Comprehensive side-by-side LLM comparison
Gemini 1.5 Pro leads with 42.4% higher average benchmark score. Gemini 1.5 Pro offers 1.6M more tokens in context window than Jamba 1.5 Large. Jamba 1.5 Large is $2.50 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.
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.
3 months newer
Gemini 1.5 Pro
2024-05-01
Jamba 1.5 Large
AI21 Labs
2024-08-22
Cost per million tokens (USD)
Gemini 1.5 Pro
Jamba 1.5 Large
Context window and performance specifications
Average performance across 27 common benchmarks
Gemini 1.5 Pro
Jamba 1.5 Large
Gemini 1.5 Pro
2023-11-01
Jamba 1.5 Large
2024-03-05
Available providers and their performance metrics
Gemini 1.5 Pro
Jamba 1.5 Large
Gemini 1.5 Pro
Jamba 1.5 Large
Gemini 1.5 Pro
Jamba 1.5 Large
Bedrock