GPT-4.1 nano vs Qwen3 VL 8B Instruct
Qwen3 VL 8B Instruct leads the LLM Stats Score 14.1 to 1.9. GPT-4.1 nano is 1.1x cheaper per token.
OpenAI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Qwen3 VL 8B Instruct leads the overall LLM Stats Score 14.1 to 1.9, ranking #228 overall.
In the 5 individual benchmarks reported for both models, Qwen3 VL 8B Instruct wins 5; this is a narrower head-to-head signal than the composite indexes.
On price, GPT-4.1 nano is roughly 1.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-4.1 nano also accepts a larger context window (1,047,576 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 GPT-4.1 nano
- cost matters — it's about 1.1x cheaper per token
- you process long inputs — it offers a 1,047,576 token context window
Choose Qwen3 VL 8B Instruct
- overall performance matters — it scores 14.1 and ranks #228 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 5 of 5 exact shared results
- 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
24 reported for GPT-4.1 nano · 46 for Qwen3 VL 8B Instruct
GPT-4.1 nano outperforms in 0 benchmarks, while Qwen3 VL 8B Instruct is better at 5 benchmarks (CharXiv-D, CharXiv-R, IFEval, MMLU, Multi-IF).
Qwen3 VL 8B Instruct significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-4.1 nano ($0.10/1M tokens) is 1.3x more expensive than Qwen3 VL 8B Instruct ($0.08/1M tokens).
For output processing, GPT-4.1 nano ($0.40/1M tokens) is 1.3x cheaper than Qwen3 VL 8B Instruct ($0.50/1M tokens).
In conclusion, Qwen3 VL 8B Instruct is more expensive than GPT-4.1 nano.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-4.1 nano accepts 1,047,576 input tokens compared to Qwen3 VL 8B Instruct's 131,072 tokens. Both models can generate responses up to 32,768 tokens.
Input capabilities
Documented input modalities across available providers
Both GPT-4.1 nano and Qwen3 VL 8B Instruct support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GPT-4.1 nano
Qwen3 VL 8B Instruct
License
Usage and distribution terms
GPT-4.1 nano is licensed under a proprietary license, while Qwen3 VL 8B 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-4.1 nano was released on 2025-04-14, while Qwen3 VL 8B Instruct was released on 2025-09-22.
Qwen3 VL 8B Instruct is 5 months newer than GPT-4.1 nano.
Apr 14, 2025
1.4 years ago
Sep 22, 2025
11 months ago
5mo newerKnowledge Cutoff
When training data ends
GPT-4.1 nano has a documented knowledge cutoff of 2024-05-31, while Qwen3 VL 8B Instruct's cutoff date is not specified.
We can confirm GPT-4.1 nano's training data extends to 2024-05-31, but cannot make a direct comparison without Qwen3 VL 8B Instruct's cutoff date.
May 2024
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Provider Availability
GPT-4.1 nano is available from OpenAI. Qwen3 VL 8B Instruct is available from Novita, DeepInfra.
GPT-4.1 nano
Qwen3 VL 8B Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-4.1 nano and Qwen3 VL 8B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-4.1 nano vs Qwen3 VL 8B Instruct.