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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
All Tesla V100 32GB offers →
Memory · 2 precisions · 5 context lengths

How much VRAM it needs

Weights plus runtime overhead, then the KV cache that grows with the context you serve.

PrecisionWeightsWeights + headroom4k context32k context128k context256k context
FP8published checkpoint128 GB154 GB156 GB166 GB202 GB249 GB
INT4 / MXFP4estimated75 GB90 GB92 GB102 GB138 GB185 GB
KV cacheone sequence, FP16 cache, included above——2 GB12 GB48 GB95 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 ↗
Smallest configuration per GPU · 109 GPUs · cheapest eligible on-demand offer per GPU count, every provider on file

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.

GPUSmallest configVRAM used$ / hour$ / monthCheapest at
Tesla V100 32GBBest fit8× 32 GB256 GB total60%$0.54$391Vast.aiTrust 78 · read Nov 2 · receipt · also Clore.ai $0.69, Edgevana $2.21
A800 80GB PCIe2× 80 GB160 GB total96% tight$0.96$702Vast.aiTrust 78 · read Nov 2 · receipt
Quadro RTX 80004× 48 GB192 GB total80%$1.01$741Vast.aiTrust 78 · read Nov 2 · receipt
RTX 30908× 24 GB192 GB total80%$1.17$851Clore.aiTrust 49 · read Nov 2 · receipt · also Vast.ai $1.29, Lium $2.32
A100 80GB2× 80 GB160 GB total96% tight$1.20$878Vast.aiTrust 78 · read Nov 2 · receipt · also Thunder Compute $2.18, Spheron $2.38
L40S4× 48 GB192 GB total80%$1.52$1,110LiumTrust 40 · read Nov 2 · receipt · also Vast.ai $1.87, VoltageGPU $3.04
A100 40GB4× 40 GB160 GB total96% tight$1.60$1,170Vast.aiTrust 78 · read Nov 2 · receipt · also iwinv $3.66, AtmosCompute $4.05
MI300X1× 192 GB192 GB total80%$1.65$1,205GPUBankTrust 93 · read Oct 25 · receipt · also OpenRelay $1.99, Runpod $2.39
RTX PRO 60002× 96 GB192 GB total80%$1.67$1,218Vast.aiTrust 78 · read Nov 2 · receipt · also UpCloud $1.94, GPU.ai $3.38
RTX A60004× 48 GB192 GB total80%$1.68$1,226LiumTrust 40 · read Nov 2 · receipt · also Spheron $1.77, Vast.ai $1.82
RTX PRO 50004× 48 GB192 GB total80%$1.92$1,403Vast.aiTrust 78 · read Nov 2 · receipt · also Edgevana $4.60, iwinv $6.66
RTX PRO 40008× 24 GB192 GB total80%$1.93$1,406Vast.aiTrust 78 · read Nov 2 · receipt · also Edgevana $2.15, AtmosCompute $3.37
H100 NVL2× 94 GB188 GB total82%$2.08$1,521Clore.aiTrust 49 · read Nov 2 · receipt · also Vast.ai $5.23, AtmosCompute $8.93
Gaudi 22× 96 GB192 GB total80%$2.11$1,538Cyfuture AInot scored · read Nov 2 · receipt
RTX 4000 Ada8× 20 GB160 GB total96% tight$2.14$1,559Vast.aiTrust 78 · read Nov 2 · receipt
MI325X1× 256 GB256 GB total60%$2.25$1,643OpenRelaynot scored · read Nov 2 · receipt · also Cyfuture AI $3.14, DigitalOcean $3.80
A404× 48 GB192 GB total80%$2.30$1,676Vast.aiTrust 78 · read Nov 2 · receipt · also Denvr Cloud $2.60, Edgevana $3.01
A100X2× 80 GB160 GB total96% tight$2.56$1,870Vast.aiTrust 78 · read Nov 2 · receipt
RTX 6000 Ada4× 48 GB192 GB total80%$2.60$1,898GPU.ainot scored · read Nov 2 · receipt · also io.net $2.73, QuantaCloud $3.11
L404× 48 GB192 GB total80%$2.65$1,932io.netTrust 42 · read Nov 2 · receipt · also GPU.ai $3.12, QuantaCloud $3.75
RTX 40908× 24 GB192 GB total80%$3.07$2,241Edgevananot scored · read Nov 2 · receipt · also Sesterce Cloud $3.52, Vast.ai $3.63
H1002× 80 GB160 GB total96% tight$3.42$2,496GcoreTrust 80 · read Nov 2 · receipt · also GPU.ai $3.96, UpCloud $4.00
B2001× 180 GB180 GB total85%$3.75$2,738packet.ainot scored · read Nov 2 · receipt · also Beam $4.11, UpCloud $4.11
RTX 50908× 32 GB256 GB total60%$3.84$2,804Vast.aiTrust 78 · read Nov 2 · receipt · also Lium $4.00, Edgevana $5.28
The 24 cheapest of 37 GPU types that fit. Every GPU, any precision and context, in the finder
Throughput estimates · Oct 4, 2026

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.

GPUCardsPrecisiontok/s per userper 1M output tokens · estimate
MI300X1FP821.5$0.885
B2001FP839.5$1.28
H2002FP838.5$1.43
RTX PRO 60002FP813.9$1.79
L40S4FP811.0$1.94
H100 SXM2FP828.9$3.04
A100 80GB2FP818.5$3.86
H100 PCIe2FP815.0$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 →