Real Engineering Decision Making · Comparison Tables · Analysis Framework

Devstral 2 · Benchmark & Comparison

What you care about isn't 'who's stronger', but 'whether the input-output ratio is worthwhile in real engineering projects'.

Engineering Decision Overview

Core Tip：First think 'who to choose', then see 'why'. The table below helps you make decisions quickly.

Quick Selection：Quick tip: For personal users, start with Devstral Small 2. For enterprise users, consider Devstral 2.

Devstral Small 2

Recommended for Beginners

✅ Local deployment

✅ Open source

✅ Single machine runnable

✅ Privacy friendly

💰 Excellent cost

🛠️ Simple deployment

Best for：Personal development, small teams, limited budget

Devstral 2

Balanced Choice

✅ Local deployment

✅ Open source

✅ Single machine runnable

✅ Privacy friendly

💰 Good cost

⚠️ Medium deployment complexity

Best for：Medium to large projects, need higher performance

Note：Requires better hardware configuration

DeepSeek-V3.2

Performance Oriented

✅ Local deployment

✅ Open source

❌ Requires multiple cards

✅ Privacy friendly

💰 Higher cost

🛠️ Complex deployment

Best for：Large enterprises, pursuing ultimate performance

Note：Requires multi-card setup, high operational cost

Claude Sonnet 4.5

Cloud Service

❌ Cloud API only

❌ Closed source

❌ No local support

⚠️ Limited privacy

💰 Pay-as-you-go

🛠️ Zero deployment

Best for：Quick prototyping, not considering data privacy

Note：Data residency risks, uncontrollable costs

GPT-5.1 Codex

Top Performance

❌ Cloud API only

❌ Closed source

❌ No local support

⚠️ Limited privacy

💸 Very high cost

🛠️ Zero deployment

Best for：Pursuing best results regardless of cost

Note：Extremely high cost, data security risks

Engineering Decision Overview

Choose the best model for your project

Model / Model	Devstral 2	Devstral Small 2	DeepSeek-V3.2	Claude Sonnet 4.5	GPT-5.1 Codex
🧠 Deployment & Controllability
Local deployment	Local deployment	Local deployment	Local deployment	Cloud API only	Cloud API only
Open Source	Open Source	Open Source	Open Source	Closed Source	Closed Source
Single machine runnable	Single machine runnable	Single machine runnable	Requires multiple cards	Requires multiple cards	Requires multiple cards
Privacy friendly	Privacy friendly	Privacy friendly	Privacy friendly	Privacy limited	Privacy limited
💰 Cost & Engineering Reality
Inference cost controllability	Good	Excellent	Poor	Poor	Very Poor
Deployment complexity	Medium	Simple	Complex	Simple	Simple
Maintenance difficulty	Medium	Simple	Complex	Simple	Simple

Performance Benchmark Comparison

Important：Data for reference only, not equivalent to engineering conclusions

Performance Benchmark Comparison

Data for reference only, not equivalent to engineering conclusions

Model	Parameter Scale	SWE-bench (Verified)	Terminal Bench	Positioning Description
Devstral 2	123B	≈ 71-73%	≈ 31-34%	Medium to large projects, need higher performance
Devstral Small 2	24B	≈ 67-69%	≈ 21-24%	Personal development, small teams, limited budget
DeepSeek-V3.2	671B	≈ 72-74%	≈ 45-48%	Large enterprises, pursuing ultimate performance
Claude Sonnet 4.5	Closed Source	≈ 76-78%	≈ 41-44%	Quick prototyping, not considering data privacy
GPT-5.1 Codex	Closed Source	≈ 77-79% Highest	≈ 56-60% Highest	Pursuing best results regardless of cost

📊 Benchmark Data Source Description

Engineering Decision Advice

One-line Conclusion

Devstral 2 achieves close to top-tier commercial model performance at a lower cost in real GitHub Issue fixing (SWE-bench) scenarios.

Engineering Decision Advice

Personal/Small Team：Start with Devstral Small 2 (24B)
Heavy Tasks/Long Context：Consider Devstral 2 (123B) or inference service
Key Principle：Run a small A/B test with your own repo, more reliable than looking at rankings