Comprehensive side-by-side LLM comparison
GPT-4.1 nano leads with 6.1% higher average benchmark score. GPT-4.1 nano offers 568.3K more tokens in context window than Jamba 1.5 Large. GPT-4.1 nano is $9.50 cheaper per million tokens. GPT-4.1 nano supports multimodal inputs. Overall, GPT-4.1 nano is the stronger choice for coding tasks.
OpenAI
GPT-4.1 Nano was developed as the smallest and most efficient variant in the GPT-4.1 family, designed for applications requiring minimal latency and resource usage. Built to enable AI capabilities on edge devices and resource-constrained environments, it distills GPT-4.1 capabilities into an ultra-compact form factor.
AI21 Labs
Jamba 1.5 Large was developed by AI21 Labs using a hybrid architecture combining transformer and state space models, designed to provide efficient long-context understanding. Built to handle extended documents and conversations with computational efficiency, it represents AI21's innovation in efficient large-scale model design.
7 months newer
Jamba 1.5 Large
AI21 Labs
2024-08-22

GPT-4.1 nano
OpenAI
2025-04-14
Cost per million tokens (USD)

GPT-4.1 nano
Jamba 1.5 Large
Context window and performance specifications
Average performance across 2 common benchmarks

GPT-4.1 nano
Jamba 1.5 Large
Jamba 1.5 Large
2024-03-05
GPT-4.1 nano
2024-05-31
Available providers and their performance metrics

GPT-4.1 nano
OpenAI
Jamba 1.5 Large

GPT-4.1 nano
Jamba 1.5 Large

GPT-4.1 nano
Jamba 1.5 Large
Bedrock