Comprehensive side-by-side LLM comparison
Gemini 2.5 Pro leads with 25.7% higher average benchmark score. Gemini 2.5 Pro offers 602.1K more tokens in context window than Jamba 1.5 Large. Jamba 1.5 Large is $1.25 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.
AI21 Labs
Jamba 1.5 Large is a language model developed by AI21 Labs. It achieves strong performance with an average score of 65.5% across 8 benchmarks. It excels particularly in ARC-C (93.0%), GSM8k (87.0%), MMLU (81.2%). It supports a 512K token context window for handling large documents. The model is available through 2 API providers. Released in 2024, it represents AI21 Labs's latest advancement in AI technology.
9 months newer
Jamba 1.5 Large
AI21 Labs
2024-08-22
Gemini 2.5 Pro
2025-05-20
Cost per million tokens (USD)
Gemini 2.5 Pro
Jamba 1.5 Large
Context window and performance specifications
Average performance across 23 common benchmarks
Gemini 2.5 Pro
Jamba 1.5 Large
Jamba 1.5 Large
2024-03-05
Gemini 2.5 Pro
2025-01-31
Available providers and their performance metrics
Gemini 2.5 Pro
ZeroEval
Jamba 1.5 Large
Gemini 2.5 Pro
Jamba 1.5 Large
Gemini 2.5 Pro
Jamba 1.5 Large
Bedrock