# Devstral: Fine-tuning Language Models for Coding Agent Applications

arXiv: https://arxiv.org/abs/2509.25193 · HTML: https://mlsanity.com/paper/2509.25193/

## Key facts

- Cited by 24 papers in the map (data through 14 Oct 2026).
- Placed in Software engineering coding agents, one of 16 directions in LLM agents and tool use.
- Builds on 10 of its 13 references that are in the map.
- First posted on arXiv 8 Aug 2025.

## Placed in

- LLM agents and tool use / [Software engineering coding agents](https://mlsanity.com/agents/software-engineering-coding-agents/)

## Builds on (most cited first, 10 of 10)

- [Chain-of-Thought Prompting Elicits Reasoning in Large Language Models](https://mlsanity.com/paper/2201.11903/) (2022)
- [Evaluating Large Language Models Trained on Code](https://mlsanity.com/paper/2107.03374/) (2021)
- [Efficient Memory Management for Large Language Model Serving with PagedAttention](https://mlsanity.com/paper/2309.06180/) (2023)
- [Program Synthesis with Large Language Models](https://mlsanity.com/paper/2108.07732/) (2021)
- [Self-Refine: Iterative Refinement with Self-Feedback](https://mlsanity.com/paper/2303.17651/) (2023)
- [Code Llama: Open Foundation Models for Code](https://mlsanity.com/paper/2308.12950/) (2023)
- [SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering](https://mlsanity.com/paper/2405.15793/) (2024)
- [Qwen2.5-Coder Technical Report](https://mlsanity.com/paper/2409.12186/) (2024)
- [Executable Code Actions Elicit Better LLM Agents](https://mlsanity.com/paper/2402.01030/) (2024)
- [Training Software Engineering Agents and Verifiers with SWE-Gym](https://mlsanity.com/paper/2412.21139/) (2024)

## Built on by (most cited first, 24 of 24)

- [AIRS-Bench: a Suite of Tasks for Frontier AI Research Science Agents](https://mlsanity.com/paper/2602.06855/) (2026)
- [On Randomness in Agentic Evals](https://mlsanity.com/paper/2602.07150/) (2026)
- [QAgent: An LLM-based Multi-Agent System for Autonomous OpenQASM programming](https://mlsanity.com/paper/2508.20134/) (2025)
- [SciCoQA: Quality Assurance for Scientific Paper--Code Alignment](https://mlsanity.com/paper/2601.12910/) (2026)
- [SERA: Soft-Verified Efficient Repository Agents](https://mlsanity.com/paper/2601.20789/) (2026)
- [SWE-QA-Pro: A Representative Benchmark and Scalable Training Recipe for Repository-Level Code Understanding](https://mlsanity.com/paper/2603.16124/) (2026)
- [Agentic Software Issue Resolution with Large Language Models: A Survey](https://mlsanity.com/paper/2512.22256/) (2025)
- [Do Chatbot LLMs Talk Too Much? The YapBench Benchmark](https://mlsanity.com/paper/2601.00624/) (2026)
- [EvoRepair: Enhancing Vulnerability Repair Agents Through Experience-Based Self-Evolution](https://mlsanity.com/paper/2605.30105/) (2026)
- [MindForge: Teaching Small Language Models Whole-Life-Cycle Software Engineering via Source-Free Program Synthesis](https://mlsanity.com/paper/2607.27146/) (2026)
- [Adaptive Hierarchical Evaluation of LLMs and SAST tools for CWE Prediction in Python](https://mlsanity.com/paper/2601.01320/) (2026)
- [TACTIC-KG: Toward Small Agent Teams for Cyber Threat Intelligence Knowledge Graph Construction](https://mlsanity.com/paper/2607.05001/) (2026)
- [TRACE-ROUTER: Task-Consistent and Adaptive Online Routing for Agentic AI](https://mlsanity.com/paper/2607.22465/) (2026)
- [Simulation Code Generation for Fluid Systems using Large Language Models: Benchmarking Models and Prompting Strategies](https://mlsanity.com/paper/2607.29389/) (2026)
- [DataKernelBench: Can LLMs Optimize Database Queries on GPUs?](https://mlsanity.com/paper/2608.25061/) (2026)
- [CodeCytos: AI-assisted spatial molecular imaging analysis via code-augmented agent action space](https://mlsanity.com/paper/2606.00472/) (2026)
- [KGVoyager: Knowledge Graph Agnostic Question Answering via Agentic Navigation](https://mlsanity.com/paper/2609.01780/) (2026)
- [CS-Guard: Benchmarking LLM Guardrails for Code Generation Security](https://mlsanity.com/paper/2609.09798/) (2026)
- [CodeTS: Verifiable Text-to-Time Series Generation via Executable Code](https://mlsanity.com/paper/2609.15393/) (2026)
- [ISA-Bench: A Benchmark for Computational Reasoning Across Instruction Set Architectures](https://mlsanity.com/paper/2609.22878/) (2026)
- [APOLO: Automatic Prompt Optimization for Ontology Learning](https://mlsanity.com/paper/2609.34540/) (2026)
- [Learning When and How to Intervene: A Hindsight-Distilled Sentinel for Coding Agents](https://mlsanity.com/paper/2609.39957/) (2026)
- [AgSpec: Pushing the Limits of Retrieval-Based Speculative Decoding in Coding Agent Pipelines](https://mlsanity.com/paper/2610.01108/) (2026)
- [AdaEva: Accelerating LLM-Driven Algorithm Design with Adaptive Partial Evaluation](https://mlsanity.com/paper/2610.03896/) (2026)

## Abstract (arXiv)

We introduce Devstral-Small, a lightweight open source model for code agents with the best performance among models below 100B size. In this technical report, we give an overview of how we design and develop a model and craft specializations in agentic software development. The resulting model, Devstral-Small is a small 24B model, fast and easy to serve. Despite its size, Devstral-Small still attains competitive performance compared to models more than an order of magnitude larger.