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GPT OSS 120B vs Llama 4 Scout
Comprehensive side-by-side LLM comparison
GPT OSS 120B leads with 16.7% higher average benchmark score. Llama 4 Scout offers 19.7M more tokens in context window than GPT OSS 120B. Both models have similar pricing. Llama 4 Scout supports multimodal inputs. Overall, GPT OSS 120B is the stronger choice for coding tasks.
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OpenAI
GPT-OSS 120B was developed as an open-source model release from OpenAI, designed to provide the research and developer community with access to a capable language model. Built with 120 billion parameters, it enables experimentation, fine-tuning, and deployment in contexts where open-source licensing and transparency are valued.
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Meta
Llama 4 Scout was created as an exploratory variant in the Llama 4 family, designed to investigate new architectures and optimization strategies. Built as part of Meta's commitment to advancing open-source AI, it serves as a testbed for innovations that may inform future model releases.
4 months newer
Llama 4 Scout
Meta
2025-04-05
GPT OSS 120B
OpenAI
2025-08-05
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Pricing Comparison
Cost per million tokens (USD)
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GPT OSS 120B
Input:$0.09
Output:$0.45
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Llama 4 Scout
Input:$0.08
Output:$0.30($0.16 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 2 common benchmarks
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GPT OSS 120B
Average Score:85.0%(+16.7%)
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Llama 4 Scout
Average Score:68.4%
Provider Availability & Performance
Available providers and their performance metrics
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GPT OSS 120B
5 providers
DeepInfra
Groq
Throughput: 500 tok/s
Latency: 0.5ms
Novita
OpenAI
Throughput: 115 tok/s
Latency: 5.2ms
ZeroEval
Throughput: 500 tok/s
Latency: 0.5ms
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GPT OSS 120B
Avg Score:85.0%(+16.7%)
Providers:5
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Llama 4 Scout
Avg Score:68.4%
Providers:6