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GPT-6 Luna vs Qwen3 VL 32B Thinking

GPT-6 Luna leads the LLM Stats Score 44.5 to 23.5.

OpenAI · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

GPT-6 Luna leads the overall LLM Stats Score 44.5 to 23.5, ranking #41 overall.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose GPT-6 Luna

  • overall performance matters — it scores 44.5 and ranks #41 on LLM Stats
  • your work emphasizes reasoning and agents — it leads those capability indexes
  • you want the most recent training data — it shipped Sep 2026

Choose Qwen3 VL 32B Thinking

  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

GPT-6 Luna
OpenAI
Qwen3 VL 32B Thinking
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
44.5
#41
23.5
#180
Reasoning
40.0
#58
24.7
#160
Agents
31.8
#30
12.9
#103
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.10 / M
— / M
Output price
$0.50 / M
— / M
Context window
1,050,000
—

Individual benchmarks

5 reported for GPT-6 Luna · 47 for Qwen3 VL 32B Thinking

No common benchmarks found

GPT-6 Luna and Qwen3 VL 32B Thinkingdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Context Window

Maximum input and output token capacity

Only GPT-6 Luna specifies input context (1,050,000 tokens). Only GPT-6 Luna specifies output context (128,000 tokens).

OpenAI
GPT-6 Luna
Input1,050,000 tokens
Output128,000 tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 32B Thinking
Input- tokens
Output- tokens
Wed Sep 23 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both GPT-6 Luna and Qwen3 VL 32B Thinking support multimodal inputs.

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

GPT-6 Luna

Text
Images
Audio
Video

Qwen3 VL 32B Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

GPT-6 Luna is licensed under a proprietary license, while Qwen3 VL 32B Thinking uses Apache 2.0.

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

GPT-6 Luna

Proprietary

Closed source

Qwen3 VL 32B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

GPT-6 Luna was released on 2026-09-22, while Qwen3 VL 32B Thinking was released on 2025-09-22.

GPT-6 Luna is 12 months newer than Qwen3 VL 32B Thinking.

GPT-6 Luna

Sep 22, 2026

0 days ago

1.0yr newer
Qwen3 VL 32B Thinking

Sep 22, 2025

1.0 years ago

Knowledge Cutoff

When training data ends

GPT-6 Luna has a documented knowledge cutoff of 2026-05-18, while Qwen3 VL 32B Thinking's cutoff date is not specified.

We can confirm GPT-6 Luna's training data extends to 2026-05-18, but cannot make a direct comparison without Qwen3 VL 32B Thinking's cutoff date.

GPT-6 Luna

May 2026

Qwen3 VL 32B Thinking

—

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against GPT-6 Luna and Qwen3 VL 32B Thinking side-by-side, then vote on the output you prefer.

GPT-6 Luna
✓ Preferred
Qwen3 VL 32B Thinking
Open in Playground

FAQ

Common questions about GPT-6 Luna vs Qwen3 VL 32B Thinking.

Which is better, GPT-6 Luna or Qwen3 VL 32B Thinking?

GPT-6 Luna leads the LLM Stats Score 44.5 to 23.5. GPT-6 Luna is made by OpenAI and Qwen3 VL 32B Thinking 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-6 Luna compare to Qwen3 VL 32B Thinking in benchmarks?

GPT-6 Luna scores DeepSWE 1.1: 66.6%, OSWorld 2.0: 52.7%, Agents' Last Exam: 50.9%, FrontierCode 1.1: 42.4%, AutomationBench v1.0.6: 20.7%. Qwen3 VL 32B Thinking scores DocVQAtest: 96.1%, ScreenSpot: 95.7%, MMLU-Redux: 91.9%, MMBench-V1.1: 90.8%, CharXiv-D: 90.2%.

What are the context window sizes for GPT-6 Luna and Qwen3 VL 32B Thinking?

GPT-6 Luna supports 1.1M tokens and Qwen3 VL 32B Thinking supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between GPT-6 Luna and Qwen3 VL 32B Thinking?

Key differences include LLM Stats Score (44.5 vs 23.5), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes GPT-6 Luna and Qwen3 VL 32B Thinking?

GPT-6 Luna is developed by OpenAI and Qwen3 VL 32B Thinking is developed by Alibaba Cloud / Qwen Team.

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