Comprehensive side-by-side LLM comparison
GPT-4.1 mini leads with 26.1% higher average benchmark score. GPT-4.1 mini offers 568.3K more tokens in context window than Jamba 1.5 Large. GPT-4.1 mini is $8.00 cheaper per million tokens. GPT-4.1 mini supports multimodal inputs. Overall, GPT-4.1 mini is the stronger choice for coding tasks.
OpenAI
GPT-4.1 mini is a multimodal language model developed by OpenAI. The model shows competitive results across 29 benchmarks. It excels particularly in CharXiv-D (88.4%), MMLU (87.5%), IFEval (84.1%). 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 OpenAI'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.
7 months newer
Jamba 1.5 Large
AI21 Labs
2024-08-22
GPT-4.1 mini
OpenAI
2025-04-14
Cost per million tokens (USD)
GPT-4.1 mini
Jamba 1.5 Large
Context window and performance specifications
Average performance across 35 common benchmarks
GPT-4.1 mini
Jamba 1.5 Large
Jamba 1.5 Large
2024-03-05
GPT-4.1 mini
2024-05-31
Available providers and their performance metrics
GPT-4.1 mini
OpenAI
ZeroEval
Jamba 1.5 Large
GPT-4.1 mini
Jamba 1.5 Large
GPT-4.1 mini
Jamba 1.5 Large
Bedrock