Llama 4 Scout vs Phi-4 Mini
Side-by-side comparison of pricing, features, and capabilities — 2026.
Llama 4 Scout is Meta's efficient multimodal language model featuring a mixture-of-experts architecture with 17 billion active parameters (109B total), delivering frontier-level performance at a fraction of the compute cost. Scout's groundbreaking 10 million token context window — the largest of any commercially available model — enables processing entire codebases, lengthy legal documents, and comprehensive research corpora in a single context. The model handles both text and images natively and is released under Meta's open license, enabling broad deployment.
Try Llama 4 ScoutPhi-4 Mini is Microsoft's compact but highly capable small language model optimized for reasoning tasks, mathematical problem-solving, and coding. With only 3.8 billion parameters, Phi-4 Mini achieves performance comparable to much larger models by focusing on high-quality training data and novel architectural choices. The model runs efficiently on edge devices and consumer hardware, making advanced AI reasoning accessible without cloud infrastructure. Phi-4 Mini supports multilingual text and is released under the MIT license for broad research and commercial use.
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Llama 4 Scout vs Phi-4 Mini: Which Should You Choose?
Llama 4 Scout is a free tool. Llama 4 Scout is Meta's efficient multimodal language model featuring a mixture-of-experts architecture with 17 billion active parameters (109B total), delivering frontier-level performance at a fraction of the compute cost. Scout's groundbreaking 10 million token context window — the largest of any commercially available model — enables processing entire codebases, lengthy legal documents, and comprehensive research corpora in a single context. The model handles both text and images natively and is released under Meta's open license, enabling broad deployment.
Phi-4 Mini is a free tool. Phi-4 Mini is Microsoft's compact but highly capable small language model optimized for reasoning tasks, mathematical problem-solving, and coding. With only 3.8 billion parameters, Phi-4 Mini achieves performance comparable to much larger models by focusing on high-quality training data and novel architectural choices. The model runs efficiently on edge devices and consumer hardware, making advanced AI reasoning accessible without cloud infrastructure. Phi-4 Mini supports multilingual text and is released under the MIT license for broad research and commercial use.
The right choice depends on your budget and specific needs. Both are listed in Nextool.ai's curated directory. See all Llama 4 Scout alternatives or See all Phi-4 Mini alternatives.