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Jamba 1.5 Large vs MiMo-V2.6-Flash

MiMo-V2.6-Flash leads the LLM Stats Score 45.7 to 0.9.

AI21 Labs · Xiaomi · Updated for 2026

Which is better?

MiMo-V2.6-Flash leads the overall LLM Stats Score 45.7 to 0.9, ranking #29 overall.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose Jamba 1.5 Large

  • you want predictable pricing at $2.00/M input and $8.00/M output

Choose MiMo-V2.6-Flash

  • overall performance matters — it scores 45.7 and ranks #29 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you want the most recent training data — it shipped Sep 2026

At a glance

The differences that matter most.

Core performance indexes
0.9
#325
45.7
#29
1.0
#316
43.2
#42
Cost, coverage & limits
Benchmark wins
Input price
$2.00 / M
— / M
Output price
$8.00 / M
— / M
Context window
256,000

Individual benchmarks

8 reported for Jamba 1.5 Large · 16 for MiMo-V2.6-Flash

No common benchmarks found

Jamba 1.5 Large 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

Model Size

Parameter count comparison

89.0B diff

Jamba 1.5 Large has 89.0B more parameters than MiMo-V2.6-Flash, making it 28.8% larger.

AI21 Labs
Jamba 1.5 Large
398.0Bparameters
Xiaomi
MiMo-V2.6-Flash
309.0Bparameters
398.0B
Jamba 1.5 Large
309.0B
MiMo-V2.6-Flash

Context Window

Maximum input and output token capacity

Only Jamba 1.5 Large specifies input context (256,000 tokens). Only Jamba 1.5 Large specifies output context (256,000 tokens).

AI21 Labs
Jamba 1.5 Large
Input256,000 tokens
Output256,000 tokens
Xiaomi
MiMo-V2.6-Flash
Input- tokens
Output- tokens
Tue Sep 22 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

MiMo-V2.6-Flash supports multimodal inputs, whereas Jamba 1.5 Large 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 Large

Text
Images
Audio
Video

MiMo-V2.6-Flash

Text
Images
Audio
Video

License

Usage and distribution terms

Jamba 1.5 Large 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 1.5 Large

Jamba Open Model License

Open weights

MiMo-V2.6-Flash

MIT

Open weights

Release Timeline

When each model was launched

Jamba 1.5 Large 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 Large.

Jamba 1.5 Large

Aug 22, 2024

2.1 years ago

MiMo-V2.6-Flash

Sep 22, 2026

-1 days ago

2.1yr newer

Knowledge Cutoff

When training data ends

Jamba 1.5 Large 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 Large's training data extends to 2024-03-05, but cannot make a direct comparison without MiMo-V2.6-Flash's cutoff date.

Jamba 1.5 Large

Mar 2024

MiMo-V2.6-Flash

Outputs Comparison

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Judge for yourself.

Run your own prompts against Jamba 1.5 Large and MiMo-V2.6-Flash side-by-side, then vote on the output you prefer.

Jamba 1.5 Large
✓ Preferred
MiMo-V2.6-Flash
Open in Playground

FAQ

Common questions about Jamba 1.5 Large vs MiMo-V2.6-Flash.

Which is better, Jamba 1.5 Large or MiMo-V2.6-Flash?

MiMo-V2.6-Flash leads the LLM Stats Score 45.7 to 0.9. Jamba 1.5 Large is made by AI21 Labs and MiMo-V2.6-Flash is made by Xiaomi. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Jamba 1.5 Large compare to MiMo-V2.6-Flash in benchmarks?

Jamba 1.5 Large scores ARC-C: 93.0%, GSM8k: 87.0%, MMLU: 81.2%, Arena Hard: 65.4%, TruthfulQA: 58.3%. MiMo-V2.6-Flash scores CyberGym: 95.1%, Terminal-Bench 2.1: 87.6%, OSWorld-Verified: 80.8%, MiMo Cyber Bench: 77.2%, Toolathlon-Verified: 73.6%.

What are the context window sizes for Jamba 1.5 Large and MiMo-V2.6-Flash?

Jamba 1.5 Large supports 256K tokens and MiMo-V2.6-Flash supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Jamba 1.5 Large and MiMo-V2.6-Flash?

Key differences include LLM Stats Score (0.9 vs 45.7), multimodal support (no vs yes), licensing (Jamba Open Model License vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes Jamba 1.5 Large and MiMo-V2.6-Flash?

Jamba 1.5 Large is developed by AI21 Labs and MiMo-V2.6-Flash is developed by Xiaomi.