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MistralMistral

Devstral Small 1.1

Aktuell
huggingfaceHuggingFace
45.2KDownloads365LikesJul 2025Veröffentlicht131K TokenKontextApache 2.0Lizenz92 HerausragendQualität

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.

Loslegen

— kopieren & einfügen, um lokal auszuführen

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

Verwandte Modelle

Deine Hardware

Erkennung...

Schnellauswahl

Intel
Bestes BudgetS
Intel Arc Pro B60 24GB~$599 — 18 tok/s
NVIDIA
Beste GesamtwahlS
RTX 5090 32GB~$1,999 — 88 tok/s

Beste Hardware

Top-Empfehlungen für Devstral Small 1.1

NVIDIA
RTX 5090 32GBS
32 GB
NVIDIA
RTX PRO 4500 Blackwell 32GBS
32 GB
AMD Instinct MI100 32GBS
32 GB
NVIDIA
NVIDIA V100 32GBS
32 GB
NVIDIA
NVIDIA A100 40GBS
40 GB

Dieses Modell ausführen

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

Quantisierungsoptionen

VRAM-Schätzungen nach Quantisierungsstufe

No hardware detected — fit column shows raw VRAM estimates

QuantBitsVRAMQualityFit
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

Devstral Small 1.1 benchmark scores

Benchmark verified

Coding

SWE-bench Verified38.0%
HumanEval+—
Aider Polyglot—
LiveCodeBench—

Hardware-Kompatibilität

Eignungsschätzungen für alle Hardware

Rechner öffnen

Computing compatibility...

Speicheraufschlüsselung

Reference: RTX 2060 6GB

Weights14.6 GB
KV Cache2.4 GB
Runtime1.2 GB
Headroom0.6 GB

Häufig gestellte Fragen

FAQ — Devstral Small 1.1

Siehe auch

QuantisierungsleitfadenBewertungsmethodikRechner öffnen