Model Comparison
Jamba 1.5 Large vs Pixtral-12BWhich is better in 2026?
Jamba 1.5 Large significantly outperforms across most benchmarks. Pixtral-12B is 23.3x cheaper per token.
Verdict: Jamba 1.5 Large vs Pixtral-12B — which is better?
Jamba 1.5 Large (by AI21 Labs) and Pixtral-12B (by Mistral AI) 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.
Jamba 1.5 Large outperforms in 1 benchmarks (MMLU), while Pixtral-12B is better at 0 benchmarks. Jamba 1.5 Large significantly outperforms across most benchmarks.
On price, Pixtral-12B is roughly 23.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Jamba 1.5 Large also accepts a larger context window (256,000 input tokens), making it the stronger choice for long documents and large codebases.
Choose Jamba 1.5 Large if…
- you want the strongest raw capability — it leads on 1 of 1 shared benchmarks
- you process long inputs — it offers a 256,000 token context window
Choose Pixtral-12B if…
- cost matters — it's about 23.3x cheaper per token
- you want the most recent training data — it shipped Sep 2024
Performance Benchmarks
Comparative analysis across standard metrics
Jamba 1.5 Large outperforms in 1 benchmarks (MMLU), while Pixtral-12B is better at 0 benchmarks.
Jamba 1.5 Large significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, Jamba 1.5 Large ($2.00/1M tokens) is 13.3x more expensive than Pixtral-12B ($0.15/1M tokens).
For output processing, Jamba 1.5 Large ($8.00/1M tokens) is 53.3x more expensive than Pixtral-12B ($0.15/1M tokens).
In conclusion, Jamba 1.5 Large is more expensive than Pixtral-12B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Jamba 1.5 Large has 385.6B more parameters than Pixtral-12B, making it 3109.7% larger.
Context Window
Maximum input and output token capacity
Jamba 1.5 Large accepts 256,000 input tokens compared to Pixtral-12B's 128,000 tokens. Jamba 1.5 Large can generate longer responses up to 256,000 tokens, while Pixtral-12B is limited to 8,192 tokens.
Input Capabilities
Supported data types and modalities
Pixtral-12B supports multimodal inputs, whereas Jamba 1.5 Large does not.
Pixtral-12B can handle both text and other forms of data like images, making it suitable for multimodal applications.
Jamba 1.5 Large
Pixtral-12B
License
Usage and distribution terms
Jamba 1.5 Large is licensed under Jamba Open Model License, while Pixtral-12B uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
Jamba Open Model License
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
Jamba 1.5 Large was released on 2024-08-22, while Pixtral-12B was released on 2024-09-17.
Pixtral-12B is 1 month newer than Jamba 1.5 Large.
Aug 22, 2024
1.9 years ago
Sep 17, 2024
1.9 years ago
3w newerKnowledge Cutoff
When training data ends
Jamba 1.5 Large has a documented knowledge cutoff of 2024-03-05, while Pixtral-12B'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 Pixtral-12B's cutoff date.
Mar 2024
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Provider Availability
Jamba 1.5 Large is available from Bedrock, Google. Pixtral-12B is available from Mistral AI.
Jamba 1.5 Large
Pixtral-12B
Outputs Comparison
Key Takeaways
Jamba 1.5 Large
View detailsAI21 Labs
Pixtral-12B
View detailsMistral AI
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against Jamba 1.5 Large and Pixtral-12B side-by-side, then vote on the output you prefer.
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FAQ
Common questions about Jamba 1.5 Large vs Pixtral-12B.