Comprehensive side-by-side LLM comparison
Both models show comparable benchmark performance. DeepSeek-V3.1 offers 71.7K more tokens in context window than Llama 3.2 90B Instruct. Llama 3.2 90B Instruct is $0.52 cheaper per million tokens. Llama 3.2 90B Instruct supports multimodal inputs. Llama 3.2 90B Instruct is available on 5 providers. Both models have their strengths depending on your specific coding needs.
DeepSeek
DeepSeek-V3.1 is a language model developed by DeepSeek. The model shows competitive results across 16 benchmarks. It excels particularly in SimpleQA (93.4%), MMLU-Redux (91.8%), MMLU-Pro (83.7%). It supports a 328K 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.
Meta
Llama 3.2 90B Instruct is a multimodal language model developed by Meta. It achieves strong performance with an average score of 71.3% across 13 benchmarks. It excels particularly in AI2D (92.3%), DocVQA (90.1%), MGSM (86.9%). It supports a 256K token context window for handling large documents. The model is available through 5 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Meta's latest advancement in AI technology.
3 months newer
Llama 3.2 90B Instruct
Meta
2024-09-25
DeepSeek-V3.1
DeepSeek
2025-01-10
Cost per million tokens (USD)
DeepSeek-V3.1
Llama 3.2 90B Instruct
Context window and performance specifications
Average performance across 28 common benchmarks
DeepSeek-V3.1
Llama 3.2 90B Instruct
Available providers and their performance metrics
DeepSeek-V3.1
DeepInfra
Novita
Llama 3.2 90B Instruct
DeepSeek-V3.1
Llama 3.2 90B Instruct
DeepSeek-V3.1
Llama 3.2 90B Instruct
Bedrock
DeepInfra
Fireworks
Hyperbolic
Together