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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

Últimas publicaciones

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 Open on X →
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 Open on X →
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 Open on X →
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 Open on X →
@PhalaNetwork Why aren't these amounts quoted in $PHA? https://t.co/YFigTr3Crf 246 views · 2 likes · 0 reposts · 0 replies Open on X →
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 Open on X →
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 Open on X →
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 Open on X →
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 Open on X →
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 Open on X →

Frente a cuentas del mismo tamaño

4 publicaciones de los últimos 90 días, junto al rango de 100K–1M seguidores. llega mucho más allá de su propia audiencia, y esa audiencia responde.

Visualizaciones medianas4 371esta cuenta5 983mediana de 100K–1M
Alcance, %3.10%esta cuenta1.49%mediana de 100K–1M
Interacción, %1.86%esta cuenta0.93%mediana de 100K–1M
MétricaEsta cuentaMediana de 100K–1MProporción
Visualizaciones medianas por publicación4 3715 9830.73×
Alcance (visualizaciones ÷ seguidores)3.10%1.49%2.08×
Tasa de interacción1.86%0.93%2.01×

Otras cuentas de este rango →   Comparar con otra cuenta →   Cómo se construyen estas referencias →

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
1.7K
2K
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 0.93%.

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.

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Frequently asked questions about @PhalaNetwork

How many followers does @PhalaNetwork have?

141 081 followers.

How many posts has @PhalaNetwork published?

6 334 posts.

How do posts by @PhalaNetwork perform?

Collected posts: 10. Views: 67 990. Likes: 518.