Thinking Machines: Inkling
Analysis Summary
Thinking Machines Inkling is a multimodal model with a one-million-token context window, vision and audio input, tool use, and function calling. Its coding result is a clear strength, while the general reasoning result supports useful professional work without placing it in the frontier tier. Pricing is moderate for a model with this context and modality range.
It suits software assistance, long-document review, multimodal content operations, and structured client workflows that benefit from external tools. The lower agentic result suggests caution with long chains of autonomous actions, ambiguous planning, and systems that must recover independently from failures.
Inkling is a credible secondary model for teams needing coding and multimodal coverage. Use explicit validation and human review for consequential outputs, especially where the workflow depends on sustained autonomous execution.
Assessed September 7, 2026
Editorial notes
Inkling combines strong coding, multimodal input, a million-token context, and tool-enabled workflows at moderate pricing. Its agentic result is less convincing, so complex autonomous operations need supervision.
Rankings consider pricing, capabilities, benchmarks, and real-world applicability and are refreshed as new models launch. Feedback?
DFO Verdict
Inkling combines strong coding, multimodal input, a million-token context, and tool-enabled workflows at moderate pricing. Its agentic result is less convincing, so complex autonomous operations need supervision.
How Thinking Machines: Inkling compares
Thinking Machines: Inkling ranks #96 of 438 AI models we track for overall intelligence, #70 of 210 for coding, #73 of 192 for agentic tasks. Its 1M-token context window is larger than 94% of the models we list. At $1.00 per million input tokens it is cheaper than 27% 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 business fit. 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 | $1.00 | $0.001000 |
| Output | $4.05 | $0.004050 |
What would Thinking Machines: Inkling cost your business?
Pick the job that looks most like yours, then fine-tune with the sliders. Estimates update live.
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 for the hard ones. Most clients cut their estimate by 60-80%.
Talk to our teamAbout Thinking Machines: Inkling
Inkling is an open-weight multimodal mixture-of-experts model from Thinking Machines Lab, with 41B active parameters out of 975B total. It is designed for general-purpose reasoning, coding, agentic and tool-use systems,..
Frequently asked questions about Thinking Machines: Inkling
How much does Thinking Machines: Inkling cost?
Thinking Machines: Inkling costs $1.00 per million input tokens and $4.05 per million output tokens.
What is the context window of Thinking Machines: Inkling?
Thinking Machines: Inkling has a context window of 1,048,576 tokens (1M).
Is Thinking Machines: Inkling good for coding?
On our coding benchmark index, Thinking Machines: Inkling ranks #70 of 210 models, placing it in the broader range of the field for code generation and debugging.
What can Thinking Machines: Inkling do?
Thinking Machines: Inkling supports image/vision input, tool use, and function calling.
Who created Thinking Machines: Inkling?
Thinking Machines: Inkling is developed by Thinking Machines and was released on July 17, 2026.