Thinking Machines ✓

@thinkymachines · joined 17 Feb 2025

Thinking, beeping, and booping. @tinkerapi

182 221Followers

1Following

70Posts total

850.6KViews on collected posts

Against accounts of the same size

4 posts from the last 90 days, next to the 100K–1M follower range. shown widely, but few of those viewers react.

Median views219 383this account21 891median for 100K–1M

Reach, %120.39%this account6.81%median for 100K–1M

Engagement, %0.69%this account1.14%median for 100K–1M

Metric	This account	Median for 100K–1M	Ratio
Median views per post	219 383	21 891	10.0×
Reach (views ÷ followers)	120.39%	6.81%	17.7×
Engagement rate	0.69%	1.14%	0.61×

Others in this range → Compare with another account → How these benchmarks are built →

Growth & engagement

How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.

Views per post

343.2K21 Aug

239K24 Aug

199.7K27 Aug

68.7K

Last 4 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.68%21 Aug

0.71%24 Aug

0.21%27 Aug

0.80%

Reactions — likes, reposts, replies and quotes — divided by views. Median for 100K–1M accounts is 1.14%.

What the audience does

Likes68.8%4 461 in total

Reposts5.2%340 in total

Replies1.7%112 in total

Quotes1.2%79 in total

Bookmarks23.0%1 491 in total

Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.

The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.

Latest posts

Cleaning data and aligning the reward function for RLVR takes expertise and effort upfront, but the result is a model that's state-of-the-art on a complex task. Guest post by researchers at UIUC and Bridgewater, in collaboration with our team. https://t.co/1UHTXFcZnW 68.7K views · 493 likes · 40 reposts · 10 replies 27 Aug 2026 LLMs with scaffolds have lagged on text-to-SQL, a task that relies on human judgment. By folding expert judgment into every part of RLVR on Tinker, @maxYuxuanZhu and @ddkang (UIUC and Bridgwater) trained the first text-to-SQL model to beat the human mark. https://t.co/JxEQC31rX9 199.7K views · 361 likes · 46 reposts · 4 replies 27 Aug 2026 Today, we are launching Tinker grants of up to $50,000 in credits for safety research on open-weight models. We share some project ideas that excite us below; if you’re working on a safety project that could be accelerated by additional Tinker credits, we want to hear from you! 239K views · 1.5K likes · 128 reposts · 42 replies 24 Aug 2026 We want to improve Inkling’s agentic performance. To help us understand its real-world behavior, we are making it available for free on OpenRouter (only with agentic harnesses) for the next few weeks, starting now. We’ll use the data, disassociated from accounts, to better it. 343.2K views · 2.1K likes · 126 reposts · 56 replies 21 Aug 2026