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Llama 4 Scout vs Phi-3.5-MoE-instruct
Comprehensive side-by-side LLM comparison
Llama 4 Scout leads with 10.0% higher average benchmark score. Llama 4 Scout supports multimodal inputs. Llama 4 Scout is available on 6 providers. Overall, Llama 4 Scout 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-3.5 MoE was created using a mixture-of-experts architecture, designed to provide enhanced capabilities while maintaining efficiency through sparse activation. Built to combine the benefits of larger models with practical computational requirements, it represents Microsoft's exploration of efficient scaling techniques.
7 months newer
Phi-3.5-MoE-instruct
Microsoft
2024-08-23
Llama 4 Scout
Meta
2025-04-05
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Performance Metrics
Context window and performance specifications
Average performance across 6 common benchmarks
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Llama 4 Scout
Average Score:70.0%(+10.0%)
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Phi-3.5-MoE-instruct
Average Score:60.0%
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:70.0%(+10.0%)
Providers:6
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Phi-3.5-MoE-instruct
Avg Score:60.0%
Providers:0