azure/o4-mini-2025-04-16| Provider | Input, $ per 1M | Output, $ per 1M | In our data since |
|---|---|---|---|
Microsoft Foundry
azure/o4-mini-2025-04-16
|
$1.1 | $4.4 | 31 Jul 2026 |
| OpenAI | $1.1 | $4.4 | 31 Jul 2026 |
Microsoft Foundry
azure/us/o4-mini-2025-04-16
|
$1.21 | $4.84 | 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.
| Task set | Result | Run conditions | Measured by |
|---|---|---|---|
| Arena Score, mathematics | 1,386.94 1,376–1,398 | — | — |
| Arena Score, programming | 1,368.52 1,362–1,375 | — | — |
| Arena Score in English | 1,366.19 1,361–1,371 | — | — |
| Arena Score in French | 1,359.86 1,334–1,385 | — | — |
| Arena Score, overall | 1,352.74 1,349–1,357 | — | — |
| Arena Score, hard prompts | 1,350.98 1,346–1,356 | — | — |
| Arena Score, multi-turn dialogue | 1,349.24 1,342–1,356 | — | — |
| Arena Score in Spanish | 1,345.84 1,325–1,366 | — | — |
| Arena Score, expert questions | 1,343.59 1,331–1,356 | — | — |
| Arena Score in Russian | 1,335.24 1,325–1,346 | — | — |
| Arena Score, instruction following | 1,321.33 1,315–1,327 | — | — |
| Arena Score, long queries | 1,314.94 1,308–1,322 | — | — |
| Arena Score, creative writing | 1,295.6 1,287–1,304 | — | — |
| Arena Score, text recognition in images | 1,197.64 1,189–1,206 | — | — |
| Arena Score, understanding diagrams | 1,197.47 1,185–1,210 | — | — |
| Arena Score, working with images | 1,194.83 1,188–1,202 | — | — |
| MATH, difficulty level five | 97.83 % | effort: high · with a tuned harness | Epoch evaluations |
| Mock AIME 2024–2025 — olympiad problems | 81.65 % | effort: low · with a tuned harness | Epoch evaluations |
| Fiction.LiveBench — holding a long context | 77.8 % | effort: medium | Fiction.live leaderboard |
| Creative writing (Lech Mazur’s evaluation) | 75 % | effort: medium | lechmazur/writing Github repository |
| GPQA Diamond — graduate-level questions | 72.81 % | effort: low · with a tuned harness | Epoch evaluations |
| Aider Polyglot — code edits in six languages | 72 % | effort: high · with a tuned harness | Aider LLM Leaderboards |
| GeoBench — locating a place from a photograph | 64 % | effort: high | GeoBench leaderboard |
| CadEval — building CAD models with code | 62 % | effort: medium | CadEval Dashboard |
| ARC-AGI — generalising to unseen patterns | 58.7 % | effort: high · with a tuned harness | ARC Prize Leaderboard |
| WeirdML — unusual machine learning tasks | 52.56 % | effort: high | WeirdML Leaderboard |
| FrontierMath, levels 1–3 | 36.14 % | effort: high | Epoch evaluations |
| SimpleBench — trick questions | 26.44 % | effort: high | SimpleBench Leaderboard |
| GDPval — tasks from real occupations | 25.3 % | effort: high | — |
| SimpleQA Verified — factual accuracy | 23.9 % | effort: low | Epoch evaluations |
| Chess puzzles | 22.14 % | effort: low | Epoch evaluations |
| Humanity’s Last Exam — expert-level questions | 13.95 % | effort: high | — |
| ARC-AGI-2 | 6.11 % | effort: high | — |
| FrontierMath, level 4 — research-grade problems | 4.88 % | effort: high | Epoch evaluations |
| GSO-Bench — code optimisation | 3.6 % | effort: high | GSO Leaderboard |
| CritPt — physics problems | 0.6 % | effort: high | — |