qwen
Qwen: Qwen3.8 27B (batch)
qwen/qwen3.8-27b:batch
Our take
AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.
qwen/qwen3.8-27b:batch is a 27B-parameter, dense, open-weight vision-language model from Qwen, listed on OpenRouter as a batch variant. It accepts text, image, and video inputs and produces text, with a native 262,144-token context that the vendor describes as extensible to one million tokens. Reasoning is enabled by default and its effort is tunable per request. The vendor's model card reports gains in coding and agentic work, but these are self-published figures awaiting independent confirmation.[1][2]
Strengths
- Native vision-language design: accepts text, images, and video, with the model card citing documents, STEM diagrams, and hour-scale videos.[1][2]
- Vendor-published benchmarks report strong results in coding, agentic, and long-horizon tasks.[2]
- Open weights under Apache-2.0, compatible with Transformers, vLLM, and SGLang; broad API controls including tools, structured output, and adjustable reasoning.[1][2]
Limitations
- Benchmark figures are vendor-published; no independent evaluation was included in this source pack, so validate on your own workloads.[1][2]
- Output is text only; it cannot generate images or video despite multimodal input.[1]
- Knowledge cutoff is not stated, and catalog-level evidence leaves batch-specific behavior and safety characteristics undocumented.[1]
Where to use it
- Offline batch jobs such as bulk summarization, code review, or dataset labeling that tolerate asynchronous processing.[1]
- Multimodal assistants that read images or long videos and answer in text.[1][2]
- Agentic coding and multi-step workflows where adjustable reasoning effort helps trade cost for depth.[1][2]
Sources
- [1] OpenRouter catalog · Qwen: Qwen3.8 27B (batch)Sources checked: Nov 13, 2026
- [2] Model documentation · Qwen: Qwen3.8 27B (batch)Sources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
Qwen3.8 27B is an open-weight dense vision-language model from Qwen. It is suited for coding, professional workflows, research, multimodal interaction, and long-running agent tasks, with flexible thinking that can be...
Specifications
- Model ID
- qwen/qwen3.8-27b:batch
- Canonical ID
- qwen/qwen3.8-27b-20260814
- Creator
- qwen
- Added to OpenRouter
- 14.08.2026
- Context length
- 262,144
- Modality
- text+image+video->text
- Input modalities
- text, image, video
- Output modalities
- text
- Token pricing
- USD per 1M tokens: in $0.160 / out $2
- 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 | CC — below the B band | reasoning: optional · default xhigh · efforts: xhigh, medium, low, none · parameters: include_reasoning, reasoning, reasoning_effort |
| Coding | AA — next 20% of the cohort | — |
| Agents | AA — next 20% of the cohort | parameters: structured_outputs, tool_choice, tools |
| Writing | No measurement | output: text |
| Reasoning | No measurement | reasoning: optional · default xhigh · efforts: xhigh, medium, low, none · parameters: include_reasoning, reasoning, reasoning_effort |
| 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 | Intelligence index | 20.1 | CC — below the B band | 13.11.2026 |
| Artificial Analysis | Coding index | 68.1 | AA — next 20% of the cohort | 13.11.2026 |
| Artificial Analysis | Agentic index | 45.8 | 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) |
|---|---|---|---|---|---|---|
| DeepInfrabf16 | 262,144 | $0.160 | $2 | — | — | — |
Provider data retrieved: 13.11.2026
Related articles
No published articles identify this model yet.