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DeepSeek-R1-0528 vs Llama 4 Scout
Comprehensive side-by-side LLM comparison
DeepSeek-R1-0528 leads with 25.0% higher average benchmark score. Llama 4 Scout offers 19.7M more tokens in context window than DeepSeek-R1-0528. Llama 4 Scout is $2.27 cheaper per million tokens. Llama 4 Scout supports multimodal inputs. Llama 4 Scout is available on 6 providers. Overall, DeepSeek-R1-0528 is the stronger choice for coding tasks.
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DeepSeek
DeepSeek-R1-0528 represents a specific release iteration of the DeepSeek-R1 model, developed to incorporate refinements and improvements from ongoing training. Built to provide enhanced reasoning capabilities based on accumulated insights, it continues the evolution of DeepSeek's reasoning-focused architecture.
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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.
1 month newer
Llama 4 Scout
Meta
2025-04-05
DeepSeek-R1-0528
DeepSeek
2025-05-28
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Pricing Comparison
Cost per million tokens (USD)
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DeepSeek-R1-0528
Input:$0.50
Output:$2.15
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Llama 4 Scout
Input:$0.08
Output:$0.30($2.27 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 3 common benchmarks
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DeepSeek-R1-0528
Average Score:79.8%(+25.0%)
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Llama 4 Scout
Average Score:54.8%
Provider Availability & Performance
Available providers and their performance metrics
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DeepSeek-R1-0528
3 providers
DeepInfra
Throughput: 45.04 tok/s
Latency: 0.61ms
DeepSeek
Throughput: 9 tok/s
Latency: 0.3ms
Novita
Throughput: 37.96 tok/s
Latency: 1.18ms
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DeepSeek-R1-0528
Avg Score:79.8%(+25.0%)
Providers:3
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Llama 4 Scout
Avg Score:54.8%
Providers:6