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DeepSeek-V3 vs Llama 4 Scout
Comprehensive side-by-side LLM comparison
DeepSeek-V3 leads with 4.3% higher average benchmark score. Llama 4 Scout offers 19.7M more tokens in context window than DeepSeek-V3. Llama 4 Scout is $0.99 cheaper per million tokens. Llama 4 Scout supports multimodal inputs. Llama 4 Scout is available on 6 providers. Both models have their strengths depending on your specific coding needs.
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DeepSeek
DeepSeek-V3 was introduced as a major architectural advancement, developed with 671B mixture-of-experts parameters and trained on 14.8 trillion tokens. Built to be three times faster than V2 while maintaining open-source availability, it demonstrates competitive performance against frontier closed-source models and represents a significant leap in efficient large-scale model design.
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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.
3 months newer
DeepSeek-V3
DeepSeek
2024-12-25
Llama 4 Scout
Meta
2025-04-05
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Pricing Comparison
Cost per million tokens (USD)
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DeepSeek-V3
Input:$0.27
Output:$1.10
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Llama 4 Scout
Input:$0.08
Output:$0.30($0.99 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 4 common benchmarks
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DeepSeek-V3
Average Score:65.3%(+4.3%)
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Llama 4 Scout
Average Score:61.0%
Provider Availability & Performance
Available providers and their performance metrics
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DeepSeek-V3
1 providers
DeepSeek
Throughput: 100 tok/s
Latency: 0.5ms
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Llama 4 Scout
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DeepSeek-V3
Avg Score:65.3%(+4.3%)
Providers:1
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Llama 4 Scout
Avg Score:61.0%
Providers:6