What are the hardware requirements for Devstral Small 2505?

Devstral Small 2505 requires approximately 47.3 GB of VRAM and supports a context window of 128K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Devstral Small 2505 and how large is it?

Devstral Small 2505 is developed by mistralai, a model with 24b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Devstral Small 2505?

Devstral Small 2505 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Devstral Small 2505 by mistralai — VRAM 47.3GB, 128K context

Name: Devstral Small 2505
Author: mistralai

Devstral Small 2505 is an open-source language model by mistralai. Features: 24b LLM, VRAM: 47.3GB, Context: 128K, License: MNPL-0.1, Instruction-Based, LLM Explorer Score: 0.25.

Ar Base model:finetune:mistralai/... Base model:mistralai/mistral-s... Bn De En Es Fa Fr Hi Id Instruct It Ja Ko Mistral Mistral-common Ms Ne Pl Pt Region:us Ro Ru Safetensors Sharded Sr Sv Tensorflow Tr Uk Vi Vllm Zh

Model Card on HF 🤗: https://huggingface.co/mistralai/Devstral-Small-2505

Devstral Small 2505 Parameters and Internals

LLM Name	Devstral Small 2505
Repository 🤗	https://huggingface.co/mistralai/Devstral-Small-2505
Base Model(s)	mistralai/Mistral-Small-3.1-24B-Instruct-2503 mistralai/Mistral-Small-3.1-24B-Instruct-2503
Model Size	24b
Required VRAM	47.3 GB
Updated	2026-07-29
Maintainer	mistralai
Instruction-Based	Yes
Model Files	47.1 GB 4.8 GB: 1-of-10 4.8 GB: 2-of-10 4.8 GB: 3-of-10 4.9 GB: 4-of-10 4.8 GB: 5-of-10 4.8 GB: 6-of-10 4.9 GB: 7-of-10 4.8 GB: 8-of-10 4.8 GB: 9-of-10 3.9 GB: 10-of-10
Supported Languages	en fr de es pt it ja ko ru zh ar fa id ms ne pl ro sr sv tr uk vi hi bn
Model Architecture	MambaSSM
License	MNPL-0.1
Context Length	131072
Model Max Length	131072
Vocabulary Size	131072

Rank the Devstral Small 2505 capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

Quantized Models of the Devstral Small 2505

Model	Likes	Downloads	VRAM
Devstral Small 2505 GGUF	117	2866	0 GB
Devstral Small 2505 4bit	2	854	13 GB
Devstral Small 2505 Bnb 4bit	3	108	14 GB
Devstral Small 2505 8bit	2	93	25 GB
...al Small 2505 Unsloth Bnb 4bit	5	82	15 GB

Best Alternatives to Devstral Small 2505

Best Alternatives	Context / RAM	Downloads	Likes
...tral Small 2 24B Instruct 2512	384K / 51.6 GB	240440	618
...Small 2 24B Instruct 2512 Bf16	384K / 47.8 GB	367	4
...al Small 3.2 24B Instruct 2506	128K / 48.2 GB	312176	602
Devstral Small 2507	128K / 47.3 GB	116445	368
Magistral Small 2509	128K / 48.2 GB	33508	305
...mall 3.2 24B Instruct 2506 FP8	128K / 25.8 GB	81	6
Magistral Small 2506	40K / 47.3 GB	18796	609
Magistral Small 2507	40K / 47.3 GB	632	104
...al Small 3.1 24B Instruct 2503	0K / 48.2 GB	298064	1378
...istral Small 24B Instruct 2501	0K / 47.3 GB	85437	962

Note: green Score (e.g. "73.2") means that the model is better than mistralai/Devstral-Small-2505.