o1
Active76.3StrongReasoning-focused model that thinks before answering.
Intelligence Index
76.3/ 100
Strongweighted across 4 benchmarks
- Math
- 89.0
- Reasoning
- 78.0
- Coding
- 61.7
Computed as the mean of per-category averages across MMLU, GPQA, SWE-bench, HumanEval, MATH, GSM8K, AIME, Aider Polyglot and more. See each benchmark for methodology.
Overview
The o1 model is trained to spend additional inference-time compute on internal reasoning before producing a response. Strong on math, coding, and science benchmarks.
History
o1 became available via the OpenAI API on 2024-12-17.
Training & availability
Training data has a knowledge cutoff of 2023-10-31 — information about events after that date is unlikely to appear in the model's responses. OpenAI has not released the underlying model weights — access is via their hosted API only.
Capabilities
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Context window: 200K tokens.
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Max output: 100K tokens.
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Input modalities: text, image.
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Intelligence Index: 76.2/100.
Strongest categories: Math (89), Reasoning (78), Coding (62).
Recommended for: vision, math, agentic, long-context, reasoning.
Limitations
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The knowledge cutoff is 30 months old — this model will not know about recent events, releases, or API changes.
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At $60.00/1M output tokens, this is in the premium tier — verify cost-per-value for high-volume workloads.
Pricing
- Input: $15.0000 per 1M tokens
- Output: $60.0000 per 1M tokens
Use the cost calculator above to estimate monthly spend for your workload.
Quick start
Minimal example using the openai API. Copy, paste, replace the key.
from openai import OpenAI
client = OpenAI(api_key="sk-...")
resp = client.chat.completions.create(
model="o1",
messages=[{"role": "user", "content": "Explain quantum computing in one sentence."}],
)
print(resp.choices[0].message.content)Cost calculator
Estimate your monthly bill. Presets are typical workload sizes.
Benchmarks
| Benchmark | Score | Source |
|---|---|---|
| AIME 2024Math | 83.3% accuracy | Self-reported OpenAI o1 system card |
| Aider PolyglotCoding | 61.7% pass@2 | Third-party Papers With Code |
| GPQA DiamondReasoning | 78% accuracy | Self-reported OpenAI o1 system card |
Integrations & tooling support
- Tool calling
- Supported
- Structured outputs
- Supported
Price vs quality
Mid-tier performance at frontier pricing.
- Quality percentile
- 72.3%
- Effective price
- $48.75/1M
- Pricing breakdown
- $15/1M in
$60/1M out
Community ratings
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Comments
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