Mistral Small 3.1 vs Devstral Small (May '25)

Comparing 2 AI models · 6 benchmarks · Mistral

Most Affordable
Mistral logo
Mistral Small 3.1
$0.10/1M
Highest Intelligence
Mistral logo
Mistral Small 3.1
45.4% GPQA
Best for Coding
Mistral logo
Mistral Small 3.1
13.9 Coding Index
Price Difference
1.0x
input cost range

Composite Indices

Intelligence, Coding, Math

Standard Benchmarks

Academic and industry benchmarks

Benchmark Winners

6 tests
Mistral logo

Mistral Small 3.1

5
  • GPQA
  • MMLU Pro
  • HLE
  • MATH 500
  • AIME 2025
Mistral logo

Devstral Small (May '25)

1
  • LiveCodeBench
Metric
Mistral logo Mistral Small 3.1
Mistral
Mistral logo Devstral Small (May '25)
Mistral
Pricing
Per 1M tokens
Input Cost $0.10/1M $0.10/1M
Output Cost $0.30/1M $0.30/1M
Blended Cost 3:1 input/output ratio
$0.15/1M $0.15/1M
Specifications
Organization Model creator
Mistral Mistral
Release Date Launch date
Mar 17, 2025 May 21, 2025
Performance & Speed
Throughput Output speed
106.8 tok/s
Time to First Token (TTFT) Initial response delay
295ms
Latency Time to first answer token
295ms
Composite Indices
Intelligence Index Overall reasoning capability
14.4 18.0
Coding Index Programming ability
13.9 12.2
Math Index Mathematical reasoning
3.7
Standard Benchmarks
GPQA Graduate-level reasoning
45.4% 43.4%
MMLU Pro Advanced knowledge
65.9% 63.2%
HLE Hard language evaluation
4.8% 4.0%
LiveCodeBench Real-world coding tasks
21.2% 25.8%
MATH 500 Mathematical problems
70.7% 68.4%
AIME 2025 Advanced math competition
3.7%
AIME (Original) Math olympiad problems
9.3% 6.7%
SciCode Scientific code generation
26.5% 24.5%
LCR Code review capability
19.7% 26.7%
IFBench Instruction-following
29.9% 31.6%
TAU-bench v2 Tool use & agentic tasks
25.1% 38.0%
TerminalBench Hard CLI command generation
7.6% 6.1%

Key Takeaways

Mistral Small 3.1 offers the best value at $0.10/1M, making it ideal for high-volume applications and cost-conscious projects.

Mistral Small 3.1 leads in reasoning capabilities with a 45.4% GPQA score, excelling at complex analytical tasks and problem-solving.

Mistral Small 3.1 achieves a 13.9 coding index, making it the top choice for software development and code generation tasks.

All models support context windows of ∞+ tokens, suitable for processing lengthy documents and maintaining extended conversations.

When to Choose Each Model

Mistral logo

Mistral Small 3.1

  • Cost-sensitive applications
  • High-volume processing
  • Complex reasoning tasks
  • Research & analysis
  • Code generation
  • Software development
Mistral logo

Devstral Small (May '25)

  • General-purpose AI
  • Versatile applications

Cost Calculator

Mistral logo Mistral Small 3.1
$0.00
per month
Mistral logo Devstral Small (May '25)
$0.00
per month

Costs are estimates based on API pricing. Actual costs may vary based on caching, batch processing, and volume discounts.

AI Model Comparison Guide

Compare large language models (LLMs) side-by-side with detailed benchmark scores, pricing, and performance metrics. Our interactive comparison tool helps you evaluate AI models from OpenAI, Anthropic, Google, Meta, DeepSeek, and other leading providers. Use our AI model leaderboard to discover more models to compare.

Understanding Composite Indices

  • Intelligence Index: Aggregated score combining MMLU-Pro, GPQA, and HLE benchmarks - measures overall reasoning and knowledge capabilities
  • Coding Index: Composite metric from LiveCodeBench, SciCode, and LiveCodeBench Review - evaluates programming proficiency across multiple languages
  • Math Index: Combined score from AIME, AIME 2025, and MATH-500 benchmarks - assesses mathematical reasoning from high school to competition level

Key Comparison Metrics

  • Benchmark Scores: Standardized tests measuring intelligence, coding, math, and specialized capabilities - higher percentages indicate better performance
  • Pricing Analysis: Compare input and output token costs across models - critical for budgeting API usage and scaling applications
  • Performance Metrics: Throughput (tokens/second) and latency measurements for real-time application planning
  • Context Windows: Maximum token capacity for processing documents and maintaining conversation history

How to Compare AI Models Effectively

Performance vs Cost

Balance benchmark scores against token pricing - flagship models offer 10-15% better performance but cost 5-10x more than smaller alternatives

Task-Specific Selection

Prioritize relevant indices: coding index for development tasks, math index for STEM applications, intelligence index for general reasoning

Real-World Testing

Use our free AI chat interface to test models with your specific prompts before committing to API integration

All benchmark scores, pricing data, and performance metrics are sourced from Artificial Analysis and updated daily. Compare models by intelligence, coding ability, math performance, speed, cost, or release date using our comprehensive AI model leaderboard.