Thinking Machines: Inkling Small
Analysis Summary
Thinking Machines: Inkling Small pairs a general intelligence level suited to routine professional reasoning with coding capability that is considerably stronger than its broader reasoning profile. A 1M-token context window supports large documents and codebases, while vision, audio input, tool use, and function calling broaden the range of production tasks it can handle.
For Design for Online, the model fits software assistance, structured content production, SEO workflows, document transformation, and multimodal briefs. Its $0.45 input and $1.20 output pricing supports regular API use without placing it in the budget tier. The main limitation is agentic capability, which makes it less suitable for complex autonomous task loops than its coding results suggest.
Adopt it as a practical coding and content workhorse where long context and multimodal input matter, while reserving more agent-focused models for open-ended execution.
Assessed September 7, 2026
Editorial notes
Inkling Small combines good general reasoning with world-class coding, a 1M-token context, vision, audio input, and tool calling at moderate pricing. Its weaker agentic performance limits autonomous workflow use.
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DFO Verdict
Inkling Small combines good general reasoning with world-class coding, a 1M-token context, vision, audio input, and tool calling at moderate pricing. Its weaker agentic performance limits autonomous workflow use.
How Thinking Machines: Inkling Small compares
Thinking Machines: Inkling Small ranks #91 of 438 AI models we track for overall intelligence, #67 of 210 for coding, #71 of 192 for agentic tasks. Its 1M-token context window is larger than 94% of the models we list. At $0.45 per million input tokens it is cheaper than 39% of comparable models.
Dark bar = input · light bar = output, scaled to the priciest peer.
1M tokens ≈ 8 full-length novels or ~2,500 pages of business documents in a single request.
Strongest on content. The pulled-in intelligence corner is the trade-off, and if the shape matters more than the price, this is your model.
Compare shapes side-by-side →Pricing
| Token Type | Cost per 1M tokens | Cost per 1K tokens |
|---|---|---|
| Input | $0.45 | $0.000450 |
| Output | $1.20 | $0.001200 |
What would Thinking Machines: Inkling Small cost your business?
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A website chatbot handling around 100 customer conversations a day, a few short messages each.
Full calculator with 779 models → Price Calculator
These numbers get smaller with the right architecture.
We route routine calls to cheap models and save Thinking Machines: Inkling Small for the hard ones. Most clients cut their estimate by 60-80%.
Talk to our teamAbout Thinking Machines: Inkling Small
Inkling Small is an open-weight multimodal mixture-of-experts model from Thinking Machines Lab, with 12B active parameters out of 276B total. It is positioned as the smaller, more efficient member of..
Frequently asked questions about Thinking Machines: Inkling Small
How much does Thinking Machines: Inkling Small cost?
Thinking Machines: Inkling Small costs $0.45 per million input tokens and $1.20 per million output tokens.
What is the context window of Thinking Machines: Inkling Small?
Thinking Machines: Inkling Small has a context window of 1,048,576 tokens (1M).
Is Thinking Machines: Inkling Small good for coding?
On our coding benchmark index, Thinking Machines: Inkling Small ranks #67 of 210 models, placing it in the broader range of the field for code generation and debugging.
What can Thinking Machines: Inkling Small do?
Thinking Machines: Inkling Small supports image/vision input, tool use, and function calling.
Who created Thinking Machines: Inkling Small?
Thinking Machines: Inkling Small is developed by Thinking Machines and was released on July 30, 2026.