Thinking Machines launches Inkling 2 Small, with Apache 2.0 weights promised next week
Inkling 2 Small is a 594B-parameter mixture-of-experts model with 17B active parameters, image input and adjustable effort. It is on Tinker now with closed weights, and Thinking Machines says the full weights come under Apache 2.0 after external safety testing.
Thinking Machines Lab released Inkling 2 Small on Nov 5. You can try it in the Tinker Playground today, and sample or fine-tune it on Tinker. Checkpoints become downloadable when the weights are released, which the company says it intends to do next week once red-teaming is done.
The company reports a score of 31 on the Artificial Analysis Intelligence Index. On coding, its own table shows 25.4% on FrontierCode v2.0, 72.1% on DeepSWE v1.1 and 86.3% on SWE-bench Pro v2 (Hard). It is second-highest in those rows, behind DeepSeek V4.1 Flash on the first two and Kimi K3 on the third. On vision and several finance benchmarks it leads the open-weight models it compared against. These are the lab's own numbers.
In one demo, the model ran an autoresearch task on its own: it trained Qwen3.5-4B on Tinker to forecast time series, spent about 4.5 hours and $426 of a $500 budget, and more than doubled the forecasting score. The post also admits limits: it isn't the most succinct writer, doesn't always pick the best tools in repos with many skills, and the chat experience is less polished.
Why it matters for builders
A 17B-active model with image input and an Apache 2.0 license would be one you can host yourself and fine-tune without a usage agreement. The license is a promise until the weights actually land, so don't plan around it before then.
Try this
Open the Tinker Playground and paste in one real task from your backlog, ideally one with a screenshot. Run it again with the same prompt when the weights are released next week, and compare.
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