Phala ✓

@PhalaNetwork · San Francisco, CA · joined 27 Aug 2019

Empowering 10,000 builders and companies to build scalable, private, and safe intelligence.

141 081Followers

836Following

6 334Posts total

68KViews on collected posts

Against accounts of the same size

10 posts from the last 90 days, next to the 100K–1M follower range. right around the median for its follower range.

Median views2 714this account4 963median for 100K–1M

Reach, %1.92%this account2.08%median for 100K–1M

Engagement, %1.39%this account1.47%median for 100K–1M

Metric	This account	Median for 100K–1M	Ratio
Median views per post	2 714	4 963	0.55×
Reach (views ÷ followers)	1.92%	2.08%	0.92×
Engagement rate	1.39%	1.47%	0.95×

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

42.1K25 Jun

1.7K

24623 Jul

4.9K31 Aug

6.3K1 Sep

3.8K4 Sep

3.5K

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

0.47%25 Jun

1.55%

1.20%

1.42%

1.37%

0.81%23 Jul

2.39%31 Aug

1.18%1 Sep

1.53%4 Sep

2.20%

Reactions — likes, reposts, replies and quotes — divided by views. Median for 100K–1M accounts is 1.47%.

What the audience does

Likes81.2%518 in total

Reposts9.9%63 in total

Replies4.7%30 in total

Quotes1.9%12 in total

Bookmarks2.4%15 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

Phala Confidential AI: 38.86 billion billed input + output tokens over the past 24 hours. Top models: 1. DeepSeek V4 Flash — 28.59% 2. GLM-5.2 — 13.61% 3. GLM-5.3 — 9.53% Explore #1: https://t.co/HFFGd77pc1 TEE-backed AI infrastructure. https://t.co/LJZU5O8oer 3.5K views · 66 likes · 6 reposts · 4 replies 04 Sep 2026 ViMax transforms ideas, novels, or scripts into multi-scene video plans and final generated clips. The Phala template uses a source_verifier runtime. https://t.co/vRJiogOCEI https://t.co/ELlLUmPw2u 3.8K views · 53 likes · 4 reposts · 1 replies 04 Sep 2026 39.81 billion tokens powered Confidential AI on Phala over the past 24 hours. Top models: 1. DeepSeek V4 Flash — 29.90% 2. GLM-5.2 — 17.19% 3. Kimi K3 — 14.98% Explore #1: https://t.co/HFFGd77pc1 TEE-backed AI infrastructure. https://t.co/9TzuFhBlgY 6.3K views · 64 likes · 8 reposts · 0 replies 01 Sep 2026 Phala Confidential AI network token volume: 42.98 billion billed input + output tokens over the past 24 hours. Top models 1. Kimi K3 — 35.48% 2. DeepSeek V4 Flash — 22.56% 3. Qwen3.5 397B A17B — 8.50% https://t.co/eHSPzOFiwk TEE-backed AI infrastructure. https://t.co/3IiBcsdve 4.9K views · 98 likes · 14 reposts · 6 replies 31 Aug 2026 @PhalaNetwork Why aren't these amounts quoted in $PHA? https://t.co/YFigTr3Crf 246 views · 2 likes · 0 reposts · 0 replies 23 Jul 2026 For builders, this points to the next bar for private AI infra: scale Kubernetes workloads while preserving hardware-backed identity per Pod. Full writeup: https://t.co/KdtOc2Vo75 1.7K views · 22 likes · 1 reposts · 0 replies 25 Jun 2026 The paper introduces dstack-capsule: Pod-level attestation, privilege fuse, multi-layer sandbox, and a Kubernetes implementation on Intel TDX + Sysbox. dstack: https://t.co/bzMCR6DXVw https://t.co/WKxzSCSpQA 2K views · 25 likes · 2 reposts · 1 replies 25 Jun 2026 The design uses a two-layer model: • static platform measurements frozen in RTMR[3] • dynamic Pod identity carried in TDX Quote report_data A verifier can check the Pod before it receives secrets, data, or service access. https://t.co/pzlNl8pnxa 1.7K views · 19 likes · 1 reposts · 1 replies 25 Jun 2026 What changes at Pod level: attestation moves from “this VM looks right” to “this exact Kubernetes Pod is running the expected image, on measured hardware, with the expected cluster identity.” That is the trust layer cloud-native AI needs. https://t.co/ZQmDVR7Tf2 1.7K views · 23 likes · 2 reposts · 1 replies 25 Jun 2026 OPPO × Phala published a joint paper on Kubernetes Pod-level remote attestation for confidential AI. Goal: prove the hardware, container image, and Pod identity before sensitive data enters the workload. https://t.co/jQjC6DFsS0 https://t.co/fX68Ij8ECm 42.1K views · 146 likes · 25 reposts · 16 replies 25 Jun 2026