GPT-6 Luna vs Qwen3.6 Plus
Compare GPT-6 Luna and Qwen3.6 Plus side-by-side.
Compare GPT-6 Luna vs Qwen3.6 Plus live
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These models don't share enough common tasks for a side-by-side demo. See the comparison table below for their capabilities.
Models in this comparison
GPT-6 Luna vs Qwen3.6 Plus Comparison Table
Evals updated September 22, 2026Pricing updated September 22, 2026
| Property | GPT-6 Luna | Qwen3.6 Plus |
|---|---|---|
| Organization | OpenAI | Qwen |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Sep 2026 | Apr 2026 |
| Context Window | 1.1M | 1.0M |
| Parameters | ||
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $0.325 | |
| Output $/1M | $1.95 | |
| Vision Tasks | ||
| Captioning | Demo | |
| Chart Question Answering | ||
| Classification | ||
| Document Question Answering | ||
| Image Tagging | ||
| Multi-Label Classification | ||
| Object Detection | ||
| OCR | Demo | |
| Vision Language | ||
| Visual Question Answering | Demo | |
| Model Features | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort | ||
| Overall | 68.6% | Not evaluated |
| Avg cost / sample | $0.0004 | – |
| Avg speed / sample | 11.27s | – |
| By task | ||
| Object Detection (low) | 56.8% ±1.9, Mean of 3 runs, range 54.8 to 58.5 | – |
| Object Detection (high) | 64.1% ±0.5, Mean of 3 runs, range 63.6 to 64.5 | – |
| Counting (low) | 65.8% ±1.4, Mean of 3 runs, range 64.9 to 67.6 | – |
| Counting (high) | 64.4% ±2.0, Mean of 3 runs, range 62.2 to 66.2 | – |
| Identification (low) | 81.3% ±0.0, Mean of 3 runs, range 81.3 to 81.3 | – |
| Identification (high) | 80.2% ±1.6, Mean of 3 runs, range 78.1 to 81.3 | – |
| OCR (low) | 87.9% ±0.6, Mean of 3 runs, range 87.2 to 88.3 | – |
| OCR (high) | 88.5% ±0.6, Mean of 3 runs, range 87.9 to 89.2 | – |
| Data Extraction (low) | 68.0% ±3.1, Mean of 3 runs, range 65.0 to 71.1 | – |
| Data Extraction (high) | 66.7% ±0.5, Mean of 3 runs, range 66.0 to 67.0 | – |
| Reasoning (low) | 52.1% ±2.0, Mean of 3 runs, range 49.7 to 53.6 | – |
| Reasoning (high) | 60.7% ±1.7, Mean of 3 runs, range 58.9 to 62.3 | – |
GPT-6 Luna vs Qwen3.6 Plus: Overview
GPT-6 Luna is the fast, cost-efficient tier of OpenAI's GPT-6 model family, sitting below GPT-6 Sol and the larger GPT-6 Astra model that opened the generation. It is a proprietary multimodal transformer that accepts text and image input and returns text, and it exposes an adjustable reasoning effort setting so the same model can run in a low-latency mode or spend additional inference compute on harder problems. OpenAI positions it for high-volume and latency-sensitive workloads such as conversational assistants, classification, and lightweight agentic pipelines, while noting that at higher reasoning effort it handles software engineering and computer-use tasks that previously required a Sol-tier model.
The model supports a context window of roughly 1,050,000 input tokens with a maximum output of 128,000 tokens, which allows long documents, extended agent traces, and large code repositories to be processed in a single request. OpenAI describes the GPT-6 generation as improving factual reliability and adopting a more concise communication style relative to the GPT-5.6 series, and attributes the efficiency of the Sol and Luna tiers to gains in caching and inference rather than to reduced capability. Architecture details, parameter counts, and training data are not published.
Qwen3.6 Plus is a flagship model in Alibaba’s Qwen Plus series, designed for agentic workflows, coding, and multi-step reasoning. It supports a 1 million token context window and up to 65,536 output tokens, with built-in reasoning capabilities. The model is available as a hosted, proprietary API through Alibaba Cloud.
Compared to Qwen3.5, it improves reliability in multi-step execution and frontend code generation, with stronger performance on agentic coding tasks. It also supports document and image understanding, though its vision capabilities are more limited than dedicated Qwen-VL models. Qwen3.6 Plus is part of a broader Qwen ecosystem that includes both closed-source APIs and open-weight models.