o3-mini
OpenAI Responses/🇺🇸 US/chat
o3-mini is OpenAI's most recent small reasoning model, providing high intelligence at the same cost and latency targets of o1-mini. o3-mini also supports key developer features, like Structured Outputs, function calling, Batch API, and more. Like other models in the o-series, it is designed to excel at science, math, and coding tasks.MoreLess
Which id to call
openai-responses/o3-miniThis exact deployment on OpenAI Responses, with no routing and no failover. Send it as the model field.
Input /1M
$1.10
$0.55 cached
Output /1M
$4.40
4.0x input
Context
200K
100K output
Added
Jan 2025
chat
Capabilities 4/8
Provider rates
What o3-mini costs
Provider prices per 1M tokens, updated September 8, 2026.moreless
These are the upstream provider rates. Pay as you go adds 5%, or 0% if you bring your own keys, and there is no per-request fee. Prompt caching and routing change what you pay against these rates, not the rates themselves.
Input /1M
$1.10
Output /1M
$4.40
Cache write /1M
-
Cache read /1M
$0.55
What a workload costs
- 100K input + 10K output
- $0.15
- 1M input + 100K output
- $1.54
- 10M input + 1M output
- $15.40
At the rates above, before caching. A cache read costs $0.55 per 1M, so repeated context lands under these figures.
OpenAI compatible
Call it in three lines
Change the base url, use your Requesty key, set the model to openai-responses/o3-mini. Existing OpenAI SDK code needs no other edit.
123456789101112131415from openai import OpenAI client = OpenAI( api_key="YOUR_REQUESTY_API_KEY", base_url="https://router.requesty.ai/v1", ) response = client.chat.completions.create( model="openai-responses/o3-mini", messages=[ {"role": "user", "content": "Explain quantum computing in one paragraph."}, ], ) print(response.choices[0].message.content)
Reference
Specs and data terms
What the catalog reports for this deployment, and what the provider does with the traffic.
Released 2025-01-31
Benchmark scores
Benchmarks measure the model, not this endpoint, so they are the same wherever these weights are served.
Graduate-level physics, chemistry & biology questions designed to resist Googling.
Artificial Analysis Intelligence Index: a composite of multiple evaluations measuring overall model capability.
Scores from official model cards, Artificial Analysis and public leaderboards. They measure specific skills and do not capture every aspect of model quality, so test on your own workload.
Same provider
More from OpenAI Responses
Newest first, on the same provider and the same key.
Reference
o3-mini questions
How much does o3-mini cost?
o3-mini is priced at $1.10 per million input tokens and $4.40 per million output tokens when accessed via Requesty. Prompt caching is supported, which can cut effective input cost by up to 90% on repeated context. Those are the upstream provider rates: pay as you go adds 5% on top, or 0% if you bring your own provider keys.
What is the context window of o3-mini?
o3-mini has a context window of 200K tokens, with a maximum output of 100K tokens per response. That's roughly 267 words of input you can fit in a single prompt.
How does o3-mini perform on benchmarks?
o3-mini scores 79.1% on MMLU Pro, 74.8% on GPQA Diamond, 71.7% on LiveCodeBench. See the full benchmark chart above for results across MMLU Pro, GPQA Diamond, SWE-Bench Verified, HumanEval, MATH, AIME, MMMU, and LiveBench.
What can o3-mini do?
o3-mini supports tool calling, extended reasoning, prompt caching, structured outputs (JSON schema). You can call it through any OpenAI-compatible client by pointing base_url to Requesty.
How do I use o3-mini with the OpenAI SDK?
Install the OpenAI SDK, set base_url to "https://router.requesty.ai/v1", set your API key to your Requesty key, and set the model to "openai-responses/o3-mini". The Quickstart above shows Python, JavaScript and cURL snippets.
Can I run o3-mini through Requesty?
Yes. o3-mini runs through Requesty's OpenAI-compatible API, served from OpenAI Responses. You do not host the model yourself: point base_url at Requesty, set the model to "openai-responses/o3-mini", and requests are routed to the upstream provider with automatic failover. The same key gives you 600+ other models too.
Call o3-mini through one endpoint
One key for this endpoint and 600+ other models. No markup on provider prices, automatic failover, caching built in.