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DeepSeek-V2.5 vs GPT OSS 20B
Comprehensive side-by-side LLM comparison
GPT OSS 20B leads with 4.9% higher average benchmark score. GPT OSS 20B offers 245.8K more tokens in context window than DeepSeek-V2.5. Both models have similar pricing. 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
GPT-OSS 20B was created as a smaller open-source variant, designed to balance capability with accessibility for researchers and developers. Built with 20 billion parameters, it provides a more approachable entry point for those seeking to work with open-source language models while benefiting from OpenAI's architectural insights.
1 year newer
DeepSeek-V2.5
DeepSeek
2024-05-08
GPT OSS 20B
OpenAI
2025-08-05
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Pricing Comparison
Cost per million tokens (USD)
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DeepSeek-V2.5
Input:$0.14
Output:$0.28
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GPT OSS 20B
Input:$0.05
Output:$0.20($0.17 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 1 common benchmarks
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DeepSeek-V2.5
Average Score:80.4%
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GPT OSS 20B
Average Score:85.3%(+4.9%)
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:80.4%
Providers:3
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GPT OSS 20B
Avg Score:85.3%(+4.9%)
Providers:4