GPT-5.1 Codex Mini vs Jamba 1.5 Large
GPT-5.1 Codex Mini and Jamba 1.5 Large are closely matched at -2.8 and 0.9 on the LLM Stats Score. GPT-5.1 Codex Mini is 5.1x cheaper per token.
OpenAI · AI21 Labs · Updated for 2026
Which is better?
GPT-5.1 Codex Mini and Jamba 1.5 Large are closely matched on the overall LLM Stats Score at -2.8 and 0.9.
On price, GPT-5.1 Codex Mini is roughly 5.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-5.1 Codex Mini also accepts a larger context window (400,000 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-5.1 Codex Mini
- cost matters — it's about 5.1x cheaper per token
- you process long inputs — it offers a 400,000 token context window
- you want the most recent training data — it shipped Nov 2025
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
1 reported for GPT-5.1 Codex Mini · 8 for Jamba 1.5 Large
GPT-5.1 Codex Mini 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-5.1 Codex Mini ($0.25/1M tokens) is 8.0x cheaper than Jamba 1.5 Large ($2.00/1M tokens).
For output processing, GPT-5.1 Codex Mini ($2.00/1M tokens) is 4.0x cheaper than Jamba 1.5 Large ($8.00/1M tokens).
In conclusion, Jamba 1.5 Large is more expensive than GPT-5.1 Codex Mini.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-5.1 Codex Mini accepts 400,000 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-5.1 Codex Mini is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
GPT-5.1 Codex Mini supports multimodal inputs, whereas Jamba 1.5 Large does not.
GPT-5.1 Codex Mini can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT-5.1 Codex Mini
Jamba 1.5 Large
License
Usage and distribution terms
GPT-5.1 Codex Mini 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-5.1 Codex Mini was released on 2025-11-12, while Jamba 1.5 Large was released on 2024-08-22.
GPT-5.1 Codex Mini is 15 months newer than Jamba 1.5 Large.
Nov 12, 2025
10 months ago
1.2yr newerAug 22, 2024
2.1 years ago
Knowledge Cutoff
When training data ends
Jamba 1.5 Large has a documented knowledge cutoff of 2024-03-05, while GPT-5.1 Codex Mini's cutoff date is not specified.
We can confirm Jamba 1.5 Large's training data extends to 2024-03-05, but cannot make a direct comparison without GPT-5.1 Codex Mini's cutoff date.
—
Mar 2024
Provider Availability
GPT-5.1 Codex Mini is available from OpenAI. Jamba 1.5 Large is available from Bedrock, Google.
GPT-5.1 Codex Mini
Jamba 1.5 Large
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-5.1 Codex Mini and Jamba 1.5 Large side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-5.1 Codex Mini vs Jamba 1.5 Large.