qwen
Qwen: Qwen3.6 Plus
qwen/qwen3.6-plus
Our take
AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.
qwen/qwen3.6-plus is a multimodal text-generation model listed in the OpenRouter catalog, accepting text, image, and video inputs and producing text output. The catalog describes a hybrid architecture combining linear attention with sparse mixture-of-experts routing, and advertises a context window of one million tokens. Tool calling, structured outputs, and optional reasoning are listed among supported parameters. All claims here come from OpenRouter's catalog; an independent model card was not available in this source pack, so architecture details are provider-reported rather than verified.[1]
Strengths
Limitations
- Evidence is catalog-only; no independent model card was available, so architecture and capability claims are provider-reported and unverified.[1]
- Knowledge cutoff, licensing terms, and agentic/intelligence index scores are not reported, leaving real-world quality uncertain pending workload validation.[1]
- Reported design-arena results sit mid-pack with roughly even win rates, so measured performance does not clearly stand out.[1]
Where to use it
- Potentially suitable for multimodal pipelines that mix long documents with images or video; validate against your workload first.[1]
- May fit tool-calling or structured-output integrations, based on the catalog's supported parameters.[1]
- Candidates for long-context summarization or analysis, subject to independent quality testing.[1]
Sources
- [1] OpenRouter catalog · Qwen: Qwen3.6 PlusSources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
Qwen 3.6 Plus builds on a hybrid architecture that combines efficient linear attention with sparse mixture-of-experts routing, enabling strong scalability and high-performance inference. Compared to the 3.5 series, it delivers...
Specifications
- Model ID
- qwen/qwen3.6-plus
- Canonical ID
- qwen/qwen3.6-plus-04-02
- Creator
- qwen
- Added to OpenRouter
- 02.04.2026
- Context length
- 1,000,000
- Modality
- text+image+video->text
- Input modalities
- text, image, video
- Output modalities
- text
- Token pricing
- USD per 1M tokens: in $0.325 / out $1.95
- Knowledge cutoff
- —
- Expiration date
- —
Tasks and capabilities
A grade appears only where the source supplies a matching measurement for that task, the model is active and the cohort holds at least 10 comparable models. The capability column lists facts the source declares — supported formats, reasoning and tool parameters — which are not measured quality.
| Task | Grade | Source-declared capability |
|---|---|---|
| General quality | No measurement | reasoning: optional · parameters: include_reasoning, reasoning |
| Coding | BB — next 30% of the cohort | — |
| Agents | No measurement | parameters: structured_outputs, tool_choice, tools |
| Writing | No measurement | output: text |
| Reasoning | No measurement | reasoning: optional · parameters: include_reasoning, reasoning |
| Document analysis | No measurement | — |
| Vision | No measurement | input: image |
| Image generation | No measurement | — |
| Audio | No measurement | — |
| Video | No measurement | input: video |
| Embeddings | No measurement | — |
Evaluations
| Source | Benchmark | Value | Grade | Data retrieved |
|---|---|---|---|---|
| Artificial Analysis | Coding index | 54.5 | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | models · 3dwin rate 50.5% · rank 56 | 1,186Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | models · asciiartwin rate 40.8% · rank 60 | 1,110Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · codecategorieswin rate 50.1% · rank 53 | 1,227Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | models · datavizwin rate 50.5% · rank 48 | 1,224Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | models · gamedevwin rate 48.3% · rank 54 | 1,203Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | models · svgwin rate 50.1% · rank 47 | 1,153Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | models · uicomponentwin rate 50.3% · rank 54 | 1,223Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | models · websitewin rate 50.1% · rank 54 | 1,235Elo | BB — next 30% of the cohort | 13.11.2026 |
How grades work
Each letter grade compares a model only against other models scored by the same source and metric in the current snapshot. S means the top 10%, A the next 20%, B the next 30%, C the rest. Models without a published measurement are shown as not rated — a supported format alone never implies measured quality.
- S — S — top 10% of the cohort
- A — A — next 20% of the cohort
- B — B — next 30% of the cohort
- C — C — below the B band
Providers
Optional live provider statistics from OpenRouter. Missing values are unknown, not zero.
| Provider | Context length | Price in /1M | Price out /1M | Latency p50 (30m, s) | Throughput p50 (30m, tok/s) | Uptime (30m) |
|---|---|---|---|---|---|---|
| Alibaba | 1,000,000 | $0.325 | $1.95 | — | — | 100% |
Provider data retrieved: 13.11.2026
Related articles
No published articles identify this model yet.