GPT-6 Astra vs Jamba 1.5 Large
GPT-6 Astra leads the LLM Stats Score 60.7 to 1.1. Jamba 1.5 Large is 5.7x cheaper per token.
OpenAI · AI21 Labs · Updated for 2026
Which is better?
GPT-6 Astra leads the overall LLM Stats Score 60.7 to 1.1, ranking #1 overall.
In the 1 individual benchmarks reported for both models, GPT-6 Astra wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, Jamba 1.5 Large is roughly 5.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-6 Astra 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 Astra
- overall performance matters — it scores 60.7 and ranks #1 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- 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
- cost matters — it's about 5.7x cheaper per token
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
22 reported for GPT-6 Astra · 8 for Jamba 1.5 Large
GPT-6 Astra outperforms in 1 benchmarks (GPQA), while Jamba 1.5 Large is better at 0 benchmarks.
GPT-6 Astra significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-6 Astra ($10.00/1M tokens) is 5.0x more expensive than Jamba 1.5 Large ($2.00/1M tokens).
For output processing, GPT-6 Astra ($50.00/1M tokens) is 6.3x more expensive than Jamba 1.5 Large ($8.00/1M tokens).
In conclusion, GPT-6 Astra is more expensive than Jamba 1.5 Large.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-6 Astra 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 Astra is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
GPT-6 Astra supports multimodal inputs, whereas Jamba 1.5 Large does not.
GPT-6 Astra can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT-6 Astra
Jamba 1.5 Large
License
Usage and distribution terms
GPT-6 Astra 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 Astra was released on 2026-09-03, while Jamba 1.5 Large was released on 2024-08-22.
GPT-6 Astra is 25 months newer than Jamba 1.5 Large.
Sep 3, 2026
0 days ago
2.0yr newerAug 22, 2024
2.0 years ago
Knowledge Cutoff
When training data ends
GPT-6 Astra has a knowledge cutoff of 2026-04-30, while Jamba 1.5 Large has a cutoff of 2024-03-05.
GPT-6 Astra has more recent training data (up to 2026-04-30), making it potentially better informed about events through that date compared to Jamba 1.5 Large (2024-03-05).
Apr 2026
2.1 yr newerMar 2024
Provider Availability
GPT-6 Astra is available from OpenAI. Jamba 1.5 Large is available from Bedrock, Google.
GPT-6 Astra
Jamba 1.5 Large
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-6 Astra and Jamba 1.5 Large side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-6 Astra vs Jamba 1.5 Large.