OpenAI · Efficient
OpenAI o3-mini (Low)
OpenAI's o3-mini reasoning model with reasoning effort set to low.
- Reasoning
- Tools
- Structured output
- Input
- Text
- Output
- Text
- Reasoning effort
- low · medium · high
- Discovery tier
- Efficient
Pricing
USD per 1M tokens- Input
- $1.10
- Output
- $4.40
- Cache read
- $0.55
Reference prices as published by the model provider. API example
Specifications
- Context window
- 200K
- Max output
- 100K
Side by side
OpenAI o3-mini (Low) compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| OpenAI o3-mini (Low)OpenAIThis model | Kimi K2 0711 FastMoonshotRemove | |
|---|---|---|
| Provider | OpenAI | Moonshot |
| Discovery tier | Efficient | Open weights |
| Added | Jan 31, 2026 | Dec 15, 2025 |
| Limits | ||
| Context window | 200KBest | 131.07K |
| Max output | 100KBest | 16.38K |
| Pricing, USD per 1M tokens | ||
| Input | $1.10 | $0.40Best |
| Output | $4.40 | $1.80Best |
| Cache read | $0.55 | — |
| Benchmark indexes | ||
| Intelligence Index | 12.5 | 12.7Best |
| Math Index | — | 57.0 |
| Capabilities | ||
| Reasoning | Yes | No |
| Tools | Yes | No |
| Structured output | Yes | No |
| PDF input | No | Yes |
| Reasoning effort | low, medium, high | — |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- OpenAI o3-mini (Low)
- Kimi K2 0711 Fast
Intelligence Index
- OpenAI o3-mini (Low)12.5
- Kimi K2 0711 Fast12.7
OpenAI o3-mini (Low): Better than 27% of 326 scored models
Indexes
Math Index
Composite of the math evaluations
- OpenAI o3-mini (Low): —
- Kimi K2 0711 Fast: 57.0
Document reasoning
AA-LCRv1.1
Reasoning across long documents
- OpenAI o3-mini (Low): —
- Kimi K2 0711 Fast: 53.0%
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- OpenAI o3-mini (Low): 7.9%Top
- Kimi K2 0711 Fast: 7.4%
GPQA Diamond
Graduate-level science questions
- OpenAI o3-mini (Low): 74.8%
- Kimi K2 0711 Fast: 76.6%Top
MMLU-Pro
Multi-subject knowledge and reasoning
- OpenAI o3-mini (Low): 79.1%
- Kimi K2 0711 Fast: 82.4%Top
IFBench
Following precise output instructions
- OpenAI o3-mini (Low): —
- Kimi K2 0711 Fast: 41.5%
Coding
LiveCodeBench
Recent competitive programming problems
- OpenAI o3-mini (Low): 71.7%Top
- Kimi K2 0711 Fast: 55.6%
Math
AIME 2025
Competition mathematics, 2025 problems
- OpenAI o3-mini (Low): —
- Kimi K2 0711 Fast: 57.0%
AIME
Competition mathematics
- OpenAI o3-mini (Low): 77.0%Top
- Kimi K2 0711 Fast: 69.3%
MATH-500
Competition math problems
- OpenAI o3-mini (Low): 97.3%Top
- Kimi K2 0711 Fast: 97.1%
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- OpenAI o3-mini (Low): 6.8%
- Kimi K2 0711 Fast: 15.9%Top
τ²-Bench Telecom
Tool use in a customer-support simulation
- OpenAI o3-mini (Low): 28.7%
- Kimi K2 0711 Fast: 61.1%Top
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- OpenAI o3-mini (Low): —
- Kimi K2 0711 Fast: 53.0%
Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis
Developers
Use it through the API
Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.
curl https://www.noumen.xyz/api/v1/chat/completions \
-H "Authorization: Bearer $NOUMEN_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "openai/o3-mini-low",
"reasoning_effort": "medium",
"messages": [{ "role": "user", "content": "Explain this stack trace." }]
}'import os
from openai import OpenAI
client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
model="openai/o3-mini-low",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)OpenAI
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