GPT-5.4 nano vs Qwen3 VL 32B Instruct
GPT-5.4 nano leads the LLM Stats Score 26.6 to 20.3.
OpenAI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
GPT-5.4 nano leads the overall LLM Stats Score 26.6 to 20.3, ranking #150 overall.
In the 2 individual benchmarks reported for both models, GPT-5.4 nano wins 2; this is a narrower head-to-head signal than the composite indexes.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose GPT-5.4 nano
- overall performance matters — it scores 26.6 and ranks #150 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 2 of 2 exact shared results
- you want the most recent training data — it shipped Mar 2026
Choose Qwen3 VL 32B Instruct
- 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
15 reported for GPT-5.4 nano · 45 for Qwen3 VL 32B Instruct
GPT-5.4 nano outperforms in 2 benchmarks (GPQA, MMMU-Pro), while Qwen3 VL 32B Instruct is better at 0 benchmarks.
GPT-5.4 nano significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Context Window
Maximum input and output token capacity
Only GPT-5.4 nano specifies input context (400,000 tokens). Only GPT-5.4 nano specifies output context (128,000 tokens).
Input capabilities
Documented input modalities across available providers
Both GPT-5.4 nano and Qwen3 VL 32B Instruct support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GPT-5.4 nano
Qwen3 VL 32B Instruct
License
Usage and distribution terms
GPT-5.4 nano is licensed under a proprietary license, while Qwen3 VL 32B Instruct 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-5.4 nano was released on 2026-03-17, while Qwen3 VL 32B Instruct was released on 2025-09-22.
GPT-5.4 nano is 6 months newer than Qwen3 VL 32B Instruct.
Mar 17, 2026
6 months ago
5mo newerSep 22, 2025
12 months ago
Knowledge Cutoff
When training data ends
GPT-5.4 nano has a documented knowledge cutoff of 2025-08-31, while Qwen3 VL 32B Instruct's cutoff date is not specified.
We can confirm GPT-5.4 nano's training data extends to 2025-08-31, but cannot make a direct comparison without Qwen3 VL 32B Instruct's cutoff date.
Aug 2025
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Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-5.4 nano and Qwen3 VL 32B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-5.4 nano vs Qwen3 VL 32B Instruct.