Model Comparison
Comprehensive side-by-side analysis of model capabilities and performance

Llama 4 Scout
Meta
Llama 4 Scout is a multimodal language model developed by Meta. It achieves strong performance with an average score of 67.3% across 12 benchmarks. It excels particularly in DocVQA (94.4%), MGSM (90.6%), ChartQA (88.8%). The model shows particular specialization in vision tasks with an average performance of 81.9%. With a 20.0M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 6 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.

Phi-3.5-mini-instruct
Microsoft
Phi-3.5-mini-instruct is a language model developed by Microsoft. The model shows competitive results across 31 benchmarks. It excels particularly in GSM8k (86.2%), ARC-C (84.6%), RULER (84.1%). It supports a 256K token context window for handling large documents. The model is available through 1 API provider. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Microsoft's latest advancement in AI technology.

Phi-3.5-mini-instruct
Microsoft
2024-08-23

Llama 4 Scout
Meta
2025-04-05
7 months newer
Pricing Comparison
Cost per million tokens (USD)

Llama 4 Scout

Phi-3.5-mini-instruct
Performance Metrics
Context window and performance specifications

Llama 4 Scout

Phi-3.5-mini-instruct
Average performance across 6 common benchmarks

Llama 4 Scout

Phi-3.5-mini-instruct
Performance comparison across key benchmark categories

Llama 4 Scout

Phi-3.5-mini-instruct
Provider Availability & Performance
Available providers and their performance metrics

Llama 4 Scout
Together
DeepInfra
Fireworks
Groq
Novita
Lambda

Phi-3.5-mini-instruct
Azure

Llama 4 Scout

Phi-3.5-mini-instruct