Model Comparison

LongCat-Flash-Lite vs Qwen3 VL 4B Thinking

LongCat-Flash-Lite shows notably better performance in the majority of benchmarks. LongCat-Flash-Lite is 1.9x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

LongCat-Flash-Lite outperforms in 3 benchmarks (GPQA, MMLU, MMLU-Pro), while Qwen3 VL 4B Thinking is better at 1 benchmark (AIME 2025).

LongCat-Flash-Lite shows notably better performance in the majority of benchmarks.

Wed Apr 15 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

LongCat-Flash-Lite costs less

For input processing, LongCat-Flash-Lite ($0.10/1M tokens) costs the same as Qwen3 VL 4B Thinking ($0.10/1M tokens).

For output processing, LongCat-Flash-Lite ($0.40/1M tokens) is 2.5x cheaper than Qwen3 VL 4B Thinking ($1.00/1M tokens).

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

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

Lowest available price from all providers
Wed Apr 15 2026 • llm-stats.com
Meituan
LongCat-Flash-Lite
Input tokens$0.10
Output tokens$0.40
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

64.5B diff

LongCat-Flash-Lite has 64.5B more parameters than Qwen3 VL 4B Thinking, making it 1612.5% larger.

Meituan
LongCat-Flash-Lite
68.5Bparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 4B Thinking
4.0Bparameters
68.5B
LongCat-Flash-Lite
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-Lite's 256,000 tokens. Qwen3 VL 4B Thinking can generate longer responses up to 262,144 tokens, while LongCat-Flash-Lite is limited to 128,000 tokens.

Meituan
LongCat-Flash-Lite
Input256,000 tokens
Output128,000 tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 4B Thinking
Input262,144 tokens
Output262,144 tokens
Wed Apr 15 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3 VL 4B Thinking supports multimodal inputs, whereas LongCat-Flash-Lite 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-Lite

Text
Images
Audio
Video

Qwen3 VL 4B Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

LongCat-Flash-Lite 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-Lite

MIT

Open weights

Qwen3 VL 4B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

LongCat-Flash-Lite was released on 2026-02-05, while Qwen3 VL 4B Thinking was released on 2025-09-22.

LongCat-Flash-Lite is 5 months newer than Qwen3 VL 4B Thinking.

LongCat-Flash-Lite

Feb 5, 2026

2 months ago

4mo newer
Qwen3 VL 4B 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-Lite is available from Meituan. Qwen3 VL 4B Thinking is available from DeepInfra.

LongCat-Flash-Lite

meituan logo
Meituan
Input Price:Input: $0.10/1MOutput Price:Output: $0.40/1M

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
Less expensive output tokens
Higher GPQA score (66.8% vs 64.1%)
Higher MMLU score (85.5% vs 81.5%)
Higher MMLU-Pro score (78.3% 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
Higher AIME 2025 score (74.5% vs 63.2%)

Detailed Comparison

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

FAQ

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

LongCat-Flash-Lite shows notably better performance in the majority of benchmarks. LongCat-Flash-Lite 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-Lite scores MATH-500: 96.8%, MMLU: 85.5%, CMMLU: 82.5%, MMLU-Pro: 78.3%, Tau2 Retail: 73.1%. Qwen3 VL 4B Thinking scores DocVQAtest: 94.2%, ScreenSpot: 92.9%, MMBench-V1.1: 86.7%, MMLU-Redux: 86.0%, AI2D: 84.9%.
Both models cost $0.10 per million input tokens.
LongCat-Flash-Lite supports 256K 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 (256K vs 262K), multimodal support (no vs yes), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
LongCat-Flash-Lite is developed by Meituan and Qwen3 VL 4B Thinking is developed by Alibaba Cloud / Qwen Team.