Comprehensive side-by-side LLM comparison
DeepSeek R1 Distill Llama 70B leads with 6.7% higher average benchmark score. GPT-5 nano offers 272.0K more tokens in context window than DeepSeek R1 Distill Llama 70B. Both models have similar pricing. GPT-5 nano supports multimodal inputs. Overall, DeepSeek R1 Distill Llama 70B is the stronger choice for coding tasks.
DeepSeek
DeepSeek R1 Distill Llama 70B is a language model developed by DeepSeek. It achieves strong performance with an average score of 76.0% across 4 benchmarks. It excels particularly in MATH-500 (94.5%), AIME 2024 (86.7%), GPQA (65.2%). 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.
OpenAI
GPT-5 nano is a multimodal language model developed by OpenAI. The model shows competitive results across 5 benchmarks. It excels particularly in AIME 2025 (85.2%), HMMT 2025 (75.6%), GPQA (71.2%). It supports a 528K token context window for handling large documents. The model is available through 2 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents OpenAI's latest advancement in AI technology.
6 months newer
DeepSeek R1 Distill Llama 70B
DeepSeek
2025-01-20
GPT-5 nano
OpenAI
2025-08-07
Cost per million tokens (USD)
DeepSeek R1 Distill Llama 70B
GPT-5 nano
Context window and performance specifications
Average performance across 8 common benchmarks
DeepSeek R1 Distill Llama 70B
GPT-5 nano
GPT-5 nano
2024-05-30
Available providers and their performance metrics
DeepSeek R1 Distill Llama 70B
DeepInfra
GPT-5 nano
DeepSeek R1 Distill Llama 70B
GPT-5 nano
DeepSeek R1 Distill Llama 70B
GPT-5 nano
OpenAI
ZeroEval