Gemini 1.5 Pro vs Qwen3 VL 8B Thinking
Both models are evenly matched across the benchmarks. Qwen3 VL 8B Thinking is 6.7x cheaper per token.
Google · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Gemini 1.5 Pro outperforms in 2 benchmarks (MMLU, Video-MME), while Qwen3 VL 8B Thinking is better at 2 benchmarks (GPQA, MMLU-Pro). Both models are evenly matched across the benchmarks.
On price, Qwen3 VL 8B Thinking is roughly 6.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Gemini 1.5 Pro also accepts a larger context window (2,097,152 input tokens), making it the stronger choice for long documents and large codebases.
Based on current benchmark, pricing, and model metadata for 2026.
Choose Gemini 1.5 Pro
- you process long inputs — it offers a 2,097,152 token context window
Choose Qwen3 VL 8B Thinking
- cost matters — it's about 6.7x cheaper per token
- you want the most recent training data — it shipped Sep 2025
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
Gemini 1.5 Pro outperforms in 2 benchmarks (MMLU, Video-MME), while Qwen3 VL 8B Thinking is better at 2 benchmarks (GPQA, MMLU-Pro).
Both models are evenly matched across the benchmarks.
Arena Performance
Playground indexes and blind preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Gemini 1.5 Pro ($2.50/1M tokens) is 13.9x more expensive than Qwen3 VL 8B Thinking ($0.18/1M tokens).
For output processing, Gemini 1.5 Pro ($10.00/1M tokens) is 4.8x more expensive than Qwen3 VL 8B Thinking ($2.09/1M tokens).
In conclusion, Gemini 1.5 Pro is more expensive than Qwen3 VL 8B Thinking.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Gemini 1.5 Pro accepts 2,097,152 input tokens compared to Qwen3 VL 8B Thinking's 262,144 tokens. Qwen3 VL 8B Thinking can generate longer responses up to 262,144 tokens, while Gemini 1.5 Pro is limited to 8,192 tokens.
Input Capabilities
Supported data types and modalities
Both Gemini 1.5 Pro and Qwen3 VL 8B Thinking support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Gemini 1.5 Pro
Qwen3 VL 8B Thinking
License
Usage and distribution terms
Gemini 1.5 Pro is licensed under a proprietary license, while Qwen3 VL 8B Thinking uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Apache 2.0
Open weights
Release Timeline
When each model was launched
Gemini 1.5 Pro was released on 2024-05-01, while Qwen3 VL 8B Thinking was released on 2025-09-22.
Qwen3 VL 8B Thinking is 17 months newer than Gemini 1.5 Pro.
May 1, 2024
2.3 years ago
Sep 22, 2025
11 months ago
1.4yr newerKnowledge Cutoff
When training data ends
Gemini 1.5 Pro has a documented knowledge cutoff of 2023-11-01, while Qwen3 VL 8B Thinking's cutoff date is not specified.
We can confirm Gemini 1.5 Pro's training data extends to 2023-11-01, but cannot make a direct comparison without Qwen3 VL 8B Thinking's cutoff date.
Nov 2023
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Provider Availability
Gemini 1.5 Pro is available from Google. Qwen3 VL 8B Thinking is available from DeepInfra.
Gemini 1.5 Pro
Qwen3 VL 8B Thinking
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemini 1.5 Pro and Qwen3 VL 8B Thinking side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemini 1.5 Pro vs Qwen3 VL 8B Thinking.