Thinking Machines releases Inkling 2 Small and says Apache 2.0 weights follow next week

Inkling 2 Small is a mixture-of-experts model with 594B total parameters and 17B active, with image input and variable effort. It is available now on the company's Tinker service with closed weights. The company says it will release full weights under Apache 2.0 next week, after external safety testing and red-teaming. It says the model was trained with reinforcement learning on hundreds of thousands of long-horizon coding tasks across several agent harnesses and context-compaction strategies.

On the coding rows of the company's own benchmark table, Inkling 2 Small is second on all three: FrontierCode v2.0 at 25.4 percent, DeepSWE v1.1 at 72.1 percent and SWE-Bench Pro v2 (Hard) at 86.3 percent. DeepSeek-V4.1-Flash-1017 leads the first two and Kimi K3 leads the third. The company also reports that the model trained Qwen3.5-4B on Tinker to forecast time series, working autonomously for 4.5 hours at a cost of $426 in Tinker spend, and "more than doubled" its forecasting score.

Every figure here is the company's. We read the announcement page and did not find an independent evaluation, and the weights were not yet downloadable when we read it.

Why it matters: The practical test comes next week, when teams can run the model in their own harnesses if the weights ship as stated. Until then the coding results are the lab's own and we have not seen an independent run.