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Llama 4 Scout vs Phi 4 Reasoning
Comprehensive side-by-side LLM comparison
Phi 4 Reasoning leads with 9.9% higher average benchmark score. Llama 4 Scout supports multimodal inputs. Llama 4 Scout is available on 6 providers. Overall, Phi 4 Reasoning is the stronger choice for coding tasks.
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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.
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Microsoft
Phi-4 Reasoning was developed to incorporate extended analytical thinking into the Phi-4 architecture, designed to spend more time on complex problem-solving. Built to combine compact model efficiency with reasoning depth, it represents Microsoft's exploration of thoughtful small models.
25 days newer
Llama 4 Scout
Meta
2025-04-05
Phi 4 Reasoning
Microsoft
2025-04-30
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Performance Metrics
Context window and performance specifications
Average performance across 3 common benchmarks
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Llama 4 Scout
Average Score:54.8%
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Phi 4 Reasoning
Average Score:64.6%(+9.9%)
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Knowledge Cutoff
Training data recency comparison
Phi 4 Reasoning
2025-03-01
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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Llama 4 Scout
6 providers
DeepInfra
Throughput: 76.1 tok/s
Latency: 0.31ms
Fireworks
Throughput: 116.1 tok/s
Latency: 0.53ms
Groq
Throughput: 776.1 tok/s
Latency: 1.08ms
Lambda
Throughput: 139.7 tok/s
Latency: 0.43ms
Novita
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Llama 4 Scout
Avg Score:54.8%
Providers:6
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Phi 4 Reasoning
Avg Score:64.6%(+9.9%)
Providers:0