NOUMENOpen app

OpenAI · Balanced

OpenAI o1

Added Jan 1, 2024

Compare models

Choose up to 3 models to compare.1 of 3 chosen

Loading models…

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 Outdated compared to the newer o3 and o4 models.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.

Compare models

Choose up to 3 models to compare.1 of 3 chosen

Loading models…

OpenAI o1OpenAIThis modelKimi K2 0905MoonshotRemove
ProviderOpenAIMoonshot
Discovery tierBalancedOpen weights
AddedJan 1, 2024Sep 25, 2025
Limits
Context window200K262.14KBest
Max output100K100.35KBest
Average output28 tokens677 tokens
Pricing, USD per 1M tokens
Input$15.00$0.40Best
Output$60.00$1.80Best
Cache read$7.50—
Performance
Throughput—55.2 tok/s
Time to first token—3.2 s
Request success (24h)—100.0%
Benchmark indexes
Intelligence Index15.215.3Best
Coding Index39.7—
Math Index—57.3
Capabilities
ReasoningYesNo
ToolsNoYes
Structured outputNoYes
Reasoning effortlow, medium, high—

Public evaluations

Benchmarks

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

  • OpenAI o1
  • Kimi K2 0905

Intelligence Index

  • OpenAI o115.2
  • Kimi K2 090515.3

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: 39.7
    • Kimi K2 0905: —
  • Math Index

    Composite of the math evaluations

    • OpenAI o1: —
    • Kimi K2 0905: 57.3

Document reasoning

  • AA-LCRv1.1

    Reasoning across long documents

    • OpenAI o1: 65.0%Top
    • Kimi K2 0905: 53.0%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • OpenAI o1: 7.0%Top
    • Kimi K2 0905: 6.4%
  • GPQA Diamond

    Graduate-level science questions

    • OpenAI o1: 74.7%
    • Kimi K2 0905: 76.7%Top
  • MMLU-Pro

    Multi-subject knowledge and reasoning

    • OpenAI o1: 84.1%Top
    • Kimi K2 0905: 81.9%
  • IFBench

    Following precise output instructions

    • OpenAI o1: 70.3%Top
    • Kimi K2 0905: 41.7%

Coding

  • LiveCodeBench

    Recent competitive programming problems

    • OpenAI o1: 67.9%Top
    • Kimi K2 0905: 61.0%

Math

  • AIME 2025

    Competition mathematics, 2025 problems

    • OpenAI o1: —
    • Kimi K2 0905: 57.3%
  • AIME

    Competition mathematics

    • OpenAI o1: 72.3%
    • Kimi K2 0905: —
  • MATH-500

    Competition math problems

    • OpenAI o1: 97.0%
    • Kimi K2 0905: —

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • OpenAI o1: 12.9%
    • Kimi K2 0905: 23.5%Top
  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • OpenAI o1: 62.6%
    • Kimi K2 0905: 73.4%Top
  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • OpenAI o1: 65.0%Top
    • Kimi K2 0905: 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.

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.