GPT-4o-mini
Small omni GPT for cheap multimodal assistance and production-scale traffic
- Context
- 128K
- Released
- —
- Input / 1M tokens
- $0.15
- Output / 1M tokens
- $0.60
- Cached input / 1M tokens
- $0.08
Sources:models.devOpenRouter
Benchmarks
DeepSWE is the primary coding benchmark where an exact model evaluation exists. Other sourced evaluations appear below; missing scores are not zero.
Not evaluated in DeepSWE 1.1 as of 2026-09-22. Results are only shown for exact model versions in the official dataset. Official leaderboard.
No benchmark results have been matched to this model yet.
Specifications
- Developer
- OpenAI
- Model family
- GPT
- Type
- Language model
- Predecessor
- —
- Successor
- —
- Released
- —
- Model ID
openai/gpt-4o-mini- Openness
- Closed
- License
- —
- Input modalities
- text, image, file
- Output modalities
- text
- Modality
- text+image+file->text
- Tokenizer
- GPT
- Max output tokens
- 16K
- Knowledge cutoff
- 2023-09
- Hugging Face
- —
- Source freshness
- Metadata synced Oct 8, 2026, 10:17 PM UTC
Additional source evidence
- Source model
- openai/gpt-4o-mini
- Source family
- gpt-mini
- Last updated
- 2024-07-18
- Knowledge cutoff
- 2023-09
- Model context
- 128K
- Model output limit
- 16K
- Open weights
- No
- File attachments
- Yes
- Reasoning
- No
- Tool calling
- Yes
- Structured output
- Yes
- Temperature control
- Yes
Published benchmarks
Complete source record (JSON)
{
"id": "openai/gpt-4o-mini",
"name": "GPT-4o mini",
"description": "Small omni GPT for cheap multimodal assistance and production-scale traffic",
"family": "gpt-mini",
"last_updated": "2024-07-18",
"knowledge": "2023-09",
"attachment": true,
"reasoning": false,
"tool_call": true,
"structured_output": true,
"temperature": true,
"modalities": {
"input": [
"text",
"image",
"pdf"
],
"output": [
"text"
]
},
"limit": {
"context": 128000,
"output": 16384
},
"benchmarks": [
{
"name": "Aider Polyglot",
"score": 3.6,
"source": "https://aider.chat/docs/leaderboards/",
"metric": "percent correct",
"date": "2024-12-21"
},
{
"name": "SciCode",
"score": 22.9,
"source": "https://openrouter.ai/openai/gpt-4o-mini/benchmarks",
"metric": "percent correct",
"date": "2026-03-11"
}
],
"release_date": "2024-07-18",
"open_weights": false
}Infrastructure
Provider availability
| Provider | Endpoint | Context | Input /M tokens | Output /M tokens | Cached input /M tokens | Cache write /M tokens | Uptime 1d | Data handling |
|---|---|---|---|---|---|---|---|---|
| azure | 128K | $0.15 | $0.60 | $0.08 | — | 99.79% | ZDR: YesTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| azureBatch pricing | 128K | $0.15 | $0.60 | $0.08 | — | 99.79% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| openai | 128K | $0.15 | $0.60 | $0.08 | — | 100.00% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| openaiBatch pricing | 128K | $0.15 | $0.60 | $0.08 | — | 100.00% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| azure/swedencentral | 128K | $0.17 | $0.66 | $0.08 | — | 100.00% | ZDR: YesTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 | |
| azure/swedencentralBatch pricing | 128K | $0.17 | $0.66 | $0.08 | — | 100.00% | ZDR: NoTraining: Unknown Prompt logging: Unknown Retention: Unknown Checked 2026-10-15 |
Provider data:OpenRouter
Text provenance
EU · product-scopedOpenAI textGrain watermarking
In the EU, ChatGPT-generated text uses textGrain. OpenAI says API customers can opt in globally for select models, so watermarking depends on the product surface and configuration.
Official explanation