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

DeepSeek R1 Distill Qwen 32B
DeepSeek
DeepSeek R1 Distill Qwen 32B is a language model developed by DeepSeek. It achieves strong performance with an average score of 74.2% across 4 benchmarks. It excels particularly in MATH-500 (94.3%), AIME 2024 (83.3%), GPQA (62.1%). 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 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.

DeepSeek R1 Distill Qwen 32B
DeepSeek
2025-01-20

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

DeepSeek R1 Distill Qwen 32B

Llama 4 Scout
Performance Metrics
Context window and performance specifications

DeepSeek R1 Distill Qwen 32B

Llama 4 Scout
Average performance across 2 common benchmarks

DeepSeek R1 Distill Qwen 32B

Llama 4 Scout
Performance comparison across key benchmark categories

DeepSeek R1 Distill Qwen 32B

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

DeepSeek R1 Distill Qwen 32B
DeepInfra

Llama 4 Scout
Together
DeepInfra
Fireworks
Groq
Novita
Lambda

DeepSeek R1 Distill Qwen 32B

Llama 4 Scout