Comprehensive side-by-side LLM comparison
Phi-3.5-MoE Instruct leads with 3.2% higher average benchmark score. Llama 4 Maverick supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
Meta AI
Llama 4 Maverick, released by Meta on April 5, 2025, is a natively multimodal Mixture-of-Experts large language model with 400 billion total parameters and 17 billion active parameters per inference. It features a 1M token context window and supports text and image input, enabling strong performance on both language and vision tasks. Maverick targets open-source deployments requiring large-scale multimodal reasoning, released under Meta's custom license.
Microsoft
Phi-3.5-MoE-instruct is a sparse mixture-of-experts model from Microsoft's Phi research team, released in August 2024 with 42 billion total parameters across 16 experts and approximately 6.6 billion active parameters per forward pass. The model applies Microsoft's small-data, high-quality training philosophy — developed across earlier Phi generations — to a MoE architecture, targeting reasoning quality comparable to much larger dense models at a fraction of the inference compute. Released under the MIT license, it was notable in the research community for demonstrating that MoE efficiency gains could be realized at smaller total parameter counts than typical large-scale MoE deployments.
7 months newer

Phi-3.5-MoE Instruct
Microsoft
2024-08-22

Llama 4 Maverick
Meta AI
2025-04-05
Context window and performance specifications
Average performance across 1 common benchmarks
Llama 4 Maverick
Phi-3.5-MoE Instruct
Performance comparison across key benchmark categories
Llama 4 Maverick
Phi-3.5-MoE Instruct
Available providers and their performance metrics
Llama 4 Maverick
Together AI
Phi-3.5-MoE Instruct
Llama 4 Maverick
Phi-3.5-MoE Instruct
Llama 4 Maverick
Phi-3.5-MoE Instruct