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Minimax M 2.5 vs o1 mini
Comprehensive side-by-side LLM comparison
Minimax M 2.5 offers 10.6K more tokens in context window than o1 mini. Minimax M 2.5 is $4.00 cheaper per million tokens. Both models have their strengths depending on your specific coding needs.
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MiniMax
MiniMax M2.5 is a large language model from MiniMax extensively trained with reinforcement learning across hundreds of thousands of complex real-world environments. It targets agentic tool use, coding automation, and office productivity tasks, with strong results on software engineering and web browsing benchmarks. M2.5 represents the next generation of MiniMax's M-series models optimized for production agentic workloads.
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OpenAI
OpenAI o1 mini, released by OpenAI in September 2024, is a lightweight reasoning model from the o1 family optimized for efficient STEM problem-solving at lower cost and latency. It features a 128K token context window and applies chain-of-thought reasoning specifically tuned for mathematics, science, and coding tasks. o1 mini targets use cases where rapid, cost-efficient reasoning is preferred over the broader capabilities of the full o1 model.
1 year newer
o1 mini
OpenAI
2024-09-12
Minimax M 2.5
MiniMax
2026-02-13
Pricing Comparison
Cost per million tokens (USD)
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Minimax M 2.5
Input:$0.30
Output:$1.20($4.00 cheaper)
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o1 mini
Input:$1.10
Output:$4.40
Performance Metrics
Context window and performance specifications
Provider Availability & Performance
Available providers and their performance metrics
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Minimax M 2.5
1 providers
MiniMax
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o1 mini
1 providers
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Minimax M 2.5
Avg Score:0.0%
Providers:1
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o1 mini
Avg Score:0.0%
Providers:1