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thinkingmachines · Open weights

Inkling Thinking

Added Jul 15, 2026Open weights

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Use in the app

The thinking version of Thinking Machines' 975B-parameter open-weights Mixture-of-Experts generalist with 41B active parameters. It reasons natively over text, images, and audio, and is built for agentic coding, tool use, detailed instruction following, long-context work, and controllable thinking effort.

  • Reasoning
  • Tools
  • Vision
  • Structured output
  • Audio input
Input
Text, Images, Audio
Output
Text
Reasoning effort
minimal · low · medium · high · xhigh
Discovery tier
Open weights

Pricing

USD per 1M tokens
Input
$1.00
Output
$4.05
Cache read
$0.17

Reference prices as published by the model provider. API example

Specifications

Context window
1M
Max output
32.8K
Average output (7 days)
1.2K tokens
Longer than 76% of 465 models

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TryDeepSeek V4.1 Flash 1017Tencent Hy3Claude Sonnet 4.6All 3

Public evaluations

Benchmarks

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

Intelligence Index

25.0

Tested at xhigh reasoning effort

Better than 61% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Coding Index

    52.1

    Composite of the coding evaluations

    Better than 50% of 168 scored models

Agentic work

  • AutomationBench-AA

    5.0%

    Workflow automation, penalized for guardrail violations

    Better than 30% of 173 scored models

  • AutomationBench-AA tasks completed

    0.3%

    Workflows finished end to end without a guardrail violation

    Better than 19% of 173 scored models

  • Harvey LAB-AAv1.1

    0.0%

    Legal tasks passed in full, with no material hallucination

    Better than 0% of 29 scored models

  • AA-Briefcasev1.1

    832 Elo

    Agentic knowledge work, rated head to head

    Better than 31% of 166 scored models

  • GDPval-AAv2.1

    1,072 Elo

    Economically valuable occupational tasks, rated head to head

    Better than 43% of 187 scored models

Document reasoning

  • GDP.pdf

    12.8%

    Professional reasoning over PDF documents, all-pass rate

    Better than 56% of 171 scored models

  • AA-LCRv1.1

    77.3%

    Reasoning across long documents

    Better than 63% of 309 scored models

  • MLCR-AA

    6.1%

    Long-context reasoning over medical records

    Better than 23% of 121 scored models

Reasoning and knowledge

  • Humanity’s Last Exam

    31.9%

    Expert-level questions across academic fields

    Better than 65% of 323 scored models

  • GPQA Diamond

    87.2%

    Graduate-level science questions

    Better than 69% of 291 scored models

Coding

  • Terminal-Benchv4.0

    1.0%

    Practical software engineering in a terminal

    Better than 37% of 171 scored models

  • SciCode

    47.0%

    Scientific computing in Python

    Better than 38% of 174 scored models

Legacy evaluations

  • AA-LCR (unversioned)

    77.3%

    Long-context reasoning, earlier grading

    Better than 63% of 309 scored models

Scores from Artificial Analysis, updated Oct 26, 2026. Inkling Thinking was tested at xhigh reasoning effort; compare scores measured at the same effort.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": "thinkingmachines/inkling:thinking",
    "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="thinkingmachines/inkling:thinking",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

thinkingmachines

Other thinkingmachines models, starting with the same family.