GPT-6 Luna vs Jamba 1.5 Large
GPT-6 Luna leads the LLM Stats Score 44.5 to 0.9. GPT-6 Luna is 17.5x cheaper per token.
OpenAI · AI21 Labs · Updated for 2026
Which is better?
GPT-6 Luna leads the overall LLM Stats Score 44.5 to 0.9, ranking #41 overall.
On price, GPT-6 Luna is roughly 17.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-6 Luna also accepts a larger context window (1,050,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose GPT-6 Luna
- overall performance matters — it scores 44.5 and ranks #41 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- cost matters — it's about 17.5x cheaper per token
- you process long inputs — it offers a 1,050,000 token context window
- you want the most recent training data — it shipped Sep 2026
Choose Jamba 1.5 Large
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Individual benchmarks
5 reported for GPT-6 Luna · 8 for Jamba 1.5 Large
GPT-6 Luna and Jamba 1.5 Largedon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-6 Luna ($0.10/1M tokens) is 20.0x cheaper than Jamba 1.5 Large ($2.00/1M tokens).
For output processing, GPT-6 Luna ($0.50/1M tokens) is 16.0x cheaper than Jamba 1.5 Large ($8.00/1M tokens).
In conclusion, Jamba 1.5 Large is more expensive than GPT-6 Luna.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-6 Luna accepts 1,050,000 input tokens compared to Jamba 1.5 Large's 256,000 tokens. Jamba 1.5 Large can generate longer responses up to 256,000 tokens, while GPT-6 Luna is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
GPT-6 Luna supports multimodal inputs, whereas Jamba 1.5 Large does not.
GPT-6 Luna can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT-6 Luna
Jamba 1.5 Large
License
Usage and distribution terms
GPT-6 Luna is licensed under a proprietary license, while Jamba 1.5 Large 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-6 Luna was released on 2026-09-22, while Jamba 1.5 Large was released on 2024-08-22.
GPT-6 Luna is 25 months newer than Jamba 1.5 Large.
Sep 22, 2026
0 days ago
2.1yr newerAug 22, 2024
2.1 years ago
Knowledge Cutoff
When training data ends
GPT-6 Luna has a knowledge cutoff of 2026-05-18, while Jamba 1.5 Large has a cutoff of 2024-03-05.
GPT-6 Luna has more recent training data (up to 2026-05-18), making it potentially better informed about events through that date compared to Jamba 1.5 Large (2024-03-05).
May 2026
2.2 yr newerMar 2024
Provider Availability
GPT-6 Luna is available from OpenAI. Jamba 1.5 Large is available from Bedrock, Google.
GPT-6 Luna
Jamba 1.5 Large
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-6 Luna and Jamba 1.5 Large side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-6 Luna vs Jamba 1.5 Large.