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DeepSeek-V2.5 vs o1-mini
Comprehensive side-by-side LLM comparison
o1-mini leads with 4.1% higher average benchmark score. o1-mini offers 177.2K more tokens in context window than DeepSeek-V2.5. DeepSeek-V2.5 is $14.58 cheaper per million tokens. Both models have their strengths depending on your specific coding needs.
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DeepSeek
DeepSeek-V2.5 was developed as an enhanced iteration of the DeepSeek-V2 architecture, designed to incorporate improvements in model quality and efficiency. Built to advance the DeepSeek foundation model series, it provides refined capabilities for general-purpose language understanding and generation tasks.
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OpenAI
o1-mini was created as a faster, more cost-effective reasoning model, designed to bring extended thinking capabilities to applications with tighter latency and budget constraints. Built to excel particularly in coding and STEM reasoning while maintaining affordability, it provides a more accessible entry point to reasoning-enhanced AI assistance.
4 months newer
DeepSeek-V2.5
DeepSeek
2024-05-08
o1-mini
OpenAI
2024-09-12
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Pricing Comparison
Cost per million tokens (USD)
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DeepSeek-V2.5
Input:$0.14
Output:$0.28($14.58 cheaper)
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o1-mini
Input:$3.00
Output:$12.00
Performance Metrics
Context window and performance specifications
Average performance across 2 common benchmarks
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DeepSeek-V2.5
Average Score:84.7%
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o1-mini
Average Score:88.8%(+4.1%)
Provider Availability & Performance
Available providers and their performance metrics
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DeepSeek-V2.5
3 providers
DeepInfra
Throughput: 63 tok/s
Latency: 0.5ms
DeepSeek
Throughput: 100 tok/s
Latency: 0.5ms
Hyperbolic
Throughput: 100 tok/s
Latency: 0.5ms
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DeepSeek-V2.5
Avg Score:84.7%
Providers:3
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o1-mini
Avg Score:88.8%(+4.1%)
Providers:2