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Jamba 1.5 Large vs Qwen2.5-Omni-7B

Jamba 1.5 Large and Qwen2.5-Omni-7B are closely matched at 0.9 and 5.2 on the LLM Stats Score.

AI21 Labs · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Jamba 1.5 Large and Qwen2.5-Omni-7B are closely matched on the overall LLM Stats Score at 0.9 and 5.2.

In the 3 individual benchmarks reported for both models, Jamba 1.5 Large wins 2; this is a narrower head-to-head signal than the composite indexes.

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

Choose Jamba 1.5 Large

  • you value its reported benchmark strengths — it wins 2 of 3 exact shared results

Choose Qwen2.5-Omni-7B

  • you want the most recent training data — it shipped Mar 2025

At a glance

The differences that matter most.

Core performance indexes
0.9
#328
5.2
#305
1.0
#320
1.4
#318
Cost, coverage & limits
Benchmark wins
2 of 3
1 of 3
Input price
$2.00 / M
— / M
Output price
$8.00 / M
— / M
Context window
256,000

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
Jamba 1.5 Large
Qwen2.5-Omni-7B
4.4#283
5.0#274
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

8 reported for Jamba 1.5 Large · 45 for Qwen2.5-Omni-7B

3 shared

Jamba 1.5 Large outperforms in 2 benchmarks (GPQA, MMLU-Pro), while Qwen2.5-Omni-7B is better at 1 benchmark (GSM8k).

Jamba 1.5 Large shows notably better performance in the majority of benchmarks.

Wed Sep 23 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

391.0B diff

Jamba 1.5 Large has 391.0B more parameters than Qwen2.5-Omni-7B, making it 5585.7% larger.

AI21 Labs
Jamba 1.5 Large
398.0Bparameters
Alibaba Cloud / Qwen Team
Qwen2.5-Omni-7B
7.0Bparameters
398.0B
Jamba 1.5 Large
7.0B
Qwen2.5-Omni-7B

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
Alibaba Cloud / Qwen Team
Qwen2.5-Omni-7B
Input- tokens
Output- tokens
Wed Sep 23 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Qwen2.5-Omni-7B supports multimodal inputs, whereas Jamba 1.5 Large does not.

Qwen2.5-Omni-7B 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

Qwen2.5-Omni-7B

Text
Images
Audio
Video

License

Usage and distribution terms

Jamba 1.5 Large is licensed under Jamba Open Model License, while Qwen2.5-Omni-7B uses Apache 2.0.

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

Qwen2.5-Omni-7B

Apache 2.0

Open weights

Release Timeline

When each model was launched

Jamba 1.5 Large was released on 2024-08-22, while Qwen2.5-Omni-7B was released on 2025-03-27.

Qwen2.5-Omni-7B is 7 months newer than Jamba 1.5 Large.

Jamba 1.5 Large

Aug 22, 2024

2.1 years ago

Qwen2.5-Omni-7B

Mar 27, 2025

1.5 years ago

7mo newer

Knowledge Cutoff

When training data ends

Jamba 1.5 Large has a documented knowledge cutoff of 2024-03-05, while Qwen2.5-Omni-7B'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 Qwen2.5-Omni-7B's cutoff date.

Jamba 1.5 Large

Mar 2024

Qwen2.5-Omni-7B

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against Jamba 1.5 Large and Qwen2.5-Omni-7B side-by-side, then vote on the output you prefer.

Jamba 1.5 Large
✓ Preferred
Qwen2.5-Omni-7B
Open in Playground

FAQ

Common questions about Jamba 1.5 Large vs Qwen2.5-Omni-7B.

Which is better, Jamba 1.5 Large or Qwen2.5-Omni-7B?

Jamba 1.5 Large and Qwen2.5-Omni-7B are closely matched on the LLM Stats Score at 0.9 and 5.2. Jamba 1.5 Large is made by AI21 Labs and Qwen2.5-Omni-7B is made by Alibaba Cloud / Qwen Team. 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 Qwen2.5-Omni-7B in benchmarks?

Jamba 1.5 Large scores ARC-C: 93.0%, GSM8k: 87.0%, MMLU: 81.2%, Arena Hard: 65.4%, TruthfulQA: 58.3%. Qwen2.5-Omni-7B scores FLEURS: 95.9%, DocVQA: 95.2%, VocalSound: 93.9%, GSM8k: 88.7%, GiantSteps Tempo: 88.0%.

What are the context window sizes for Jamba 1.5 Large and Qwen2.5-Omni-7B?

Jamba 1.5 Large supports 256K tokens and Qwen2.5-Omni-7B 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 Qwen2.5-Omni-7B?

Key differences include LLM Stats Score (0.9 vs 5.2), multimodal support (no vs yes), licensing (Jamba Open Model License vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Jamba 1.5 Large and Qwen2.5-Omni-7B?

Jamba 1.5 Large is developed by AI21 Labs and Qwen2.5-Omni-7B is developed by Alibaba Cloud / Qwen Team.