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Thinkingmachines

Inkling Small

Inkling Small is the smaller model in the Inkling family at 276 billion total parameters and 12 billion active. It matches or beats Inkling on many coding, reasoning, and tool-use evaluations, reasons natively over images and audio, and supports a context window of 1M tokens. Your use is subject to Thinkingmachines's Terms & Privacy Policies.

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


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

  • How does Inkling Small differ from Inkling?

    Size and knowledge. Inkling Small has 276 billion total parameters and 12 billion active, against 975 billion and 41 billion for Inkling. Inkling Small matches or beats Inkling on coding, reasoning, and tool-use evaluations, and trails it on factual recall, scoring 20.6% on SimpleQA Verified against 43.9%.

  • How did Inkling Small score on coding benchmarks?

    80.2% on SWE-bench Verified, 55.9% on SWE-bench Pro (public), 64.7% on Terminal-Bench 2.1, and 48.7% on SciCode. Each result sits at or above Inkling on the same evaluation.

  • What input types does Inkling Small accept?

    Text, images, and audio, with text output. Images are encoded through a hierarchical patch encoder and audio through discrete token encoding, and the decoder processes all three together.

  • How does Inkling Small handle documents and charts?

    Inkling Small can crop, zoom, and inspect images programmatically, which helps when the detail that answers a question is small. Inkling Small scores 77.4% on CharXiv reasoning questions, or 81.3% with a Python tool, and 74.0% on MMMU Pro.

  • How does controllable thinking effort work?

    You set effort per request, from minimal to maximum. Higher effort spends more thinking tokens and raises scores on hard tasks; lower effort cuts cost and latency. Published benchmark results are reported at maximum effort.

  • Can I use Inkling Small in a coding agent?

    Yes. Run vercel ai-gateway coding-agents setup to connect your agents to AI Gateway, then select thinkingmachines/inkling-small in the agent's model configuration. See the coding agents guide at https://vercel.com/docs/ai-gateway/coding-agents.

  • Does AI Gateway support Zero Data Retention for Inkling Small?

    Yes, Zero Data Retention is available for this model. Turn it on team-wide from the dashboard or per request with zeroDataRetention: true. Zero Data Retention is offered on a per-provider basis. See https://vercel.com/docs/ai-gateway/capabilities/zdr for details.

  • Are the weights for Inkling Small open?

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

  • How do I call Inkling Small through AI Gateway?

    Set the model to thinkingmachines/inkling-small 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, deepinfra, togetherai.

  • What does Inkling Small cost?

    Current rates appear in the pricing panel on this page. AI Gateway mirrors provider pricing with no markup and adds no platform fee on inference, including on Bring Your Own Key requests.