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Devstral-2-123B vs Qwen3-235B-A22B
Comprehensive side-by-side LLM comparison
Qwen3-235B-A22B offers 6.1K more tokens in context window than Devstral-2-123B. Qwen3-235B-A22B is $3.00 cheaper per million tokens. Both models have their strengths depending on your specific coding needs.
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Mistral AI
Devstral 2, released by Mistral AI on December 9, 2025, is a 123 billion parameter dense transformer model specifically designed for software engineering tasks. It features a 256K token context window and achieved 72.2% on SWE-bench Verified at release, making it a competitive open-weight option for automated coding and agentic development. Devstral 2 targets code generation, multi-file software engineering, and agentic development workflows under a modified MIT license.
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Alibaba / Qwen
Qwen3-235B-A22B, released by Alibaba's Qwen team on April 28, 2025, is a Mixture-of-Experts large language model with 235 billion total parameters and 22 billion active parameters per inference. It features a 256K token context window, hybrid thinking capabilities (both reasoning and direct generation modes), and was trained on 36 trillion tokens across 119 languages. Qwen3-235B targets complex reasoning, multilingual tasks, and open-source deployments under the Apache 2.0 license.
7 months newer
Qwen3-235B-A22B
Alibaba / Qwen
2025-04-28
Devstral-2-123B
Mistral AI
2025-12-09
Pricing Comparison
Cost per million tokens (USD)
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Devstral-2-123B
Input:$1.00
Output:$3.00
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Qwen3-235B-A22B
Input:$0.25
Output:$0.75($3.00 cheaper)
Performance Metrics
Context window and performance specifications
Provider Availability & Performance
Available providers and their performance metrics
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Devstral-2-123B
1 providers
OpenRouter
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Qwen3-235B-A22B
1 providers
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Devstral-2-123B
Avg Score:0.0%
Providers:1
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Qwen3-235B-A22B
Avg Score:0.0%
Providers:1