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OpenAI · Balanced

OpenAI o1

Added Jan 1, 2024

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Use in the app

Useful when tackling complex problems in science, coding, math, and similar fields. Outdated compared to the newer o3 and o4 models.

  • Reasoning
Input
Text
Output
Text
Reasoning effort
low · medium · high
Discovery tier
Balanced

Pricing

USD per 1M tokens
Input
$15.00
Output
$60.00
Cache read
$7.50

Reference prices as published by the model provider. API example

Specifications

Context window
200K
Max output
100K
Average output (7 days)
28 tokens
Longer than 1% of 468 models

Side by side

OpenAI o1 compared

Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.

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OpenAI o1OpenAIThis modelQwen3.6 35B A3B TEEQwenRemove
ProviderOpenAIQwen
Discovery tierBalancedOpen weights
AddedJan 1, 2024Jun 9, 2026
Limits
Context window200K262.14KBest
Max output100K262.14KBest
Average output28 tokens3.9K tokens
Pricing, USD per 1M tokens
Input$15.00$0.20Best
Output$60.00$1.27Best
Cache read$7.50—
Performance
Request success (24h)—99.5%
Benchmark indexes
Intelligence Index15.215.2
Coding Index39.7Best28.1
Capabilities
ReasoningYesNo
Reasoning effortlow, medium, high—

Public evaluations

Benchmarks

Independent evaluation results, with how each score ranks among the models in the Noumen catalog.

  • OpenAI o1
  • Qwen3.6 35B A3B TEE

Intelligence Index

  • OpenAI o115.2
  • Qwen3.6 35B A3B TEE15.2

OpenAI o1: Better than 38% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • OpenAI o1: 39.7Top
    • Qwen3.6 35B A3B TEE: 28.1

Agentic work

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • OpenAI o1: —
    • Qwen3.6 35B A3B TEE: 847 Elo

Document reasoning

  • AA-LCRv1.1

    Reasoning across long documents

    • OpenAI o1: 65.0%Top
    • Qwen3.6 35B A3B TEE: 64.3%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • OpenAI o1: 7.0%
    • Qwen3.6 35B A3B TEE: 13.9%Top

  • GPQA Diamond

    Graduate-level science questions

    • OpenAI o1: 74.7%
    • Qwen3.6 35B A3B TEE: 81.7%Top

  • MMLU-Pro

    Multi-subject knowledge and reasoning

    • OpenAI o1: 84.1%
    • Qwen3.6 35B A3B TEE: —

  • IFBench

    Following precise output instructions

    • OpenAI o1: 70.3%Top
    • Qwen3.6 35B A3B TEE: 36.2%

Coding

  • LiveCodeBench

    Recent competitive programming problems

    • OpenAI o1: 67.9%
    • Qwen3.6 35B A3B TEE: —

Math

  • AIME

    Competition mathematics

    • OpenAI o1: 72.3%
    • Qwen3.6 35B A3B TEE: —

  • MATH-500

    Competition math problems

    • OpenAI o1: 97.0%
    • Qwen3.6 35B A3B TEE: —

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • OpenAI o1: 12.9%
    • Qwen3.6 35B A3B TEE: 25.8%Top

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • OpenAI o1: 62.6%
    • Qwen3.6 35B A3B TEE: 85.1%Top

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • OpenAI o1: 65.0%Top
    • Qwen3.6 35B A3B TEE: 64.3%

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.

Read the quickstart
curl https://www.noumen.xyz/api/v1/chat/completions \
  -H "Authorization: Bearer $NOUMEN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "openai/o1",
    "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/o1",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

OpenAI

Other OpenAI models, starting with the same family.