Qwen3.7 Flash vs Qwen3.7 Plus
Compare Qwen3.7 Flash and Qwen3.7 Plus side-by-side. See how these vision models stack up in Image Captioning, Open Prompt, Classification, Object Detection, and OCR.
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Models in this comparison
Qwen3.7 Flash vs Qwen3.7 Plus on Vision Evals
Qwen3.7 Plus scores higher on 4 of the five Vision Evals tasks.
The widest gap is Object Detection, where Qwen3.7 Plus leads 60.1% to 42.8%.
Overall, Qwen3.7 Flash averages 52.4% (#53 of 63) against 58.9% (#37 of 63) for Qwen3.7 Plus.
Qwen3.7 Flash is both cheaper ($0.0001 vs $0.0008 per sample) and faster (5.8s vs 7.8s per sample).
Qwen3.7 Flash vs Qwen3.7 Plus Comparison Table
Evals updated October 13, 2026Pricing updated October 23, 2026
| Property | Qwen3.7 Flash | Qwen3.7 Plus |
|---|---|---|
| Organization | Qwen | Qwen |
| Category | closed | closed |
| Modality | multimodal | — |
| Release Date | Jul 2026 | Jun 2026 |
| Context Window | 1.0M | — |
| Parameters | Unknown | Unknown |
| License | Proprietary | Unknown |
| Commercial use | commercial use per vendor terms | See license terms |
| Pricing per 1M tokens | ||
| Input $/1M | $0.030 | $0.320 |
| Output $/1M | $0.130 | $1.28 |
| Vision Tasks | ||
| Captioning | Demo | Demo |
| Classification | Demo | Demo |
| Object Detection | Demo | Demo |
| OCR | Demo | Demo |
| Visual Question Answering | Demo | Demo |
| Chart Question Answering | Supported | Not listed |
| Document Question Answering | Supported | Not listed |
| Image Tagging | Supported | Not listed |
| Multi-Label Classification | Supported | Not listed |
| Vision Language | Supported | Not listed |
| Model Features | ||
| Foundation Vision | Supported | Not listed |
| LLMs with Vision Capabilities | Supported | Not listed |
| Multimodal Vision | Supported | Not listed |
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort | ||
| Overall | 52.4% | 58.9% |
| Avg cost / sample | $0.0001 | $0.0008 |
| Avg speed / sample | 5.77s | 7.77s |
| By task | ||
| Object Detection | 42.8% | 60.1% |
| Counting | 46.0% | 50.0% |
| Identification | 84.4% | 84.4% |
| OCR (low) | 54.3% | 60.3% |
| by category |
|
|
| OCR (high) | 62.3% | 65.5% |
| by category |
|
|
| Reasoning (low) | 34.4% | 39.7% |
| Reasoning (high) | 61.6% | 68.2% |
Qwen3.7 Flash vs Qwen3.7 Plus: Overview
Qwen3.7 Flash is the low-latency, cost-oriented tier of Alibaba's Qwen3.7 series, a vision-language reasoning model that accepts interleaved text and image input and returns text. It is built as a hybrid thinking model: like the rest of the Qwen3.7, Qwen3.6, and Qwen3.5 families served through Alibaba Cloud Model Studio, it can either emit an explicit reasoning trace before answering or respond directly, with thinking behavior controlled by an enable_thinking switch that defaults to on for the Qwen3.7 generation. The model exposes a context window of roughly one million tokens and a maximum generation length of 65,536 tokens, which allows long multi-image sequences, long documents, and extended agent trajectories to be held in a single request.
Functionally, Qwen3.7 Flash targets multimodal agent workloads rather than pure chat. Reported strengths include object recognition, spatial understanding, and perception of real-world scenes, alongside visual coding, search, and computer-use style interaction where the model reads screen content and reasons over interface state. Weights are not published; the model is a proprietary endpoint positioned below Qwen3.7 Plus and Qwen3.7 Max in the same series, and it supports function calling and tool use for agentic pipelines.