Comprehensive side-by-side LLM comparison
Llama 3.2 3B Instruct leads with 1.2% higher average benchmark score. Llama 4 Scout offers 19.7M more tokens in context window than Llama 3.2 3B Instruct. Both models have similar pricing. Llama 4 Scout supports multimodal inputs. Llama 4 Scout is available on 6 providers. Both models have their strengths depending on your specific coding needs.
Meta
Llama 3.2 3B Instruct is a language model developed by Meta. The model shows competitive results across 15 benchmarks. It excels particularly in NIH/Multi-needle (84.7%), ARC-C (78.6%), GSM8k (77.7%). It supports a 256K token context window for handling large documents. The model is available through 1 API provider. Released in 2024, it represents Meta's latest advancement in AI technology.
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%). 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.
6 months newer
Llama 3.2 3B Instruct
Meta
2024-09-25
Llama 4 Scout
Meta
2025-04-05
Cost per million tokens (USD)
Llama 3.2 3B Instruct
Llama 4 Scout
Context window and performance specifications
Average performance across 23 common benchmarks
Llama 3.2 3B Instruct
Llama 4 Scout
Available providers and their performance metrics
Llama 3.2 3B Instruct
DeepInfra
Llama 4 Scout
Llama 3.2 3B Instruct
Llama 4 Scout
Llama 3.2 3B Instruct
Llama 4 Scout
DeepInfra
Fireworks
Groq
Lambda
Novita
Together