Gemini 2.5 Flash-Lite vs Qwen3 VL 4B Thinking
Gemini 2.5 Flash-Lite and Qwen3 VL 4B Thinking are closely matched at 10.4 and 12.9 on the LLM Stats Score. Gemini 2.5 Flash-Lite is 1.9x cheaper per token.
Google · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Gemini 2.5 Flash-Lite and Qwen3 VL 4B Thinking are closely matched on the overall LLM Stats Score at 10.4 and 12.9.
The models split the 2 individual benchmarks reported for both models evenly.
On price, Gemini 2.5 Flash-Lite is roughly 1.9x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Gemini 2.5 Flash-Lite also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Gemini 2.5 Flash-Lite
- cost matters — it's about 1.9x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
Choose Qwen3 VL 4B Thinking
- you want the most recent training data — it shipped Sep 2025
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
13 reported for Gemini 2.5 Flash-Lite · 48 for Qwen3 VL 4B Thinking
Gemini 2.5 Flash-Lite outperforms in 1 benchmarks (GPQA), while Qwen3 VL 4B Thinking is better at 1 benchmark (AIME 2025).
Both models are evenly matched across the benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Gemini 2.5 Flash-Lite ($0.10/1M tokens) costs the same as Qwen3 VL 4B Thinking ($0.10/1M tokens).
For output processing, Gemini 2.5 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 Gemini 2.5 Flash-Lite.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Gemini 2.5 Flash-Lite accepts 1,048,576 input tokens compared to Qwen3 VL 4B Thinking's 262,144 tokens. Qwen3 VL 4B Thinking can generate longer responses up to 262,144 tokens, while Gemini 2.5 Flash-Lite is limited to 65,536 tokens.
Input capabilities
Documented input modalities across available providers
Both Gemini 2.5 Flash-Lite and Qwen3 VL 4B Thinking support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Gemini 2.5 Flash-Lite
Qwen3 VL 4B Thinking
License
Usage and distribution terms
Gemini 2.5 Flash-Lite is licensed under Creative Commons Attribution 4.0 License, 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.
Creative Commons Attribution 4.0 License
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
Gemini 2.5 Flash-Lite was released on 2025-06-17, while Qwen3 VL 4B Thinking was released on 2025-09-22.
Qwen3 VL 4B Thinking is 3 months newer than Gemini 2.5 Flash-Lite.
Jun 17, 2025
1.3 years ago
Sep 22, 2025
12 months ago
3mo newerKnowledge Cutoff
When training data ends
Gemini 2.5 Flash-Lite has a documented knowledge cutoff of 2025-01-01, while Qwen3 VL 4B Thinking's cutoff date is not specified.
We can confirm Gemini 2.5 Flash-Lite's training data extends to 2025-01-01, but cannot make a direct comparison without Qwen3 VL 4B Thinking's cutoff date.
Jan 2025
—
Provider Availability
Gemini 2.5 Flash-Lite is available from Google. Qwen3 VL 4B Thinking is available from DeepInfra.
Gemini 2.5 Flash-Lite
Qwen3 VL 4B Thinking
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemini 2.5 Flash-Lite and Qwen3 VL 4B Thinking side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemini 2.5 Flash-Lite vs Qwen3 VL 4B Thinking.