openai
OpenAI: o3 (batch)
openai/o3: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 presents openai/o3:batch as a batch variant of OpenAI’s o3-2025-04-16, producing text from text, image, and file inputs. The entry reports mandatory reasoning and lists tool calling, structured outputs, response-format controls, and a large context window. It also includes measured design-arena results with mixed outcomes. Because this source pack contains only catalog data and no independent model card, real batch-workload behavior remains unverified.[1]
Strengths
- The catalog reports breadth across math, science, coding, visual reasoning, technical writing, and instruction following.[1]
- Accepts text, image, and file inputs while producing text; the entry also lists tools, structured outputs, and response-format options.[1]
- The catalog reports a large context window and mandatory reasoning; these are declared capabilities rather than measured results.[1]
Limitations
- Only OpenRouter catalog evidence was supplied; an independent model card was not available in this source pack.[1]
- The catalog marks reasoning as mandatory and lists no selectable effort levels, so no documented control over that effort is shown.[1]
- No batch-specific latency, throughput, reliability, or completion behavior is documented; validate the variant on representative workloads.[1]
Where to use it
- Consider evaluating batch-oriented workloads that require reasoning and mixed text, image, and file inputs, after testing the end-to-end behavior.[1]
- May merit testing for coding, data visualization, game-development tasks, UI components, and website drafts because the catalog supplies arena measurements in these areas, with mixed outcomes.[1]
- Potentially suitable for technical writing, instruction following, and math, science, or visual-reasoning tasks where the catalog reports strength, subject to task-level verification.[1]
Sources
- [1] OpenRouter catalog · OpenAI: o3 (batch)Sources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
o3 is a well-rounded and powerful model across domains. It sets a new standard for math, science, coding, and visual reasoning tasks. It also excels at technical writing and instruction-following....
Specifications
- Model ID
- openai/o3:batch
- Canonical ID
- openai/o3-2025-04-16
- Creator
- openai
- Added to OpenRouter
- 16.04.2025
- Context length
- 200,000
- Modality
- text+image+file->text
- Input modalities
- image, text, file
- Output modalities
- text
- Token pricing
- USD per 1M tokens: in $1 / out $4
- Knowledge cutoff
- 30.06.2024
- Expiration date
- 11.12.2026
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: mandatory · parameters: include_reasoning, reasoning |
| Coding | No measurement | — |
| Agents | No measurement | parameters: structured_outputs, tool_choice, tools |
| Writing | No measurement | output: text |
| Reasoning | No measurement | reasoning: mandatory · parameters: include_reasoning, reasoning |
| 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 |
|---|---|---|---|---|
| Design Arena | models · codecategorieswin rate 51.9% · rank 128 | 1,010Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · datavizwin rate 48.1% · rank 62 | 1,200Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | models · gamedevwin rate 56.9% · rank 122 | 1,025Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · uicomponentwin rate 53.3% · rank 121 | 1,009Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · websitewin rate 53.8% · rank 129 | 1,029Elo | 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 | 200,000 | $1 | $4 | — | — | — |
Provider data retrieved: 13.11.2026
Related articles
No published articles identify this model yet.