 4000 Ada | 8× 20 GB160 GB total | 96% tight | $2.14 | $1,559 | |
| MI325X | 1× 256 GB256 GB total | 60% | $2.25 | $1,643 | |
| A40 | 4× 48 GB192 GB total | 80% | $2.30 | $1,676 | |
| A100X | 2× 80 GB160 GB total | 96% tight | $2.56 | $1,870 | |
| RTX 6000 Ada | 4× 48 GB192 GB total | 80% | $2.60 | $1,898 | |
| L40 | 4× 48 GB192 GB total | 80% | $2.65 | $1,932 | |
| RTX 4090 | 8× 24 GB192 GB total | 80% | $3.07 | $2,241 | |
| H100 | 2× 80 GB160 GB total | 96% tight | $3.42 | $2,496 | |
| B200 | 1× 180 GB180 GB total | 85% | $3.75 | $2,738 | |
| RTX 5090 | 8× 32 GB256 GB total | 60% | $3.84 | $2,804 | |
| The 24 cheapest of 37 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 | 21.5 | $0.885 |
| B200 | 1 | FP8 | 39.5 | $1.28 |
| H200 | 2 | FP8 | 38.5 | $1.43 |
| RTX PRO 6000 | 2 | FP8 | 13.9 | $1.79 |
| L40S | 4 | FP8 | 11.0 | $1.94 |
| H100 SXM | 2 | FP8 | 28.9 | $3.04 |
| A100 80GB | 2 | FP8 | 18.5 | $3.86 |
| H100 PCIe | 2 | FP8 | 15.0 | $4.09 |
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 →
