OpenAI

o3 2025-04-16

Type
language model
Context
200K tokens
Max output
100K
API string
azure/o3-2025-04-16

The provider has deprecated this model. It still responds, but it is not a good choice for new projects.

Prices by provider

Provider Input, $ per 1M Output, $ per 1M In our data since
Microsoft Foundry azure/o3-2025-04-16 $2 $8 31 Jul 2026
OpenAI $2 $8 31 Jul 2026
Microsoft Foundry azure/us/o3-2025-04-16 $2.2 $8.8 31 Jul 2026

Only the base tier and only per-token prices are shown. Batch, discounted and cached rates, as well as prices per image or per second of video, do not go into this table: they cannot stand in the same column as a price per million tokens.

A single provider appears several times if it sells this model under different identifiers and at different prices — for example, at different weight precision. The identifier is shown next to the name. Identical offers that arrived from two sources under different spellings are merged into one row.

The date in the last column is the day this price first entered our collection. The price may well be older: before that day we simply were not recording it. It has not changed since — otherwise a new row with a new date would stand in its place.

Measurement results

Task set Result Run conditions Measured by
Arena Score in French 1,445.04 1,422–1,468 — —
Arena Score, mathematics 1,424.48 1,415–1,434 — —
Arena Score in English 1,414.47 1,410–1,419 — —
Arena Score, overall 1,409.5 1,406–1,413 — —
Arena Score in Russian 1,408.32 1,399–1,418 — —
Arena Score, programming 1,408.19 1,402–1,414 — —
Arena Score, multi-turn dialogue 1,404.93 1,398–1,412 — —
Arena Score, hard prompts 1,401.88 1,397–1,407 — —
Arena Score, expert questions 1,400.18 1,389–1,412 — —
Arena Score in Spanish 1,384.08 1,365–1,403 — —
Arena Score, long queries 1,370.54 1,364–1,377 — —
Arena Score, instruction following 1,367.67 1,362–1,373 — —
Arena Score, creative writing 1,359.4 1,352–1,367 — —
Arena Score, understanding diagrams 1,218.28 1,206–1,230 — —
Arena Score, text recognition in images 1,218.19 1,210–1,226 — —
Arena Score, working with images 1,215.41 1,209–1,222 — —
MATH, difficulty level five 97.77 % effort: high · with a tuned harness Epoch evaluations
Fiction.LiveBench — holding a long context 88.9 % effort: medium Fiction.live leaderboard
Creative writing (Lech Mazur’s evaluation) 83.9 % effort: medium lechmazur/writing Github repository
Mock AIME 2024–2025 — olympiad problems 83.87 % effort: low · with a tuned harness Epoch evaluations
Aider Polyglot — code edits in six languages 81.3 % effort: medium · with a tuned harness Aider LLM Leaderboards
GPQA Diamond — graduate-level questions 75.76 % effort: low · with a tuned harness Epoch evaluations
CadEval — building CAD models with code 74 % effort: medium CadEval Dashboard
GeoBench — locating a place from a photograph 74 % effort: high GeoBench leaderboard
SWE-bench Verified — fixing bugs in repositories 62.32 % effort: medium · with a tuned harness Epoch evaluations
ARC-AGI — generalising to unseen patterns 60.8 % effort: high · with a tuned harness ARC Prize Leaderboard
SimpleQA Verified — factual accuracy 53 % effort: high Epoch evaluations
WeirdML — unusual machine learning tasks 52.42 % effort: high WeirdML Leaderboard
DeepResearch Bench — deep research 46.6 % effort: medium DeepResearchBench Leaderboard
SimpleBench — trick questions 43.72 % effort: high SimpleBench Leaderboard
GDPval — tasks from real occupations 30.8 % effort: medium —
Chess puzzles 23.19 % effort: low Epoch evaluations
OSWorld — working inside an operating system, first version 23 % effort: medium · with a tuned harness OS World Website
APEX-Agents 17.2 % effort: high —
Humanity’s Last Exam — expert-level questions 16.3 % effort: high —
GSO-Bench — code optimisation 8.8 % effort: high GSO Leaderboard
ARC-AGI-2 6.53 % effort: high —
CritPt — physics problems 1.4 % effort: high —