qwen
Qwen: Qwen3.7 Plus (batch)
qwen/qwen3.7-plus:batch
Our take
AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.
qwen/qwen3.7-plus:batch is the batch-serving variant of Alibaba's Qwen3.7 Plus as listed in the OpenRouter catalog. Per that listing, it accepts text and image input and returns text, offers a 262,144-token context window, and exposes optional reasoning, tool calling, and structured outputs. OpenRouter's description positions it as a cost-effective member of the Qwen3.7 series. Because the only supplied evidence is the OpenRouter catalog and no independent model card was available in this source pack, these capabilities are source-reported rather than independently verified.[1]
Strengths
- Multimodal input: the catalog lists text and image inputs with text output, so it can accept vision-plus-text prompts.[1]
- Large context: a 262,144-token window suits long documents or multi-file inputs, per the listing.[1]
- Developer controls: the listing shows tool calling, structured outputs, JSON response formats, and optional reasoning support.[1]
Limitations
- Catalog-only evidence: every claim comes from OpenRouter's listing and no independent model card was in this source pack, so capabilities remain source-reported.[1]
- Index data bundled in the listing suggests modest measured performance on agentic tasks relative to its coding index; treat agentic use as unproven.[1]
- Knowledge cutoff, license terms, and hardware requirements are not stated in the evidence and remain unknown; validate on your actual workload.[1]
Where to use it
- Possibly suitable for cost-sensitive batch workloads like bulk summarization or document processing, given its cost-effective positioning; validate on your own data.[1]
- A candidate for long-context vision-plus-text tasks such as image-grounded analysis, subject to workload testing.[1]
- Worth trialing for structured-extraction or tool-use pipelines, since the catalog lists structured output and tool parameters; confirm reliability per workflow.[1]
Sources
- [1] OpenRouter catalog · Qwen: Qwen3.7 Plus (batch)Sources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
Qwen3.7-Plus is a cost-effective model in Alibaba's Qwen3.7 series. It supports text and image input with text output, building on the series' text capabilities with a comprehensive upgrade to its...
Specifications
- Model ID
- qwen/qwen3.7-plus:batch
- Canonical ID
- qwen/qwen3.7-plus-20260602
- Creator
- qwen
- Added to OpenRouter
- 03.06.2026
- Context length
- 262,144
- Modality
- text+image->text
- Input modalities
- text, image
- Output modalities
- text
- Token pricing
- USD per 1M tokens: in $0.230 / out $0.920
- 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 | BB — next 30% of the cohort | 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 | — |
| Embeddings | No measurement | — |
Evaluations
| Source | Benchmark | Value | Grade | Data retrieved |
|---|---|---|---|---|
| Artificial Analysis | Coding index | 55.9 | BB — next 30% of the cohort | 13.11.2026 |
| Artificial Analysis | Agentic index | 17.5 | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | models · 3dwin rate 48.1% · rank 44 | 1,221Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | models · asciiartwin rate 41% · rank 53 | 1,134Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · codecategorieswin rate 50% · rank 37 | 1,260Elo | AA — next 20% of the cohort | 13.11.2026 |
| Design Arena | models · datavizwin rate 51.4% · rank 23 | 1,276Elo | AA — next 20% of the cohort | 13.11.2026 |
| Design Arena | models · gamedevwin rate 48.7% · rank 39 | 1,251Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | models · svgwin rate 47% · rank 27 | 1,202Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | models · uicomponentwin rate 49.1% · rank 40 | 1,256Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | models · websitewin rate 50.3% · rank 34 | 1,262Elo | AA — next 20% 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 | 262,144 | $0.230 | $0.920 | — | — | — |
Provider data retrieved: 13.11.2026
Related articles
No published articles identify this model yet.