OpenAI o4-mini high
nano-gpt/o4-mini-high出品方： nano-gpt · 系列: o-mini · 发布 2025-04-16
⚠ 本模型为社区微调 / 衍生版本，非厂商官方发布。
Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.
能力清单
Model fit scores
0–100 · higher is betterThese 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.
Coding77
- Tool calling40/40
- Structured output20/20
- Reasoning10/10
- Context window (100K → 1M)6/20
- Provider availability1/10
Agents91
- Tool calling35/35
- Structured output25/25
- Reasoning15/15
- Output token limit15/15
- Provider availability1/10
JSON / structured output79
- Structured output / JSON mode50/50
- Tool calling20/20
- Temperature control0/10
- Price-friendly for high-volume9/20
Cost efficiency44
- Headline price (log-scaled)44/95
- Has prompt-cache pricing0/5
Long context55
- Context window (100K → 2M)45/90
- Has published price for full window10/10
Production-readiness50
- 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)0/15
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.
| Scenario | Cost | Assumption |
|---|---|---|
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. |
定价详情
推荐定价来自 nano-gpt · openai/o4-mini-high
在 1 家渠道可用
| 服务商 | 服务商模型 ID | 输入 / 1M | 输出 / 1M | 上下文 | 发布日期 |
|---|---|---|---|---|---|
| NanoGPT nano-gpt | openai/o4-mini-high | $1.10 | $4.40 | 200K | 2025-04-16 |
Frequently asked questions
How much does OpenAI o4-mini high cost?
OpenAI o4-mini high costs $1.10 per 1M input tokens and $4.40 per 1M output tokens, sourced from nano-gpt. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.
What is the context window of OpenAI o4-mini high?
OpenAI o4-mini high 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 OpenAI o4-mini high support tool calling?
Yes. OpenAI o4-mini high 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 OpenAI o4-mini high support structured output / JSON mode?
Yes. OpenAI o4-mini high supports structured output / JSON-schema-constrained decoding. This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.
Can OpenAI o4-mini high accept image input?
No. OpenAI o4-mini high only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.
Is OpenAI o4-mini high open-weight?
No. OpenAI o4-mini high is a proprietary model — only nano-gpt (and any approved hosting partners) can serve it. The pricing above reflects the cheapest API access.
What are the best alternatives to OpenAI o4-mini high?
If OpenAI o4-mini high doesn't fit, consider Brave (Answers), Exa (Research), Auto model (Basic). 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.
Explore more
More nano-gpt models
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- Exa (Research)$2.50 in / $2.50 out
- Auto model (Basic)$10.00 in / $19.99 out
- Jamba Mini$0.20 in / $0.41 out
- Yi Large$3.20 in / $3.20 out
Capability lists this model is in
最近更新：
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.