AIモデルインテリジェンス

o4-mini

azure/o4-mini

提供: azure · ファミリー: o-mini · リリース 2025-04-16 · 知識カットオフ: 2024-05

$1.10
入力 / 100万トークン
$4.40
出力 / 100万トークン
200K
コンテキスト長
100K
最大出力

Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.

機能一覧

ツール呼び出し推論? 構造化出力添付オープンウェイト温度制御
モダリティ: 入力 text, image · 出力 text

Model fit scores

0–100 · higher is better

These scores reward declared capabilities, context size, price and provider availability — they are not benchmark results. Use them as a directional signal alongside your own evaluation.

Coding57
  • Tool calling40/40
  • Structured output0/20
  • Reasoning10/10
  • Context window (100K → 1M)6/20
  • Provider availability1/10
Agents66
  • Tool calling35/35
  • Structured output0/25
  • Reasoning15/15
  • Output token limit15/15
  • Provider availability1/10
JSON / structured output29
  • Structured output / JSON mode0/50
  • Tool calling20/20
  • Temperature control0/10
  • Price-friendly for high-volume9/20
Cost efficiency49
  • Headline price (log-scaled)44/95
  • Has prompt-cache pricing5/5
Long context55
  • Context window (100K → 2M)45/90
  • Has published price for full window10/10
Vision81
  • Accepts image input50/50
  • Context window (10K → 1M)20/30
  • Has published price10/10
  • Provider availability1/10
Production-readiness65
  • Number of independent providers5/40
  • Has published per-token price20/20
  • Context window ≥ 8K15/15
  • No data inconsistencies across providers10/10
  • Official model (not derivative)15/15

Cost Efficiency Index

Open full calculator →

Estimated cost using the recommended provider's headline rate. Each scenario fixes average input/output tokens — the assumptions are shown in the third column.

ScenarioCostAssumption
RAG answer
per 1,000 RAG answers
$7.70
< $0.01 per request
5K input tokens (query + 4 retrieved chunks of ~1K each) and a 500-token answer. Typical SaaS knowledge-base bot.
Support ticket triage
per 10,000 tickets
$15.40
< $0.01 per request
1K input tokens (ticket body + system prompt) and a 100-token JSON classification reply. High-volume customer support.
Data extraction
per 1,000 documents
$4.40
< $0.01 per request
2K input tokens (a single document page) and a 500-token JSON extraction. ETL / invoice / form pipelines.
Code review
per 1,000 PRs
$13.20
$0.01 per request
8K input tokens (diff + surrounding files) and a 1K-token review comment. PR-bot workloads.
Agent step
per 1,000 steps
$15.84
$0.02 per request
12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step.

料金詳細

推奨料金 (提供元): azure · o4-mini

$1.10
入力
$4.40
出力
$0.280
キャッシュ読み取り

1 か所で利用可能

プロバイダープロバイダーモデルID入力 / 1M出力 / 1Mコンテキストリリース日
Azure
azure
o4-mini$1.10$4.40200K2025-04-16

Frequently asked questions

How much does o4-mini cost?

o4-mini costs $1.10 per 1M input tokens and $4.40 per 1M output tokens, sourced from azure. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.

What is the context window of o4-mini?

o4-mini has a context window of 200K tokens, with a max output of 100K tokens per reply. This is the total combined size of prompt + completion.

Does o4-mini support tool calling?

Yes. o4-mini supports tool calling (function calling). This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.

Does o4-mini support structured output / JSON mode?

Support for structured output / JSON-schema-constrained decoding is not reported for o4-mini in our data source. Verify with azure's official documentation before relying on it in production.

Can o4-mini accept image input?

Yes. o4-mini accepts both text and image input. Vision pricing per image is usually billed on top of the regular token rate — check azure's docs for the exact rule.

Is o4-mini open-weight?

No. o4-mini is a proprietary model — only azure (and any approved hosting partners) can serve it. The pricing above reflects the cheapest API access.

What are the best alternatives to o4-mini?

If o4-mini doesn't fit, consider Codex Mini, Ministral 3B, text-embedding-3-large. Each one targets the same use case — see the Related links below for direct head-to-head pages.

Where does this data come from?

All numbers come from the public models.dev API and are normalised into a single canonical model record. We re-pull daily and write any changes (price, context, capability) to the /changelog page.

More azure models

最終更新:

Data is sourced from models.dev and normalized for comparison. Prices and capabilities may change. Always verify critical production decisions with the provider's official documentation.