Model Comparison

LongCat-Flash-Thinking vs Qwen3 VL 30B A3B Thinking

LongCat-Flash-Thinking significantly outperforms across most benchmarks. Qwen3 VL 30B A3B Thinking is 1.3x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

5 benchmarks

LongCat-Flash-Thinking outperforms in 4 benchmarks (AIME 2025, BFCL-v3, GPQA, MMLU-Pro), while Qwen3 VL 30B A3B Thinking is better at 1 benchmark (MMLU-Redux).

LongCat-Flash-Thinking significantly outperforms across most benchmarks.

Sat Apr 18 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Qwen3 VL 30B A3B Thinking costs less

For input processing, LongCat-Flash-Thinking ($0.30/1M tokens) is 1.5x more expensive than Qwen3 VL 30B A3B Thinking ($0.20/1M tokens).

For output processing, LongCat-Flash-Thinking ($1.20/1M tokens) is 1.2x more expensive than Qwen3 VL 30B A3B Thinking ($0.99/1M tokens).

In conclusion, LongCat-Flash-Thinking is more expensive than Qwen3 VL 30B A3B Thinking.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Sat Apr 18 2026 • llm-stats.com
Meituan
LongCat-Flash-Thinking
Input tokens$0.30
Output tokens$1.20
Best providerMeituan
Alibaba Cloud / Qwen Team
Qwen3 VL 30B A3B Thinking
Input tokens$0.20
Output tokens$0.99
Best providerNovita
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Model Size

Parameter count comparison

529.0B diff

LongCat-Flash-Thinking has 529.0B more parameters than Qwen3 VL 30B A3B Thinking, making it 1706.5% larger.

Meituan
LongCat-Flash-Thinking
560.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 30B A3B Thinking
31.0Bparameters
560.0B
LongCat-Flash-Thinking
31.0B
Qwen3 VL 30B A3B Thinking

Context Window

Maximum input and output token capacity

Qwen3 VL 30B A3B Thinking accepts 131,072 input tokens compared to LongCat-Flash-Thinking's 128,000 tokens. LongCat-Flash-Thinking can generate longer responses up to 128,000 tokens, while Qwen3 VL 30B A3B Thinking is limited to 32,768 tokens.

Meituan
LongCat-Flash-Thinking
Input128,000 tokens
Output128,000 tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 30B A3B Thinking
Input131,072 tokens
Output32,768 tokens
Sat Apr 18 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3 VL 30B A3B Thinking supports multimodal inputs, whereas LongCat-Flash-Thinking does not.

Qwen3 VL 30B A3B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.

LongCat-Flash-Thinking

Text
Images
Audio
Video

Qwen3 VL 30B A3B Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

LongCat-Flash-Thinking is licensed under MIT, while Qwen3 VL 30B A3B Thinking uses Apache 2.0.

License differences may affect how you can use these models in commercial or open-source projects.

LongCat-Flash-Thinking

MIT

Open weights

Qwen3 VL 30B A3B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

Both models were released on 2025-09-22.

They likely represent similar generations of model development.

LongCat-Flash-Thinking

Sep 22, 2025

6 months ago

Qwen3 VL 30B A3B Thinking

Sep 22, 2025

6 months 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

Provider Availability

LongCat-Flash-Thinking is available from Meituan. Qwen3 VL 30B A3B Thinking is available from Novita, DeepInfra.

LongCat-Flash-Thinking

meituan logo
Meituan
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M

Qwen3 VL 30B A3B Thinking

novita logo
Novita
Input Price:Input: $0.20/1MOutput Price:Output: $1.00/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.29/1MOutput Price:Output: $0.99/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Meituan
Higher AIME 2025 score (90.6% vs 83.1%)
Higher BFCL-v3 score (74.4% vs 68.6%)
Higher GPQA score (81.5% vs 74.4%)
Higher MMLU-Pro score (82.6% vs 80.5%)
Alibaba Cloud / Qwen Team

Qwen3 VL 30B A3B Thinking

View details

Alibaba Cloud / Qwen Team

Larger context window (131,072 tokens)
Supports multimodal inputs
Less expensive input tokens
Less expensive output tokens
Higher MMLU-Redux score (90.9% vs 89.3%)

Detailed Comparison

AI Model Comparison Table
Feature
Meituan
LongCat-Flash-Thinking
Alibaba Cloud / Qwen Team
Qwen3 VL 30B A3B Thinking

FAQ

Common questions about LongCat-Flash-Thinking vs Qwen3 VL 30B A3B Thinking

LongCat-Flash-Thinking significantly outperforms across most benchmarks. LongCat-Flash-Thinking is made by Meituan and Qwen3 VL 30B A3B Thinking is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
LongCat-Flash-Thinking scores MATH-500: 99.2%, ZebraLogic: 95.5%, AIME 2024: 93.3%, AIME 2025: 90.6%, MMLU-Redux: 89.3%. Qwen3 VL 30B A3B Thinking scores DocVQAtest: 95.0%, ScreenSpot: 94.7%, MMLU-Redux: 90.9%, MMBench-V1.1: 88.9%, MMLU: 87.6%.
Qwen3 VL 30B A3B Thinking is 1.5x cheaper for input tokens. LongCat-Flash-Thinking costs $0.30/M input and $1.20/M output via meituan. Qwen3 VL 30B A3B Thinking costs $0.20/M input and $0.99/M output via novita.
LongCat-Flash-Thinking supports 128K tokens and Qwen3 VL 30B A3B Thinking supports 131K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (128K vs 131K), input pricing ($0.30 vs $0.20/M), multimodal support (no vs yes), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
LongCat-Flash-Thinking is developed by Meituan and Qwen3 VL 30B A3B Thinking is developed by Alibaba Cloud / Qwen Team.