Model Comparison

LongCat-Flash-Chat vs Qwen3 VL 4B Thinking

LongCat-Flash-Chat significantly outperforms across most benchmarks. Qwen3 VL 4B Thinking is 1.6x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

5 benchmarks

LongCat-Flash-Chat outperforms in 4 benchmarks (GPQA, IFEval, MMLU, MMLU-Pro), while Qwen3 VL 4B Thinking is better at 1 benchmark (AIME 2025).

LongCat-Flash-Chat significantly outperforms across most benchmarks.

Thu Apr 16 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Qwen3 VL 4B Thinking costs less

For input processing, LongCat-Flash-Chat ($0.30/1M tokens) is 3.0x more expensive than Qwen3 VL 4B Thinking ($0.10/1M tokens).

For output processing, LongCat-Flash-Chat ($1.20/1M tokens) is 1.2x more expensive than Qwen3 VL 4B Thinking ($1.00/1M tokens).

In conclusion, LongCat-Flash-Chat is more expensive than Qwen3 VL 4B Thinking.*

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

Lowest available price from all providers
Thu Apr 16 2026 • llm-stats.com
Meituan
LongCat-Flash-Chat
Input tokens$0.30
Output tokens$1.20
Best providerMeituan
Alibaba Cloud / Qwen Team
Qwen3 VL 4B Thinking
Input tokens$0.10
Output tokens$1.00
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

556.0B diff

LongCat-Flash-Chat has 556.0B more parameters than Qwen3 VL 4B Thinking, making it 13900.0% larger.

Meituan
LongCat-Flash-Chat
560.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 4B Thinking
4.0Bparameters
560.0B
LongCat-Flash-Chat
4.0B
Qwen3 VL 4B Thinking

Context Window

Maximum input and output token capacity

Qwen3 VL 4B Thinking accepts 262,144 input tokens compared to LongCat-Flash-Chat's 128,000 tokens. Qwen3 VL 4B Thinking can generate longer responses up to 262,144 tokens, while LongCat-Flash-Chat is limited to 128,000 tokens.

Meituan
LongCat-Flash-Chat
Input128,000 tokens
Output128,000 tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 4B Thinking
Input262,144 tokens
Output262,144 tokens
Thu Apr 16 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3 VL 4B Thinking supports multimodal inputs, whereas LongCat-Flash-Chat does not.

Qwen3 VL 4B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.

LongCat-Flash-Chat

Text
Images
Audio
Video

Qwen3 VL 4B Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

LongCat-Flash-Chat is licensed under MIT, while Qwen3 VL 4B Thinking 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

Qwen3 VL 4B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

LongCat-Flash-Chat was released on 2025-08-29, while Qwen3 VL 4B Thinking was released on 2025-09-22.

Qwen3 VL 4B Thinking is 1 month newer than LongCat-Flash-Chat.

LongCat-Flash-Chat

Aug 29, 2025

7 months ago

Qwen3 VL 4B Thinking

Sep 22, 2025

6 months ago

3w newer

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-Chat is available from Meituan. Qwen3 VL 4B Thinking is available from DeepInfra.

LongCat-Flash-Chat

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

Qwen3 VL 4B Thinking

deepinfra logo
Deepinfra
Input Price:Input: $0.10/1MOutput Price:Output: $1.00/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Meituan
Higher GPQA score (73.2% vs 64.1%)
Higher IFEval score (89.6% vs 82.6%)
Higher MMLU score (89.7% vs 81.5%)
Higher MMLU-Pro score (82.7% vs 73.6%)
Alibaba Cloud / Qwen Team

Qwen3 VL 4B Thinking

View details

Alibaba Cloud / Qwen Team

Larger context window (262,144 tokens)
Supports multimodal inputs
Less expensive input tokens
Less expensive output tokens
Higher AIME 2025 score (74.5% vs 61.3%)

Detailed Comparison

AI Model Comparison Table
Feature
Meituan
LongCat-Flash-Chat
Alibaba Cloud / Qwen Team
Qwen3 VL 4B Thinking

FAQ

Common questions about LongCat-Flash-Chat vs Qwen3 VL 4B Thinking

LongCat-Flash-Chat significantly outperforms across most benchmarks. LongCat-Flash-Chat is made by Meituan and Qwen3 VL 4B 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-Chat scores MATH-500: 96.4%, MMLU: 89.7%, IFEval: 89.6%, ZebraLogic: 89.3%, HumanEval: 88.4%. Qwen3 VL 4B Thinking scores DocVQAtest: 94.2%, ScreenSpot: 92.9%, MMBench-V1.1: 86.7%, MMLU-Redux: 86.0%, AI2D: 84.9%.
Qwen3 VL 4B Thinking is 3.0x cheaper for input tokens. LongCat-Flash-Chat costs $0.30/M input and $1.20/M output via meituan. Qwen3 VL 4B Thinking costs $0.10/M input and $1.00/M output via deepinfra.
LongCat-Flash-Chat supports 128K tokens and Qwen3 VL 4B Thinking supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (128K vs 262K), input pricing ($0.30 vs $0.10/M), multimodal support (no vs yes), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
LongCat-Flash-Chat is developed by Meituan and Qwen3 VL 4B Thinking is developed by Alibaba Cloud / Qwen Team.