o3 Mini pricing for math reasoning

Quick start

Call o3 Mini with the OpenAI Python SDK:

from openai import OpenAI

client = OpenAI()
response = client.chat.completions.create(
    model="o3-mini",
    max_tokens=3000,
    messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.0149 per call at standard rates
# Input:  $1.10/MTok
# Output: $4.40/MTok

How o3 Mini compares on cost

Per-call cost for all models scoring 50+ on math reasoning benchmarks. Hover for details.

Cheapest viable option: Claude Sonnet 5 at $0.0330/call (-122% less, 90/100 quality).

What drives math reasoning cost

Short problems, long solutions. Input is trivial and output is large because the derivation is the answer, so output rate is effectively the only price that matters. Models differ sharply in how much they show their working, which means two models at the same output rate can differ substantially in real cost per problem.

For o3 Mini specifically, that means output tokens cost 4.0x more than input, at $4.40 vs $1.10 per MTok. At this use case’s 1,500/3,000 token split, output accounts for 89% of the $0.0149 per-call cost.

o3 Mini quality benchmarks for math reasoning

Benchmark data for math reasoning is pending for o3 Mini. Test against your own evaluation suite before moving to production.

Performance across all task types

o3 Mini scores by task type. Math Reasoning highlighted.

Confidence scores are a third-party benchmark snapshot from week 29 of 2026. This snapshot is 10 weeks old, so treat the scores as directional and validate against your own evals.

About o3 Mini

Backfilled on 2026-09-23. Prices confirmed by the provider pricing page and the LiteLLM cross-check. Release date not published in a machine-readable source. Not yet benchmarked, so never recommended.

Other models from GPT

You can compare o3 Mini head-to-head against any other model on our model comparison pages, or track how pricing has changed over time on the pricing history tracker.

Frequently asked questions