Mistral: Devstral Small 2505

Text input Text output Free Option
Author's Description

Devstral-Small-2505 is a 24B parameter agentic LLM fine-tuned from Mistral-Small-3.1, jointly developed by Mistral AI and All Hands AI for advanced software engineering tasks. It is optimized for codebase exploration, multi-file editing, and integration into coding agents, achieving state-of-the-art results on SWE-Bench Verified (46.8%). Devstral supports a 128k context window and uses a custom Tekken tokenizer. It is text-only, with the vision encoder removed, and is suitable for local deployment on high-end consumer hardware (e.g., RTX 4090, 32GB RAM Macs). Devstral is best used in agentic workflows via the OpenHands scaffold and is compatible with inference frameworks like vLLM, Transformers, and Ollama. It is released under the Apache 2.0 license.

Key Specifications
Cost
$
Context
128K
Parameters
24B (Rumoured)
Released
May 21, 2025
Speed
Ability
Reliability
Supported Parameters

This model supports the following parameters:

Stop Presence Penalty Top P Temperature Seed Min P Response Format Frequency Penalty Max Tokens
Features

This model supports the following features:

Response Format
Performance Summary

Mistral: Devstral Small 2505, a 24B parameter agentic LLM, demonstrates strong overall performance, particularly excelling in reliability and cost-efficiency. It boasts a perfect 100% success rate across all benchmarks, indicating exceptional reliability with no technical failures. In terms of speed, Devstral Small 2505 performs among the fastest models, ranking in the 73rd percentile. Its pricing is highly competitive, consistently placing in the 88th percentile for cost-effectiveness. Analyzing benchmark results, Devstral Small 2505 shows a standout performance in Instruction Following, achieving 100% accuracy in one instance, making it the most accurate among models of comparable speed. While its Coding (Baseline) accuracy is moderate at 82.0%, its cost and duration for this category are highly competitive. The model also exhibits strong performance in General Knowledge (98.0% accuracy) and Ethics (98.0% accuracy), though its percentile rankings in these areas are not as high. A notable weakness appears in another Instruction Following benchmark, where accuracy drops to 49.0%, suggesting some variability in complex instruction adherence. Reasoning and Email Classification show moderate accuracy. Overall, Devstral Small 2505 is a highly reliable and cost-effective model, particularly suited for agentic workflows and advanced software engineering tasks, with a strong aptitude for precise instruction following.

Model Pricing

Current Pricing

Feature Price (per 1M tokens)
Prompt $0.06
Completion $0.12

Price History

Available Endpoints
Provider Endpoint Name Context Length Pricing (Input) Pricing (Output)
DeepInfra
DeepInfra | mistralai/devstral-small-2505 128K $0.06 / 1M tokens $0.12 / 1M tokens
NextBit
NextBit | mistralai/devstral-small-2505 131K $0.02 / 1M tokens $0.08 / 1M tokens
Parasail
Parasail | mistralai/devstral-small-2505 131K $0.02 / 1M tokens $0.08 / 1M tokens
Mistral
Mistral | mistralai/devstral-small-2505 131K $0.1 / 1M tokens $0.3 / 1M tokens
Nebius
Nebius | mistralai/devstral-small-2505 128K $0.08 / 1M tokens $0.24 / 1M tokens
Chutes
Chutes | mistralai/devstral-small-2505 131K $0.02 / 1M tokens $0.08 / 1M tokens
Benchmark Results
Benchmark Category Reasoning Free Executions Accuracy Cost Duration
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