Devstral-2 22B (Unverified Listing) — VRAM, Speed & Local Setup

Autor: Jakub Rusinowski · Ostatnia aktualizacja: 11 września 2026

Model libraryDevstral → Devstral-2 22B (Unverified Listing)

UNVERIFIED — retained only because this URL has been live and holds inbound links. Mistral shipped Devstral 2 in two sizes, Devstral 2 123B and Devstral Small 2 24B; no 22B Devstral 2 checkpoint appears under mistralai on Hugging Face or in the Devstral 2 announcement. The figures below were published here without sources. If you came looking for the consumer-GPU Devstral, you want Devstral Small 2 24B below — 68.0% on SWE-bench Verified at about 15 GB.

Devstral-2 22B (Unverified Listing) needs about 14 GB of VRAM at Q4_K_M — quantized weights plus framework overhead, before any KV cache. On Apple Silicon that figure comes out of unified memory.

Specifications

Parameters22 Billion (unverified)
Context window128,000
ArchitectureDense Transformer
ProviderMistral AI
LicenceApache 2.0
Specified atQ4_K_M
System RAM32 GB
Record updated2026-09-11

Licence

Apache-2.0commercial use permitted. Commercial use permitted. No usage restrictions beyond attribution.

VRAM and Speed by Quantization

Modelled on a reference NVIDIA RTX 4090 (24 GB). Weights plus framework overhead only — this model publishes no architecture we can read, so no KV cache is included. A real session needs more; the figure is a floor, not a target. Speed figures are ESTIMATES from the memory-bandwidth roofline described on the methodology page, not benchmarks we ran — rows marked measured come from published or reader-submitted runs. VRAM here includes the KV cache, so it reads higher than the headline figure above, which does not.

QuantBits/weightWeightsVRAM neededEst. speedFit on 24 GB
Q2_K2.637.2 GB8 GB~78 tok/s (est.)Fits comfortably
Q3_K_M3.419.4 GB10.2 GB~64 tok/s (est.)Fits comfortably
Q4_K_M4.8313.3 GB14.1 GB~48 tok/s (est.)Fits comfortably
Q5_K_M5.6715.6 GB16.4 GB~42 tok/s (est.)Fits comfortably
Q6_K6.5618 GB18.8 GB~37 tok/s (est.)Fits comfortably
Q8_08.5023.4 GB24.2 GB~4 tok/s (est.)Offloads to system RAM (slow)
F1616.0044 GB44.8 GB~2 tok/s (est.)Offloads to system RAM (slow)

Want to set your own context length and KV-cache quantization? Use the interactive VRAM calculator.

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Recommended GPU

The cheapest catalogued GPU that runs Devstral-2 22B (Unverified Listing) is the AMD Radeon RX 9060 XT 16GB (16 GB).

Ujawnienie afiliacyjne: Niektóre odnośniki na tej stronie to linki afiliacyjne — jeśli dokonasz zakupu za ich pośrednictwem, LLM Configurator może otrzymać prowizję bez dodatkowych kosztów dla Ciebie. Jako uczestnik programu Amazon Associates, LLM Configurator zarabia na kwalifikujących się zakupach.
AMD Radeon RX 9060 XT 16GB
16 GB VRAM · 160 W board power
Ceny w 2026 są niestabilne — sprawdź aktualną ofertę.
Sprawdź cenę na Amazon

How to Run Devstral-2 22B (Unverified Listing)

Install Ollama, then run:

ollama run devstral-2

Weights on Hugging Face: mistralai/Devstral-2-22B.

Best for: software engineering, coding, consumer gpu, local inference.

Can I Run Devstral-2 22B (Unverified Listing) on My GPU?

Other Devstral Sizes

Devstral-2 22B (Unverified Listing) — Frequently Asked Questions

How much VRAM does Devstral-2 22B (Unverified Listing) need?
About 14 GB at Q4_K_M — quantized weights plus framework overhead, before any KV cache. The cache grows with context length and is added on top; the table above folds it in. Apple Silicon counts unified memory toward the same figure.
Does Devstral-2 22B (Unverified Listing) run on an RTX 4090 (24 GB)?
Yes. Devstral-2 22B (Unverified Listing) needs about 14 GB at Q4_K_M, inside a 24 GB card, at an estimated 48 tokens/sec.
How do I run Devstral-2 22B (Unverified Listing) locally?
Install Ollama and run `ollama run devstral-2`. That pulls the weights and starts a local OpenAI-compatible endpoint; after the download nothing leaves the machine.
What other sizes does Devstral come in?
Devstral-2 123B (75 GB), Devstral-2 22B (Unverified Listing) (14 GB), Devstral Small 2505 24B (15 GB), Devstral Small 2 24B (15 GB). Every size shares the family's training and licence; the larger ones score higher and need proportionally more memory.

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