openai
OpenAI: GPT-4.1 Mini (batch)
openai/gpt-4.1-mini:batch
Our take
AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.
openai/gpt-4.1-mini:batch is the batch variant of OpenAI's GPT-4.1 Mini as listed in the OpenRouter catalog. The catalog describes a mid-sized model that accepts text, image, and file inputs and produces text output, with a context window of roughly one million tokens and a knowledge cutoff in mid-2024. Its listing supports tool calling and structured outputs. The catalog description claims performance comparable to GPT-4o at lower latency and cost; this is a source-reported claim, not an independent measurement. No independent model card was available in this source pack.[1]
Strengths
- Accepts text, image, and file inputs with text output, so it can handle mixed-document workloads through a single endpoint, per the OpenRouter listing.[1]
- Exposes tool calling, tool choice, and structured output parameters, which suits automated pipeline and extraction tasks.[1]
- Catalog lists a context window of roughly one million tokens, useful for long documents or large batched prompts.[1]
Limitations
- Only OpenRouter catalog data was supplied; no independent model card or first-party documentation was available, so all capabilities here are catalog-reported rather than verified.[1]
- The listing reports no dedicated reasoning mode, and output is limited to text.[1]
- As a batch variant it is oriented to asynchronous, non-interactive jobs; throughput, latency, and quality should be validated on your own workload before adoption.[1]
Where to use it
- A reasonable candidate for bulk or offline processing such as document summarization, classification, or extraction where results are not needed in real time.[1]
- Worth evaluating for multimodal pipelines that combine text prompts with image or file inputs.[1]
- Potentially suited to high-volume structured-output or tool-calling automation, subject to accuracy validation on representative data.[1]
Sources
- [1] OpenRouter catalog · OpenAI: GPT-4.1 Mini (batch)Sources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
GPT-4.1 Mini is a mid-sized model delivering performance competitive with GPT-4o at substantially lower latency and cost. It retains a 1 million token context window and scores 45.1% on hard...
Specifications
- Model ID
- openai/gpt-4.1-mini:batch
- Canonical ID
- openai/gpt-4.1-mini-2025-04-14
- Creator
- openai
- Added to OpenRouter
- 14.04.2025
- Context length
- 1,047,576
- Modality
- text+image+file->text
- Input modalities
- image, text, file
- Output modalities
- text
- Token pricing
- USD per 1M tokens: in $0.200 / out $0.800
- Knowledge cutoff
- 30.06.2024
- 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 | — |
| Coding | CC — below the B band | — |
| Agents | No measurement | parameters: structured_outputs, tool_choice, tools |
| Writing | No measurement | output: text |
| Reasoning | No measurement | — |
| 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 | 20.2 | CC — below the B band | 13.11.2026 |
| Design Arena | models · 3dwin rate 30.5% · rank 135 | 820Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · codecategorieswin rate 47.5% · rank 133 | 984Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · datavizwin rate 49.2% · rank 114 | 1,034Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · gamedevwin rate 58.5% · rank 113 | 1,061Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · uicomponentwin rate 45.4% · rank 127 | 952Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · websitewin rate 47.8% · rank 135 | 990Elo | CC — below the B band | 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 | 1,047,576 | $0.200 | $0.800 | — | — | — |
Provider data retrieved: 13.11.2026
Related articles
No published articles identify this model yet.