Devstral Small (May '25)
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Devstral Small (May '25)

Original May 2025 release of Devstral Small, Mistral AI's first open-source coding agent model. 24B parameters achieving 46.8% on SWE-Bench Verified, outperforming GPT-4.1-mini by over 20 percentage points. Released under Apache 2.0 license, runs on single GPU, established foundation for open-source solutions in coding agents and software engineering tasks.
Intelligence(Relatively Weak)
Speed(Medium)
Input Supported Modalities
No
Is Reasoning Model
256,000
Context Window
128,000
Maximum Output Tokens
-
Knowledge Cutoff

Pricing

¥0.72 /M tokens
Input
¥2.16 /M tokens
Output
¥1.08 /M tokens
Blended Price

Quick Simple Comparison

Input

Output

Devstral
¥0.1
Devstral Medium
¥0.4
Devstral Small (May '25)
¥0.1

Basic Parameters

Devstral Small (May '25)Technical Parameters
Parameter Count
24,000.0M
Context Length
256.00k tokens
Training Data Cutoff
Open Source Category
Open Weights (Permissive License)
Multimodal Support
Text Only
Throughput
137
Release Date
2025-05-21
Response Speed
147.68,123 tokens/s

Benchmark Scores

Below is the performance of Devstral Small (May '25) in various standard benchmark tests. These tests evaluate the model's capabilities in different tasks and domains.
Intelligence Index
34.11
Large Language Model Intelligence Level
Coding Index
25.18
Indicator of AI model performance on coding tasks
Math Index
37.53
Capability indicator in solving mathematical problems, mathematical reasoning, or performing math-related tasks
MMLU Pro
63.2
Massive Multitask Multimodal Understanding - Testing understanding of text, images, audio, and video
GPQA
43.4
Graduate Physics Questions Assessment - Testing advanced physics knowledge with diamond science-level questions
HLE
4
The model's comprehensive average score on the Hugging Face Open LLM Leaderboard
LiveCodeBench
25.8
Specific evaluation focused on assessing large language models' ability in real-world code writing and solving programming competition problems
SciCode
24.5
The model's capability in code generation for scientific computing or specific scientific domains
HumanEval
84.8
Score achieved by the AI model on the specific HumanEval benchmark test set
Math 500 Score
68.4
Score on the first 500 larger, more well-known mathematical benchmark tests
AIME Score
6.7
An indicator measuring an AI model's ability to solve high-difficulty mathematical competition problems (specifically AIME level)
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