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GPT-4.1 nano vs Qwen3 VL 30B A3B Instruct

Qwen3 VL 30B A3B Instruct leads the LLM Stats Score 16.4 to 1.6. GPT-4.1 nano is 1.5x cheaper per token.

OpenAI · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Qwen3 VL 30B A3B Instruct leads the overall LLM Stats Score 16.4 to 1.6, ranking #222 overall.

In the 6 individual benchmarks reported for both models, Qwen3 VL 30B A3B Instruct wins 6; this is a narrower head-to-head signal than the composite indexes.

On price, GPT-4.1 nano is roughly 1.5x 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 1.5x cheaper per token
  • you process long inputs — it offers a 1,047,576 token context window

Choose Qwen3 VL 30B A3B Instruct

  • overall performance matters — it scores 16.4 and ranks #222 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 6 of 6 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.

Core performance indexes
1.6
#319
16.4
#222
2.0
#307
15.0
#225
Cost, coverage & limits
Benchmark wins
0 of 6
6 of 6
Input price
$0.10 / M
$0.15 / M
Output price
$0.40 / M
$0.60 / M
Context window
1,047,576
262,144

Capability indexes

Additional strengths measured across groups of related public benchmarks

4 shared
Index
GPT-4.1 nano
Qwen3 VL 30B A3B Instruct
5.0#274
16.5#203
-1.9#188
11.3#109
-7.5#113
8.8#81
0.9#149
13.8#95
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

24 reported for GPT-4.1 nano · 50 for Qwen3 VL 30B A3B Instruct

6 shared

GPT-4.1 nano outperforms in 0 benchmarks, while Qwen3 VL 30B A3B Instruct is better at 6 benchmarks (CharXiv-D, CharXiv-R, GPQA, IFEval, MMLU, Multi-IF).

Qwen3 VL 30B A3B Instruct significantly outperforms across most benchmarks.

Sun Sep 13 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

GPT-4.1 nano costs less

For input processing, GPT-4.1 nano ($0.10/1M tokens) is 1.5x cheaper than Qwen3 VL 30B A3B Instruct ($0.15/1M tokens).

For output processing, GPT-4.1 nano ($0.40/1M tokens) is 1.5x cheaper than Qwen3 VL 30B A3B Instruct ($0.60/1M tokens).

In conclusion, Qwen3 VL 30B A3B Instruct is more expensive than GPT-4.1 nano.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Sun Sep 13 2026 • llm-stats.com
OpenAI
GPT-4.1 nano
Input tokens$0.10
Output tokens$0.40
Best providerOpenAI
Alibaba Cloud / Qwen Team
Qwen3 VL 30B A3B Instruct
Input tokens$0.15
Output tokens$0.60
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue

Context Window

Maximum input and output token capacity

GPT-4.1 nano accepts 1,047,576 input tokens compared to Qwen3 VL 30B A3B Instruct's 262,144 tokens. Qwen3 VL 30B A3B Instruct can generate longer responses up to 262,144 tokens, while GPT-4.1 nano is limited to 32,768 tokens.

OpenAI
GPT-4.1 nano
Input1,047,576 tokens
Output32,768 tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 30B A3B Instruct
Input262,144 tokens
Output262,144 tokens
Sun Sep 13 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both GPT-4.1 nano and Qwen3 VL 30B A3B Instruct support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

GPT-4.1 nano

Text
Images
Audio
Video

Qwen3 VL 30B A3B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

GPT-4.1 nano is licensed under a proprietary license, while Qwen3 VL 30B A3B Instruct uses Apache 2.0.

License differences may affect how you can use these models in commercial or open-source projects.

GPT-4.1 nano

Proprietary

Closed source

Qwen3 VL 30B A3B Instruct

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 30B A3B Instruct was released on 2025-09-22.

Qwen3 VL 30B A3B Instruct is 5 months newer than GPT-4.1 nano.

GPT-4.1 nano

Apr 14, 2025

1.4 years ago

Qwen3 VL 30B A3B Instruct

Sep 22, 2025

11 months ago

5mo newer

Knowledge Cutoff

When training data ends

GPT-4.1 nano has a documented knowledge cutoff of 2024-05-31, while Qwen3 VL 30B A3B 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 30B A3B Instruct's cutoff date.

GPT-4.1 nano

May 2024

Qwen3 VL 30B A3B Instruct

Provider Availability

GPT-4.1 nano is available from OpenAI. Qwen3 VL 30B A3B Instruct is available from DeepInfra, Novita.

GPT-4.1 nano

openai logo
OpenAI
Input Price:Input: $0.10/1MOutput Price:Output: $0.40/1M

Qwen3 VL 30B A3B Instruct

deepinfra logo
Deepinfra
Input Price:Input: $0.15/1MOutput Price:Output: $0.60/1M
novita logo
Novita
Input Price:Input: $0.20/1MOutput Price:Output: $0.70/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against GPT-4.1 nano and Qwen3 VL 30B A3B Instruct side-by-side, then vote on the output you prefer.

GPT-4.1 nano
✓ Preferred
Qwen3 VL 30B A3B Instruct
Open in Playground

FAQ

Common questions about GPT-4.1 nano vs Qwen3 VL 30B A3B Instruct.

Which is better, GPT-4.1 nano or Qwen3 VL 30B A3B Instruct?

Qwen3 VL 30B A3B Instruct leads the LLM Stats Score 16.4 to 1.6. GPT-4.1 nano is made by OpenAI and Qwen3 VL 30B A3B Instruct is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does GPT-4.1 nano compare to Qwen3 VL 30B A3B Instruct in benchmarks?

GPT-4.1 nano scores MMLU: 80.1%, IFEval: 74.5%, CharXiv-D: 73.9%, MMMLU: 66.9%, Multi-IF: 57.2%. Qwen3 VL 30B A3B Instruct scores DocVQAtest: 95.0%, ScreenSpot: 94.7%, OCRBench: 90.3%, MMLU-Redux: 88.4%, MMBench-V1.1: 87.0%.

Is GPT-4.1 nano cheaper than Qwen3 VL 30B A3B Instruct?

GPT-4.1 nano is 1.5x cheaper for input tokens. GPT-4.1 nano costs $0.10/M input and $0.40/M output via openai. Qwen3 VL 30B A3B Instruct costs $0.15/M input and $0.60/M output via deepinfra.

What are the context window sizes for GPT-4.1 nano and Qwen3 VL 30B A3B Instruct?

GPT-4.1 nano supports 1.0M tokens and Qwen3 VL 30B A3B Instruct supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between GPT-4.1 nano and Qwen3 VL 30B A3B Instruct?

Key differences include LLM Stats Score (1.6 vs 16.4), context window (1.0M vs 262K), input pricing ($0.10 vs $0.15/M), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes GPT-4.1 nano and Qwen3 VL 30B A3B Instruct?

GPT-4.1 nano is developed by OpenAI and Qwen3 VL 30B A3B Instruct is developed by Alibaba Cloud / Qwen Team.