Devstral Small 1.1

Current

4.6KDownloads366LikesJul 2025Released131K tokensContextApache 2.0License92 ExceptionalQuality

Devstral Small 1.1 (24B parameters) requires approximately 18.9 GB of VRAM with Q4_K_M quantization. For the best balance of quality and speed, we recommend hardware with at least 22 GB of VRAM.

Get started

— copy & paste to run locally

Copy-paste commands to run Devstral Small 1.1 on your machine.

Run

lms load Devstral-Small-2507 && lms server start

Quick specs

Parameters24B

Architecturedense

Context131K tokens

Modalitytext

Min RAM9.4 GB

Rec. RAM14.6 GB (Q4_K_M)

LicenseApache 2.0

FamilyDevstral Small

✓ Code✓ Reasoning

About this model

Devstral is an agentic LLM for software engineering tasks built under a collaboration between Mistral AI and All Hands AI 🙌. Devstral excels at using tools to explore codebases, editing multiple files and power software engineering agents. The model achieves remarkable performance on SWE-bench which positions it as the #1 open source model on this benchmark.

•Agentic coding: Devstral is designed to excel at agentic coding tasks, making it a great choice for software engineering agents
•lightweight: with its compact size of just 24 billion parameters, Devstral is light enough to run on a single RTX 4090 or a Mac with 32GB RAM,...
•Apache 2.0 License: Open license allowing usage and modification for both commercial and non-commercial purposes
•Context Window: A 128k context window
•Tokenizer: Utilizes a Tekken tokenizer with a 131k vocabulary size

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Best hardware

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Run this model

Devstral Small 1.1 on RTX 5090 32GB Devstral Small 1.1 on RTX PRO 4500 Blackwell 32GB Devstral Small 1.1 on AMD Instinct MI100 32GB

Quantization options

VRAM estimates by quant level

No hardware detected — fit column shows raw VRAM estimates

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	9.4 GB	Low	—
Q3_K_S	3	11.8 GB	Low	—
NVFP4	4	13.4 GB	Medium	—
Q4_K_M	4	14.6 GB	Medium	—
Q5_K_M	5	17.3 GB	High	—
Q6_K	6	19.7 GB	High	—
Q8_0	8	25.7 GB	Very High	—
F16	16	49.2 GB	Maximum	—

Quality benchmarks