OpenAI
GPT-4o
model
gpt-4oMidStableVisionStreamingVisionToolsBatchLong contextUnited States
Context
128K
Input / 1M tokens
$2.50
Output / 1M tokens
$10.00
Cached input / 1M tokens
$1.44
Cache write / 1M tokens
— (bills at input price)
About this model
GPT-4o
OpenAI's GPT-4o — multimodal flagship combining strong general intelligence with vision, audio (via separate endpoint), and reliable tool calling. The default safe choice for new builds.
Key facts
- Maker
- OpenAI
- Context window
- 128K tokens
- Max output
- 16K tokens
- Lane
- Guarded: the provider has confirmed it does not train on your data
- Modality
- Text and image input
- Input price
- $2.50 per 1M tokens
- Output price
- $10.00 per 1M tokens
- Processing region(s)
- us
- Route
- Via OpenAI's API
- Cheapest plan
- Available from the Pro plan
- Price comparison
- Priced below 33 of 236 pro-band guarded models on Anoman (blended price: 1 part input to 3 parts output).
Released
2024-05
Training cutoff
2023-10
Parameters
Not disclosed
Ways to call
Ways to call GPT-4o
Each model ID below is callable through the Anoman AI API. Price and processing region depend on the route.
| Model ID | Route | Input / output per 1M tokens | Region(s) | Lane | Context |
|---|---|---|---|---|---|
| gpt-4o | Via OpenAI's API | $2.50 / $10.00 | us | Guarded | 128K |
| gpt-4o-openrouter | Via OpenRouter | $2.50 / $10.00 | global | Guarded | 128K |
| openrouter/gpt-4o | Via OpenRouter | $2.50 / $10.00 | us | Guarded | 128K |
Best for
Use cases
- General-purpose chat
- Vision + document understanding
- Agentic workflows with function calling
- Multilingual customer support
Strengths
What it does well
- Reliable tool calling + structured output
- Strong multilingual quality
- Vision built in
- 128K context window
- Battle-tested at production scale
Limitations
Know the trade-offs
- Trails newer models on coding (Claude Sonnet 4.6, Qwen 2.5 Coder)
- Knowledge cutoff trails competitors
- Premium pricing relative to open-weights at similar quality
Benchmarks
Published scores
Scores from official model cards and public leaderboards. Higher is better unless noted.
| Benchmark | Score | Measures |
|---|---|---|
| MMLU | 88.7 | General knowledge across 57 subjects |
| HumanEval | 90.2 | Python code generation, pass@1 |
| MATH | 76.6 | Mathematics, mixed difficulty |
| GPQA | 53.6 | Graduate-level science questions |
Code example
Chat completion with GPT-4o
from openai import OpenAI
client = OpenAI(
base_url="https://api.anoman.io/v1",
api_key="anm-sk-..."
)
response = client.chat.completions.create(
model="gpt-4o",
messages=[{"role": "user", "content": "Hello!"}]
)
print(response.choices[0].message.content)Alternatives
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