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Devstral-2-123B vs Qwen3-Max
Comprehensive side-by-side LLM comparison
Qwen3-Max offers 6.1K more tokens in context window than Devstral-2-123B. Qwen3-Max is $2.00 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-Max, released by Alibaba in September 2025 as an API preview, is a large language model exceeding one trillion parameters built for complex reasoning and long-context tasks. It features a 262K token context window, hybrid thinking modes that allow switching between direct generation and extended chain-of-thought, and is available as a proprietary cloud API via Alibaba Cloud and Qwen Chat. Qwen3-Max targets demanding reasoning, multilingual analysis, and applications requiring frontier-level performance from the Qwen3 generation.
3 months newer
Qwen3-Max
Alibaba / Qwen
2025-09-05
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-Max
Input:$0.50
Output:$1.50($2.00 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-Max
1 providers
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Devstral-2-123B
Avg Score:0.0%
Providers:1
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Qwen3-Max
Avg Score:0.0%
Providers:1