Model Comparison
GPT-5 nano vs Jamba 1.5 MiniWhich is better in 2026?
GPT-5 nano significantly outperforms across most benchmarks. GPT-5 nano is 1.8x cheaper per token.
Verdict: GPT-5 nano vs Jamba 1.5 Mini — which is better?
GPT-5 nano (by OpenAI) and Jamba 1.5 Mini (by AI21 Labs) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
GPT-5 nano outperforms in 1 benchmarks (GPQA), while Jamba 1.5 Mini is better at 0 benchmarks. GPT-5 nano significantly outperforms across most benchmarks.
On price, GPT-5 nano is roughly 1.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-5 nano also accepts a larger context window (400,000 input tokens), making it the stronger choice for long documents and large codebases.
Choose GPT-5 nano if…
- you want the strongest raw capability — it leads on 1 of 1 shared benchmarks
- cost matters — it's about 1.8x cheaper per token
- you process long inputs — it offers a 400,000 token context window
- you want the most recent training data — it shipped Aug 2025
Choose Jamba 1.5 Mini if…
- you need open weights you can self-host or fine-tune
Performance Benchmarks
Comparative analysis across standard metrics
GPT-5 nano outperforms in 1 benchmarks (GPQA), while Jamba 1.5 Mini is better at 0 benchmarks.
GPT-5 nano significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-5 nano ($0.05/1M tokens) is 4.0x cheaper than Jamba 1.5 Mini ($0.20/1M tokens).
For output processing, GPT-5 nano ($0.40/1M tokens) costs the same as Jamba 1.5 Mini ($0.40/1M tokens).
In conclusion, Jamba 1.5 Mini is more expensive than GPT-5 nano.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-5 nano accepts 400,000 input tokens compared to Jamba 1.5 Mini's 256,144 tokens. Jamba 1.5 Mini can generate longer responses up to 256,144 tokens, while GPT-5 nano is limited to 128,000 tokens.
Input Capabilities
Supported data types and modalities
GPT-5 nano supports multimodal inputs, whereas Jamba 1.5 Mini does not.
GPT-5 nano can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT-5 nano
Jamba 1.5 Mini
License
Usage and distribution terms
GPT-5 nano is licensed under a proprietary license, while Jamba 1.5 Mini uses Jamba Open Model License.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Jamba Open Model License
Open weights
Release Timeline
When each model was launched
GPT-5 nano was released on 2025-08-07, while Jamba 1.5 Mini was released on 2024-08-22.
GPT-5 nano is 12 months newer than Jamba 1.5 Mini.
Aug 7, 2025
11 months ago
11mo newerAug 22, 2024
1.9 years ago
Knowledge Cutoff
When training data ends
GPT-5 nano has a knowledge cutoff of 2024-05-30, while Jamba 1.5 Mini has a cutoff of 2024-03-05.
GPT-5 nano has more recent training data (up to 2024-05-30), making it potentially better informed about events through that date compared to Jamba 1.5 Mini (2024-03-05).
May 2024
2 mo newerMar 2024
Provider Availability
GPT-5 nano is available from OpenAI. Jamba 1.5 Mini is available from Bedrock, Google.
GPT-5 nano
Jamba 1.5 Mini
Outputs Comparison
Key Takeaways
GPT-5 nano
View detailsOpenAI
Jamba 1.5 Mini
View detailsAI21 Labs
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against GPT-5 nano and Jamba 1.5 Mini side-by-side, then vote on the output you prefer.
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FAQ
Common questions about GPT-5 nano vs Jamba 1.5 Mini.