Model Comparison
Jamba 1.5 Large vs MiMo-V2-FlashWhich is better in 2026?
MiMo-V2-Flash significantly outperforms across most benchmarks. MiMo-V2-Flash is 23.3x cheaper per token.
Verdict: Jamba 1.5 Large vs MiMo-V2-Flash — which is better?
Jamba 1.5 Large (by AI21 Labs) and MiMo-V2-Flash (by Xiaomi) 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 0 benchmarks, while MiMo-V2-Flash is better at 2 benchmarks (GPQA, MMLU-Pro). MiMo-V2-Flash significantly outperforms across most benchmarks.
On price, MiMo-V2-Flash is roughly 23.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Choose Jamba 1.5 Large if…
- you want predictable pricing at $2.00/M input and $8.00/M output
Choose MiMo-V2-Flash if…
- you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
- cost matters — it's about 23.3x cheaper per token
- you want the most recent training data — it shipped Dec 2025
Performance Benchmarks
Comparative analysis across standard metrics
Jamba 1.5 Large outperforms in 0 benchmarks, while MiMo-V2-Flash is better at 2 benchmarks (GPQA, MMLU-Pro).
MiMo-V2-Flash 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 20.0x more expensive than MiMo-V2-Flash ($0.10/1M tokens).
For output processing, Jamba 1.5 Large ($8.00/1M tokens) is 26.7x more expensive than MiMo-V2-Flash ($0.30/1M tokens).
In conclusion, Jamba 1.5 Large is more expensive than MiMo-V2-Flash.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Jamba 1.5 Large has 89.0B more parameters than MiMo-V2-Flash, making it 28.8% larger.
Context Window
Maximum input and output token capacity
Both models have the same input context window of 256,000 tokens. Jamba 1.5 Large can generate longer responses up to 256,000 tokens, while MiMo-V2-Flash is limited to 16,384 tokens.
License
Usage and distribution terms
Jamba 1.5 Large is licensed under Jamba Open Model License, while MiMo-V2-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 Large was released on 2024-08-22, while MiMo-V2-Flash was released on 2025-12-16.
MiMo-V2-Flash is 16 months newer than Jamba 1.5 Large.
Aug 22, 2024
1.9 years ago
Dec 16, 2025
7 months ago
1.3yr newerKnowledge Cutoff
When training data ends
Jamba 1.5 Large has a documented knowledge cutoff of 2024-03-05, while MiMo-V2-Flash'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 MiMo-V2-Flash's cutoff date.
Mar 2024
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Provider Availability
Jamba 1.5 Large is available from Bedrock, Google. MiMo-V2-Flash is available from Xiaomi.
Jamba 1.5 Large
MiMo-V2-Flash
Outputs Comparison
Key Takeaways
Jamba 1.5 Large
View detailsAI21 Labs
No standout differentiators in the data we have for this pair.
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against Jamba 1.5 Large and MiMo-V2-Flash side-by-side, then vote on the output you prefer.
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FAQ
Common questions about Jamba 1.5 Large vs MiMo-V2-Flash.