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

DeepSeek-V3.2-Exp
DeepSeek
DeepSeek-V3.2-Exp is a language model developed by DeepSeek. It achieves strong performance with an average score of 66.1% across 14 benchmarks. It excels particularly in SimpleQA (97.1%), AIME 2025 (89.3%), MMLU-Pro (85.0%). It supports a 229K token context window for handling large documents. The model is available through 2 API providers. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents DeepSeek's latest advancement in AI technology.

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.

Llama 4 Scout
Meta
2025-04-05

DeepSeek-V3.2-Exp
DeepSeek
2025-09-29
5 months newer
Pricing Comparison
Cost per million tokens (USD)

DeepSeek-V3.2-Exp

Llama 4 Scout
Performance Metrics
Context window and performance specifications

DeepSeek-V3.2-Exp

Llama 4 Scout
Average performance across 23 common benchmarks

DeepSeek-V3.2-Exp

Llama 4 Scout
Performance comparison across key benchmark categories

DeepSeek-V3.2-Exp

Llama 4 Scout
Provider Availability & Performance
Available providers and their performance metrics

DeepSeek-V3.2-Exp
Novita
ZeroEval

Llama 4 Scout
Together
DeepInfra
Fireworks
Groq
Novita
Lambda

DeepSeek-V3.2-Exp

Llama 4 Scout