Comprehensive side-by-side LLM comparison
Gemini 2.5 Pro leads with 9.3% higher average benchmark score. Gemini 2.5 Pro offers 858.1K more tokens in context window than Llama 3.2 3B Instruct. Llama 3.2 3B Instruct is $11.22 cheaper per million tokens. Gemini 2.5 Pro supports multimodal inputs. Overall, Gemini 2.5 Pro is the stronger choice for coding tasks.
Gemini 2.5 Pro is a multimodal language model developed by Google. It achieves strong performance with an average score of 69.6% across 16 benchmarks. It excels particularly in MRCR (93.0%), AIME 2024 (92.0%), Global-MMLU-Lite (88.6%). With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. 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 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.
7 months newer
Llama 3.2 3B Instruct
Meta
2024-09-25
Gemini 2.5 Pro
2025-05-20
Cost per million tokens (USD)
Gemini 2.5 Pro
Llama 3.2 3B Instruct
Context window and performance specifications
Average performance across 30 common benchmarks
Gemini 2.5 Pro
Llama 3.2 3B Instruct
Gemini 2.5 Pro
2025-01-31
Available providers and their performance metrics
Gemini 2.5 Pro
ZeroEval
Gemini 2.5 Pro
Llama 3.2 3B Instruct
Gemini 2.5 Pro
Llama 3.2 3B Instruct
Llama 3.2 3B Instruct
DeepInfra