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Llama 4 Maverick vs Phi-3.5-MoE-instruct
Comprehensive side-by-side LLM comparison
Phi-3.5-MoE-instruct leads with 28.9% higher average benchmark score. Llama 4 Maverick supports multimodal inputs. Llama 4 Maverick is available on 7 providers. Overall, Phi-3.5-MoE-instruct is the stronger choice for coding tasks.
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Meta
Llama 4 Maverick is a multimodal language model developed by Meta. It achieves strong performance with an average score of 71.8% across 13 benchmarks. It excels particularly in DocVQA (94.4%), MGSM (92.3%), ChartQA (90.0%). With a 2.0M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 7 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Meta's latest advancement in AI technology.
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Microsoft
Phi-3.5-MoE-instruct is a language model developed by Microsoft. It achieves strong performance with an average score of 65.6% across 31 benchmarks. It excels particularly in ARC-C (91.0%), OpenBookQA (89.6%), GSM8k (88.7%). It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Microsoft's latest advancement in AI technology.
7 months newer
Phi-3.5-MoE-instruct
Microsoft
2024-08-23
Llama 4 Maverick
Meta
2025-04-05
Performance Metrics
Context window and performance specifications
Average performance across 38 common benchmarks
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Llama 4 Maverick
Average Score:24.6%
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Phi-3.5-MoE-instruct
Average Score:53.5%(+28.9%)
Provider Availability & Performance
Available providers and their performance metrics
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Llama 4 Maverick
7 providers
DeepInfra
Throughput: 83.59 tok/s
Latency: 0.38ms
Fireworks
Throughput: 63.03 tok/s
Latency: 0.62ms
Groq
Throughput: 307.3 tok/s
Latency: 0.27ms
Lambda
Throughput: 93.69 tok/s
Latency: 0.65ms
Novita
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Llama 4 Maverick
Avg Score:24.6%
Providers:7
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Phi-3.5-MoE-instruct
Avg Score:53.5%(+28.9%)
Providers:0