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jietang ✓

@jietang · Beijing · joined 14 May 2008

Professor @ Tsinghua, Founder of https://t.co/3IaQ4CI5W3. AGI, LLM. “The value of a man should be seen in what he gives and not in what he is able to receive.”―Einstein

71 216Followers
430Following
529Posts total
2.7MViews on collected posts

Latest posts

Ox Alpha = GLM-5.3 Flash AA = 57 , 1/100 frontier price, Powered by pure Chinese chips. Delivered nearly 20% weekly token share (no. 1) on OpenRouter. Thanks to all for the support. https://t.co/niAGKJgrKQ 164.8K views · 2.6K likes · 187 reposts · 138 replies Open on X →
cool comment: FLOPs were intelligence; parameters were knowledge! 76.6K views · 810 likes · 78 reposts · 29 replies Open on X →
An excellent history of scaling laws from @jietang. In 2020, we explored the limits of sparsity in Switch Transformers by routing each token to only 1 out of 2048 experts (in retrospect, a bold choice). The model had fewer than 3B activated parameters, but 1.6T total parameters 166K views · 650 likes · 53 reposts · 13 replies Open on X →
@jietang Well said. 6.9K views · 38 likes · 0 reposts · 0 replies Open on X →
@jietang Excellent read! Thanks for the insights. It seems Qwen 3.8 27B (and of course the excellent GLM 5.3) are a direct proof of your point. Density still has (had?) room for growth. Vision and speed are likely the next frontier for the GLM family. One question I've had on my 11.4K views · 50 likes · 0 reposts · 2 replies Open on X →
@jietang GLM 5.3’s performance is definitely impressive enough to show you’re right!! 4.2K views · 36 likes · 0 reposts · 0 replies Open on X →
Thoughts About Scaling Law Scaling, but not only of parameters. Every model release now ends with the same question: how many parameters? It isn't a question that can be answered on its own. Parameter count is only meaningful alongside three others — how much data you have, 1.6M views · 6.3K likes · 889 reposts · 236 replies Open on X →
Artificial Analysis Index = 60 57.9K views · 900 likes · 31 reposts · 51 replies Open on X →
GLM-5.3 API is now live. - Built for coding, defensive cybersecurity, and long-horizon agentic tasks - Priced the same as GLM-5.2 - Available via the official API and partner model gateways Get started: https://t.co/3Dpy1tOdaM https://t.co/yBzgPwTFxL 517.6K views · 3.8K likes · 327 reposts · 189 replies Open on X →
GLM-5.3 is coming. focusing on coding. 118.3K views · 1.8K likes · 81 reposts · 111 replies Open on X →

Against accounts of the same size

10 posts from the last 90 days, next to the 10K–100K follower range. shown widely, but few of those viewers react.

Median views97 468this account924median for 10K–100K
Reach, %136.86%this account3.62%median for 10K–100K
Engagement, %0.86%this account1.52%median for 10K–100K
MetricThis accountMedian for 10K–100KRatio
Median views per post97 468924105×
Reach (views ÷ followers)136.86%3.62%37.8×
Engagement rate0.86%1.52%0.57×

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

118.3K14 Aug
517.6K18 Aug
57.9K
1.6M19 Aug
4.2K
11.4K
6.9K
166K20 Aug
76.6K21 Aug
164.8K27 Aug

Last 10 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

1.69%14 Aug
0.87%18 Aug
1.70%
0.48%19 Aug
0.85%
0.46%
0.55%
0.44%20 Aug
1.20%21 Aug
1.79%27 Aug

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.52%.

What the audience does

Likes67.4%16 959 in total
Reposts6.5%1 646 in total
Replies3.1%769 in total
Quotes2.1%540 in total
Bookmarks20.9%5 263 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.

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