Model Comparison

LongCat-Flash-Chat vs Qwen2.5-Omni-7BWhich is better in 2026?

LongCat-Flash-Chat significantly outperforms across most benchmarks.

Verdict: LongCat-Flash-Chat vs Qwen2.5-Omni-7B — which is better?

LongCat-Flash-Chat (by Meituan) and Qwen2.5-Omni-7B (by Alibaba Cloud / Qwen Team) 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.

LongCat-Flash-Chat outperforms in 3 benchmarks (GPQA, HumanEval, MMLU-Pro), while Qwen2.5-Omni-7B is better at 0 benchmarks. LongCat-Flash-Chat significantly outperforms across most benchmarks.

Choose LongCat-Flash-Chat if…

  • you want the strongest raw capability — it leads on 3 of 3 shared benchmarks
  • you want the most recent training data — it shipped Aug 2025

Choose Qwen2.5-Omni-7B if…

  • you are already invested in the Alibaba Cloud / Qwen Team ecosystem
Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

LongCat-Flash-Chat outperforms in 3 benchmarks (GPQA, HumanEval, MMLU-Pro), while Qwen2.5-Omni-7B is better at 0 benchmarks.

LongCat-Flash-Chat significantly outperforms across most benchmarks.

Mon Jun 15 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

553.0B diff

LongCat-Flash-Chat has 553.0B more parameters than Qwen2.5-Omni-7B, making it 7900.0% larger.

Meituan
LongCat-Flash-Chat
560.0Bparameters
Alibaba Cloud / Qwen Team
Qwen2.5-Omni-7B
7.0Bparameters
560.0B
LongCat-Flash-Chat
7.0B
Qwen2.5-Omni-7B

Context Window

Maximum input and output token capacity

Only LongCat-Flash-Chat specifies input context (128,000 tokens). Only LongCat-Flash-Chat specifies output context (128,000 tokens).

Meituan
LongCat-Flash-Chat
Input128,000 tokens
Output128,000 tokens
Alibaba Cloud / Qwen Team
Qwen2.5-Omni-7B
Input- tokens
Output- tokens
Mon Jun 15 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen2.5-Omni-7B supports multimodal inputs, whereas LongCat-Flash-Chat does not.

Qwen2.5-Omni-7B can handle both text and other forms of data like images, making it suitable for multimodal applications.

LongCat-Flash-Chat

Text
Images
Audio
Video

Qwen2.5-Omni-7B

Text
Images
Audio
Video

License

Usage and distribution terms

LongCat-Flash-Chat is licensed under MIT, 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.

LongCat-Flash-Chat

MIT

Open weights

Qwen2.5-Omni-7B

Apache 2.0

Open weights

Release Timeline

When each model was launched

LongCat-Flash-Chat was released on 2025-08-29, while Qwen2.5-Omni-7B was released on 2025-03-27.

LongCat-Flash-Chat is 5 months newer than Qwen2.5-Omni-7B.

LongCat-Flash-Chat

Aug 29, 2025

9 months ago

5mo newer
Qwen2.5-Omni-7B

Mar 27, 2025

1.2 years ago

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Meituan
Larger context window (128,000 tokens)
Higher GPQA score (73.2% vs 30.8%)
Higher HumanEval score (88.4% vs 78.7%)
Higher MMLU-Pro score (82.7% vs 47.0%)
Alibaba Cloud / Qwen Team

Qwen2.5-Omni-7B

View details

Alibaba Cloud / Qwen Team

Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature
Meituan
LongCat-Flash-Chat
Alibaba Cloud / Qwen Team
Qwen2.5-Omni-7B

FAQ

Common questions about LongCat-Flash-Chat vs Qwen2.5-Omni-7B.

Which is better, LongCat-Flash-Chat or Qwen2.5-Omni-7B?

LongCat-Flash-Chat significantly outperforms across most benchmarks. LongCat-Flash-Chat is made by Meituan and Qwen2.5-Omni-7B is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does LongCat-Flash-Chat compare to Qwen2.5-Omni-7B in benchmarks?

LongCat-Flash-Chat scores MATH-500: 96.4%, MMLU: 89.7%, IFEval: 89.6%, ZebraLogic: 89.3%, HumanEval: 88.4%. 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 LongCat-Flash-Chat and Qwen2.5-Omni-7B?

LongCat-Flash-Chat supports 128K 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 LongCat-Flash-Chat and Qwen2.5-Omni-7B?

Key differences include multimodal support (no vs yes), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes LongCat-Flash-Chat and Qwen2.5-Omni-7B?

LongCat-Flash-Chat is developed by Meituan and Qwen2.5-Omni-7B is developed by Alibaba Cloud / Qwen Team.

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