openai
OpenAI: GPT-5.1 (batch)
openai/gpt-5.1:batch
Our take
AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.
OpenRouter’s catalog lists openai/gpt-5.1:batch as an OpenAI batch variant of GPT-5.1, mapped to canonical model openai/gpt-5.1-20251113. The listing reports text, image, and file inputs with text output, a 400,000-token context, optional reasoning controls, and API parameters for tools, structured responses, seeds, token limits, and verbosity. It also includes measured design-category arena results and a coding index, while agentic and intelligence index values are absent. An independent model card was not available in this source pack.[1]
Strengths
- The catalog reports text, image, and file inputs, offering broad input support for producing text responses.[1]
- The reported 400,000-token context may help with long documents or multi-file prompts; practical limits still need workload testing.[1]
- Supported parameters include optional reasoning and controls for effort, verbosity, tools, structured outputs, response format, seeds, and token limits.[1]
Limitations
- Only OpenRouter catalog evidence was supplied; an independent model card was not available, so provider documentation and workload tests are needed before production reliance.[1]
- Reasoning is not mandatory and is disabled by default; the listed default effort is medium, so behavior should be verified rather than assumed.[1]
- Performance evidence is narrow: OpenRouter reports design-category arena outcomes and a coding index, while agentic and intelligence index fields are null.[1]
Where to use it
- Potentially suitable for batch-oriented conversion of large text, image, or file collections into text, after confirming the variant’s batch semantics and latency fit.[1]
- Candidate for long-document or multi-file analysis given the reported context size; validate quality on representative inputs.[1]
- Candidate for workflows needing tool calls or structured text responses; verify real endpoint behavior before rollout.[1]
Sources
- [1] OpenRouter catalog · OpenAI: GPT-5.1 (batch)Sources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
GPT-5.1 is the latest frontier-grade model in the GPT-5 series, offering stronger general-purpose reasoning, improved instruction adherence, and a more natural conversational style compared to GPT-5. It uses adaptive reasoning...
Specifications
- Model ID
- openai/gpt-5.1:batch
- Canonical ID
- openai/gpt-5.1-20251113
- Creator
- openai
- Added to OpenRouter
- 13.11.2025
- Context length
- 400,000
- Modality
- text+image+file->text
- Input modalities
- image, text, file
- Output modalities
- text
- Token pricing
- USD per 1M tokens: in $0.625 / out $5
- 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 · default medium · efforts: high, medium, low, none · parameters: include_reasoning, reasoning, reasoning_effort |
| 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 · default medium · efforts: high, medium, low, none · parameters: include_reasoning, reasoning, reasoning_effort |
| Document analysis | No measurement | input: file |
| 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 | 49.4 | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | models · 3dwin rate 43.7% · rank 112 | 1,044Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · asciiartwin rate 48.6% · rank 58 | 1,114Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · codecategorieswin rate 53% · rank 79 | 1,161Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | models · datavizwin rate 58% · rank 58 | 1,202Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | models · gamedevwin rate 55.9% · rank 67 | 1,169Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | models · svgwin rate 57.4% · rank 53 | 1,141Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | models · uicomponentwin rate 52.9% · rank 78 | 1,157Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · websitewin rate 54% · rank 77 | 1,180Elo | 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) |
|---|---|---|---|---|---|---|
| OpenAI | 400,000 | $0.625 | $5 | — | — | — |
Provider data retrieved: 13.11.2026
Related articles
No published articles identify this model yet.