GPT-4 vs Qwen3 VL 8B Thinking
Qwen3 VL 8B Thinking leads the LLM Stats Score 16.2 to 3.0. Qwen3 VL 8B Thinking is 57.0x cheaper per token.
OpenAI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Qwen3 VL 8B Thinking leads the overall LLM Stats Score 16.2 to 3.0, ranking #230 overall.
The models split the 2 individual benchmarks reported for both models evenly.
On price, Qwen3 VL 8B Thinking is roughly 57.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen3 VL 8B Thinking also accepts a larger context window (262,144 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 GPT-4
- you want predictable pricing at $30.00/M input and $60.00/M output
Choose Qwen3 VL 8B Thinking
- overall performance matters — it scores 16.2 and ranks #230 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- cost matters — it's about 57.0x cheaper per token
- you process long inputs — it offers a 262,144 token context window
- 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.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
12 reported for GPT-4 · 50 for Qwen3 VL 8B Thinking
GPT-4 outperforms in 1 benchmarks (MMLU), while Qwen3 VL 8B Thinking is better at 1 benchmark (GPQA).
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, GPT-4 ($30.00/1M tokens) is 166.7x more expensive than Qwen3 VL 8B Thinking ($0.18/1M tokens).
For output processing, GPT-4 ($60.00/1M tokens) is 28.7x more expensive than Qwen3 VL 8B Thinking ($2.09/1M tokens).
In conclusion, GPT-4 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
Qwen3 VL 8B Thinking accepts 262,144 input tokens compared to GPT-4's 32,768 tokens. Qwen3 VL 8B Thinking can generate longer responses up to 262,144 tokens, while GPT-4 is limited to 32,768 tokens.
Input capabilities
Documented input modalities across available providers
Both GPT-4 and Qwen3 VL 8B Thinking support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GPT-4
Qwen3 VL 8B Thinking
License
Usage and distribution terms
GPT-4 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
GPT-4 was released on 2023-06-13, while Qwen3 VL 8B Thinking was released on 2025-09-22.
Qwen3 VL 8B Thinking is 28 months newer than GPT-4.
Jun 13, 2023
3.3 years ago
Sep 22, 2025
1.0 years ago
2.3yr newerKnowledge Cutoff
When training data ends
GPT-4 has a documented knowledge cutoff of 2022-12-31, while Qwen3 VL 8B Thinking's cutoff date is not specified.
We can confirm GPT-4's training data extends to 2022-12-31, but cannot make a direct comparison without Qwen3 VL 8B Thinking's cutoff date.
Dec 2022
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Provider Availability
GPT-4 is available from Azure, OpenAI. Qwen3 VL 8B Thinking is available from DeepInfra.
GPT-4
Qwen3 VL 8B Thinking
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-4 and Qwen3 VL 8B Thinking side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-4 vs Qwen3 VL 8B Thinking.