openai
OpenAI: GPT-4o
openai/gpt-4o
Our take
AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.
GPT-4o ("omni") is an OpenAI multimodal model listed in the OpenRouter catalog as accepting text, image, and file inputs and returning text, with a 128,000-token context window and an October 2023 knowledge cutoff. The catalog documents tool calling, structured outputs, seed, logprobs, and web search options; no dedicated reasoning mode is listed. Its catalog description claims GPT-4 Turbo-level intelligence, but the supplied text is truncated. Measured Design Arena results in the catalog show more losses than wins in tracked design categories. Only catalog data was supplied; an independent model card was not available in this source pack.[1]
Strengths
- The catalog lists text, image, and file inputs with text output, plus a 128,000-token context window.[1]
- A broad API surface is reported: tool calling, tool choice, structured outputs, response format, seed, logprobs, and web search options.[1]
- The catalog description presents it as maintaining GPT-4 Turbo-level intelligence; the description text is truncated in this source pack.[1]
Limitations
- Output is listed as text only, and the reasoning field is null, so no dedicated reasoning mode is documented in this source.[1]
- Measured, crowd-sourced Design Arena listings in the catalog show it losing more head-to-head comparisons than it wins across the tracked design and front-end categories.[1]
- Evidence is catalog-only: no independent model card was available in this source pack, and the listed October 2023 knowledge cutoff dates its knowledge; validate quality and cost on your own workload.[1]
Where to use it
- May suit multimodal assistants that read images or files and reply in text, given the reported input modalities and large context.[1]
- Could fit tool-using agents or structured-extraction pipelines, since the catalog documents tools, tool choice, structured outputs, and response format.[1]
- Worth trialing for long-document Q&A or summarization within the listed context window, subject to your own evaluation.[1]
Sources
- [1] OpenRouter catalog · OpenAI: GPT-4oSources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
GPT-4o ("o" for "omni") is OpenAI's latest AI model, supporting both text and image inputs with text outputs. It maintains the intelligence level of [GPT-4 Turbo](/models/openai/gpt-4-turbo) while being twice as...
Specifications
- Model ID
- openai/gpt-4o
- Creator
- openai
- Added to OpenRouter
- 13.05.2024
- Context length
- 128,000
- Modality
- text+image+file->text
- Input modalities
- text, image, file
- Output modalities
- text
- Token pricing
- USD per 1M tokens: in $2.5 / out $10
- Knowledge cutoff
- 31.10.2023
- 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 | No measurement | — |
| 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 |
|---|---|---|---|---|
| Design Arena | models · 3dwin rate 39.2% · rank 131 | 852Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · codecategorieswin rate 34.8% · rank 144 | 851Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · datavizwin rate 36% · rank 134 | 858Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · gamedevwin rate 42.3% · rank 139 | 897Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · uicomponentwin rate 38.1% · rank 139 | 876Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · websitewin rate 31.5% · rank 149 | 824Elo | 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) |
|---|---|---|---|---|---|---|
| Azure | 128,000 | $2.5 | $10 | — | — | 100% |
| OpenAI | 128,000 | $2.5 | $10 | — | — | 100% |
Provider data retrieved: 13.11.2026
Related articles
No published articles identify this model yet.