OpenAI / openai/o3
o3 - access through LLMTR
Well suited to multi-step work across math, science, technical writing, and code analysis. A strong choice when you need deeper analysis and robust reasoning. You can tune thinking depth by setting `reasoning_effort` to `low`, `medium`, or `high`.
Technical specifications
| Canonical ID | openai/o3 |
|---|---|
| Provider | OpenAI |
| Context window | 200,000 tokens |
| Operations | CHAT_COMPLETIONS |
| Modalities | text, image |
Pricing
An 8% platform margin applies to credit top-ups; model usage prices are not separately marked up.
| Operation | Metric | Unit | Price |
|---|---|---|---|
| CHAT_COMPLETIONS | INPUT_TEXT | PER_1M_TOKENS | $2.00 |
| CHAT_COMPLETIONS | OUTPUT_TEXT | PER_1M_TOKENS | $8.00 |
Example usage
With existing OpenAI SDK flows, change only the base URL and model identifier.
curl https://llmtr.com/v1/chat/completions -H "Authorization: Bearer llmtr-your_key" -H "Content-Type: application/json" -d '{"model":"openai/o3","messages":[{"role":"user","content":"Hello"}]}'Guides about this model
- OpenAI o3: three-level reasoning_effort for math, science, and code analysis - The GPT-5.6 Terra article covered a six-level reasoning_effort range. o3 carries only three levels: low, medium, and high. This article covers how to use that simpler range on math, science, and code analysis tasks.
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