Jamba 1.5 Mini vs MiMo-V2.6-Flash
MiMo-V2.6-Flash leads the LLM Stats Score 45.6 to -5.7. MiMo-V2.6-Flash is 1.4x cheaper per token.
AI21 Labs · Xiaomi · Updated for 2026
Which is better?
MiMo-V2.6-Flash leads the overall LLM Stats Score 45.6 to -5.7, ranking #29 overall.
On price, MiMo-V2.6-Flash is roughly 1.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
MiMo-V2.6-Flash also accepts a larger context window (1,048,576 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 Mini
- you want predictable pricing at $0.20/M input and $0.40/M output
Choose MiMo-V2.6-Flash
- overall performance matters — it scores 45.6 and ranks #29 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- cost matters — it's about 1.4x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Sep 2026
At a glance
The differences that matter most.
Individual benchmarks
8 reported for Jamba 1.5 Mini · 16 for MiMo-V2.6-Flash
Jamba 1.5 Mini and MiMo-V2.6-Flashdon'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, Jamba 1.5 Mini ($0.20/1M tokens) is 1.4x more expensive than MiMo-V2.6-Flash ($0.14/1M tokens).
For output processing, Jamba 1.5 Mini ($0.40/1M tokens) is 1.4x more expensive than MiMo-V2.6-Flash ($0.28/1M tokens).
In conclusion, Jamba 1.5 Mini is more expensive than MiMo-V2.6-Flash.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
MiMo-V2.6-Flash has 257.0B more parameters than Jamba 1.5 Mini, making it 494.2% larger.
Context Window
Maximum input and output token capacity
MiMo-V2.6-Flash accepts 1,048,576 input tokens compared to Jamba 1.5 Mini's 256,144 tokens. Only Jamba 1.5 Mini specifies output context (256,144 tokens).
Input capabilities
Documented input modalities across available providers
MiMo-V2.6-Flash supports multimodal inputs, whereas Jamba 1.5 Mini does not.
MiMo-V2.6-Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.
Jamba 1.5 Mini
MiMo-V2.6-Flash
License
Usage and distribution terms
Jamba 1.5 Mini is licensed under Jamba Open Model License, while MiMo-V2.6-Flash uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
Jamba Open Model License
Open weights
MIT
Open weights
Release Timeline
When each model was launched
Jamba 1.5 Mini was released on 2024-08-22, while MiMo-V2.6-Flash was released on 2026-09-22.
MiMo-V2.6-Flash is 25 months newer than Jamba 1.5 Mini.
Aug 22, 2024
2.1 years ago
Sep 22, 2026
-1 days ago
2.1yr newerKnowledge Cutoff
When training data ends
Jamba 1.5 Mini has a documented knowledge cutoff of 2024-03-05, while MiMo-V2.6-Flash's cutoff date is not specified.
We can confirm Jamba 1.5 Mini's training data extends to 2024-03-05, but cannot make a direct comparison without MiMo-V2.6-Flash's cutoff date.
Mar 2024
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Provider Availability
Jamba 1.5 Mini is available from Bedrock, Google. MiMo-V2.6-Flash is available from Xiaomi.
Jamba 1.5 Mini
MiMo-V2.6-Flash
Outputs Comparison
Judge for yourself.
Run your own prompts against Jamba 1.5 Mini and MiMo-V2.6-Flash side-by-side, then vote on the output you prefer.
FAQ
Common questions about Jamba 1.5 Mini vs MiMo-V2.6-Flash.