Comprehensive side-by-side LLM comparison
Gemini 1.5 Pro leads with 26.1% higher average benchmark score. Gemini 1.5 Pro offers 1.8M more tokens in context window than Llama 3.2 3B Instruct. Llama 3.2 3B Instruct is $12.47 cheaper per million tokens. Gemini 1.5 Pro supports multimodal inputs. Overall, Gemini 1.5 Pro is the stronger choice for coding tasks.
Gemini 1.5 Pro is a multimodal language model developed by Google. It achieves strong performance with an average score of 72.6% across 23 benchmarks. It excels particularly in XSTest (98.8%), HellaSwag (93.3%), GSM8k (90.8%). With a 2.1M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 1 API provider. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2024, it represents Google's latest advancement in AI technology.
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.
4 months newer
Gemini 1.5 Pro
2024-05-01
Llama 3.2 3B Instruct
Meta
2024-09-25
Cost per million tokens (USD)
Gemini 1.5 Pro
Llama 3.2 3B Instruct
Context window and performance specifications
Average performance across 32 common benchmarks
Gemini 1.5 Pro
Llama 3.2 3B Instruct
Gemini 1.5 Pro
2023-11-01
Available providers and their performance metrics
Gemini 1.5 Pro
Llama 3.2 3B Instruct
Gemini 1.5 Pro
Llama 3.2 3B Instruct
Gemini 1.5 Pro
Llama 3.2 3B Instruct
DeepInfra