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OpenAI GPT · OpenAI
GPT-4o (2024-08-06).
GPT-4o (2024-08-06) is an OpenAI model, listed on 6 August 2024. It takes text, images and files and returns text, with a 128,000-token context window.
- Hosted API
- 128k context
Specification
- Provider
- OpenAI
- Family
- OpenAI GPT
- Listed
- 6 August 2024
- Catalogue id
- openai/gpt-4o-2024-08-06
- Context window
- 128,000 tokens
- Maximum output
- 16,384 tokens
- Inputs and output
- Text, images and files in; text out
- Capabilities
- Tool calling, structured outputs and web search
- Weights
- Not published — hosted API
- Knowledge cut-off
- 2023-10-31
- Listed price
- $2.50 input, $10.00 output, $1.25 cached input per million tokens
Provider-published specifications as of 30 October 2026, not figures we measured. Model families move quickly — check the provider's own documentation before committing to a number.
Source: GPT-4o (2024-08-06) in the OpenRouter catalogue, checked weekly. Confirm current terms in OpenAI's own documentation before you commit.
What it costs
Price the whole answer.
Illustrative calculation at listed rates: a batch of 10 million input tokens and 1 million output tokens costs $35.00 on GPT-4o (2024-08-06). A thousand requests of 2,000 input and 500 output tokens each costs $10.00. Calculation: input millions × input rate + output millions × output rate; it excludes reasoning tokens, retries, tools, tax and review time.
Compare cost per accepted result, not per token: replay the same work on two or three candidates and count the answers you would actually ship. Our model-routing approach sends each request to the cheapest model that passes.
THE REST OF THE FAMILY
Other OpenAI GPT models.
Every OpenAI GPT model in the catalogue. Our OpenAI GPT page covers where the family fits and how we evaluate it.
| GPT-4o (2024-08-06) | 6 Aug 2024 | — | — | 128k | $2.50 | $10.00 |
|---|---|---|---|---|---|---|
| GPT-6.1 Terra | 26 Oct 2026 | 51.0 | 91 | 1.05M | $1.00 | $5.00 |
| GPT-6.1 Sol | 29 Sep 2026 | 54.5 | 84 | 1.05M | $2.00 | $10.00 |
| GPT-6 Luna | 22 Sep 2026 | 27.8 | 116 | 1.05M | $0.100 | $0.500 |
| GPT-6 Sol | 22 Sep 2026 | — | — | 1.05M | $2.00 | $10.00 |
| GPT-6 Astra | 3 Sep 2026 | 56.9 | 88 | 1.05M | $10.00 | $50.00 |
| GPT-5.6 Luna | 9 Jul 2026 | — | — | 1.05M | $0.200 | $1.20 |
| GPT-5.6 Sol | 9 Jul 2026 | — | — | 1.05M | $4.00 | $20.00 |
| GPT-5.6 Terra | 9 Jul 2026 | — | — | 1.05M | $2.00 | $12.00 |
| GPT Chat Latest | 5 May 2026 | — | — | 400k | $5.00 | $30.00 |
| GPT-5.5 | 23 Apr 2026 | — | — | 1.05M | $5.00 | $30.00 |
| GPT-5.4 Mini | 17 Mar 2026 | — | — | 400k | $0.750 | $4.50 |
| GPT-5.4 Nano | 17 Mar 2026 | — | — | 400k | $0.200 | $1.25 |
| GPT-5.4 | 5 Mar 2026 | — | — | 1.05M | $2.50 | $15.00 |
| GPT-5.3-Codex | 5 Feb 2026 | — | 86 | 400k | $1.75 | $14.00 |
Intelligence and coding: Artificial Analysis indices at the model's best reasoning setting, and its measured output speed. Context and prices: the OpenRouter catalogue list price in USD per million tokens. Released: the provider's date where Artificial Analysis records one, otherwise the date the catalogue first listed it. Refreshed weekly; not measured by QQuantum.ai. Select a heading to sort.
Questions
Questions about GPT-4o (2024-08-06).
When was GPT-4o (2024-08-06) listed?
GPT-4o (2024-08-06) was listed on 6 August 2024 in the OpenRouter catalogue; the provider's own announcement may predate it.
What is the context window of GPT-4o (2024-08-06)?
128,000 tokens, with up to 16,384 output tokens per response, as listed in the OpenRouter catalogue on 30 October 2026. A long window is not the same as reliable recall across it; evaluate retrieval on your own documents.
How much does GPT-4o (2024-08-06) cost?
The catalogue lists $2.50 per million input tokens and $10.00 per million output tokens, and $1.25 per million cached input tokens (checked 30 October 2026). OpenAI's own rates, batch discounts and cloud marketplaces can differ.
Can GPT-4o (2024-08-06) run on our own hardware?
The catalogue lists no published weights for it, so it is used as a hosted API. Where data may not leave your infrastructure, an open-weight model is the alternative.
