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Thinkingmachines

Inkling

Inkling is an open-weights multimodal Mixture-of-Experts model that reasons over text, images, and audio. It supports controllable thinking effort and a context window of 256K tokens. Call Inkling on AI Gateway with thinkingmachines/inkling. Your use is subject to Thinkingmachines's Terms & Privacy Policies.

ReasoningTool UseVision (Image)File Input
Use with AI GatewayView docs
import { streamText } from 'ai'


const result = streamText({
  model: 'thinkingmachines/inkling',
  prompt: 'Why is the sky blue?'
})
Read docs
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Frequently Asked Questions

  • What is Inkling designed for?

    Broad generalist use. Inkling covers agentic work, reasoning, coding, instruction following, factuality, vision, and audio, rather than optimizing narrowly for one domain. Thinkingmachines positions that breadth as the reason to pick it.

  • What input types does Inkling accept?

    Text, images, and audio, with text output. Images work best with each dimension between 40px and 4096px, and audio should be WAV sampled at 16kHz. All three modalities are processed jointly by the same decoder.

  • How does controllable thinking effort work in Inkling?

    You set an effort level per request. Higher effort spends more thinking tokens and raises scores on hard tasks; lower effort returns answers sooner. Published benchmark results for Inkling are reported at maximum effort.

  • How does Inkling compare to Inkling Small?

    Inkling Small is roughly a quarter of the size and matches or beats Inkling on many coding, reasoning, and tool-use evaluations. Inkling stays ahead on world knowledge, scoring 43.9% on SimpleQA Verified against 20.6%, and posts slightly higher audio scores.

  • How did Inkling score on agentic coding benchmarks?

    77.6% on SWE-bench Verified, 54.3% on SWE-bench Pro (public), and 63.8% on Terminal-Bench 2.1, all at maximum effort. On general agentic evaluations, Inkling scores 76.0% on MCP Atlas and 45.5% on Toolathlon Verified.

  • How good is Inkling at audio and vision tasks?

    Audio is among its stronger areas, with 91.4% on VoiceBench, 77.2% on MMAU, and 56.6% on Audio MC. On vision, Inkling scores 73.5% on MMMU Pro and 78.1% on CharXiv reasoning questions, or 82.0% when it uses a Python tool to inspect the image.

  • What context window does Inkling support?

    A context window of 256K tokens. That covers long documents, extended tool-calling sessions, and conversations that mix text with images and audio.

  • Are the weights for Inkling open?

    Yes. Thinkingmachines released Inkling with open weights under the Apache 2.0 license, which permits commercial use and modification.

  • Does AI Gateway support Zero Data Retention for Inkling?

    Yes, Zero Data Retention is available for this model. Zero Data Retention is offered on a per-provider basis. See https://vercel.com/docs/ai-gateway/capabilities/zdr for details.

  • How do I call Inkling through AI Gateway?

    Set the model to thinkingmachines/inkling in the AI SDK, Chat Completions API, Responses API, Messages API, or other API formats, from TypeScript or Python. AI Gateway handles authentication, retries, and failover across baseten, togetherai.