Jamba 1.5 Large vs Mistral Large 3
Mistral Large 3 leads the LLM Stats Score 10.4 to 0.9. Mistral Large 3 is 1.3x cheaper per token.
AI21 Labs · Mistral AI · Updated for 2026
Which is better?
Mistral Large 3 leads the overall LLM Stats Score 10.4 to 0.9, ranking #263 overall.
The models split the 2 individual benchmarks reported for both models evenly.
On price, Mistral Large 3 is roughly 1.3x 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.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Jamba 1.5 Large
- you process long inputs — it offers a 256,000 token context window
Choose Mistral Large 3
- overall performance matters — it scores 10.4 and ranks #263 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- cost matters — it's about 1.3x cheaper per token
- you want the most recent training data — it shipped Sep 2025
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
8 reported for Jamba 1.5 Large · 8 for Mistral Large 3
Jamba 1.5 Large outperforms in 1 benchmarks (Arena Hard), while Mistral Large 3 is better at 1 benchmark (Wild Bench).
Both models are evenly matched across the benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Jamba 1.5 Large ($2.00/1M tokens) costs the same as Mistral Large 3 ($2.00/1M tokens).
For output processing, Jamba 1.5 Large ($8.00/1M tokens) is 1.6x more expensive than Mistral Large 3 ($5.00/1M tokens).
In conclusion, Jamba 1.5 Large is more expensive than Mistral Large 3.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Mistral Large 3 has 277.0B more parameters than Jamba 1.5 Large, making it 69.6% larger.
Context Window
Maximum input and output token capacity
Jamba 1.5 Large accepts 256,000 input tokens compared to Mistral Large 3's 128,000 tokens. Jamba 1.5 Large can generate longer responses up to 256,000 tokens, while Mistral Large 3 is limited to 8,192 tokens.
Input capabilities
Documented input modalities across available providers
Mistral Large 3 supports multimodal inputs, whereas Jamba 1.5 Large does not.
Mistral Large 3 can handle both text and other forms of data like images, making it suitable for multimodal applications.
Jamba 1.5 Large
Mistral Large 3
License
Usage and distribution terms
Jamba 1.5 Large is licensed under Jamba Open Model License, while Mistral Large 3 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 Mistral Large 3 was released on 2025-09-01.
Mistral Large 3 is 13 months newer than Jamba 1.5 Large.
Aug 22, 2024
2.1 years ago
Sep 1, 2025
1.1 years ago
1.0yr newerKnowledge Cutoff
When training data ends
Jamba 1.5 Large has a documented knowledge cutoff of 2024-03-05, while Mistral Large 3'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 Mistral Large 3's cutoff date.
Mar 2024
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Provider Availability
Jamba 1.5 Large is available from Bedrock, Google. Mistral Large 3 is available from Mistral AI.
Jamba 1.5 Large
Mistral Large 3
Outputs Comparison
Judge for yourself.
Run your own prompts against Jamba 1.5 Large and Mistral Large 3 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Jamba 1.5 Large vs Mistral Large 3.