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Minimax M 2.5 vs o1
Comprehensive side-by-side LLM comparison
o1 offers 95.9K more tokens in context window than Minimax M 2.5. Minimax M 2.5 is $73.50 cheaper per million tokens. o1 supports multimodal inputs. 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, released by OpenAI in December 2024, is a reasoning-focused large language model that applies extended chain-of-thought processing before generating responses. It features a 200K token context window and native image understanding, demonstrating strong performance on STEM benchmarks requiring multi-step reasoning. o1 targets mathematics, science, and coding tasks where careful deliberation over the problem produces more accurate outputs than direct generation.
1 year newer
o1
OpenAI
2024-12-05
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($73.50 cheaper)
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o1
Input:$15.00
Output:$60.00
Performance Metrics
Context window and performance specifications
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Knowledge Cutoff
Training data recency comparison
o1
2023-10
More recent knowledge cutoff means awareness of newer technologies and frameworks
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
1 providers
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Minimax M 2.5
Avg Score:0.0%
Providers:1
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o1
Avg Score:0.0%
Providers:1