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X @cerebras

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👋 Unclaimed listing — auto-generated from public data; rates are estimates, not set by the creator. 🔒 Paid proposals held safely in escrow — released only when the work's approved.

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Auto-generated from Cerebras’s publicly available X info.

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Followers

74.6K

Posts

2.8K

Following

269

Account age

10 yrs

💰 Suggested sponsorship rate

🎁 Free analysisfor Cerebras

🕵️Fake Followers CheckReal-audience % & bot risk→ 📊Engagement rateBenchmarked vs. peers→ 💰What they chargeFair sponsored-post price→

Known for

1.5M views The Fastest AI Just Got Faster. Meet CS-4.

Connecting the dies and working around defects were fundamental challenges for wafer-scale computing. Making it work also came down to power, cooling, and reliability.

@seanlie explains how those lessons are shaping @cerebras’ approach to stacking DRAM.

From @seanlie’s

12.2K views Connecting the dies and working around defects were fundamental challenges for wafer-scale computing. Making it work also came down to power, cooling, and reliability. @seanlie explains how those lessons are shaping @cerebras’ approach to stacking DRAM. From @seanlie’s

The first @cerebras chip had to prove that wafer-scale computing could work. The question now is what that speed makes possible.

@seanlie reflects on that shift, and why combining frontier-model intelligence with fast inference opens up a different set of applications.

From

11.6K views The first @cerebras chip had to prove that wafer-scale computing could work. The question now is what that speed makes possible. @seanlie reflects on that shift, and why combining frontier-model intelligence with fast inference opens up a different set of applications. From

AI is already helping write the code that runs on @cerebras hardware.

@seanlie describes how the team uses models running on its own systems to generate code that helps bring more models onto those same systems.

7.6K views AI is already helping write the code that runs on @cerebras hardware. @seanlie describes how the team uses models running on its own systems to generate code that helps bring more models onto those same systems.

📊 Post performance

📊 Activity & format

Posting cadence

1.9 / week

A lower-frequency account — each post lands with more weight.

Content mix

Mostly video

Recent: 6 video · 0 image · 2 text.

Follower / following

277×

Follows 269 back. A strong ratio — an audience that follows them, not a follow-for-follow network.

Verification

✓ X Premium

A paid X Premium (Blue) verified account.

Recent posts

View on X ↗

▶ 🔥 Top post The Fastest AI Just Got Faster. Meet CS-4. 1.5M❤ 4.3K🔁 520

▶ A new chip needs a system that can power it, cool it, and support what comes next. @seanlie walks through the modular Nexus platform behind @cerebras CS-4, and how designing it alongside the next wafer-scale chip creates room for further … 1.6K❤ 12🔁 1 Codebase analysis in seconds! 7.3K❤ 71🔁 10

▶ The first @cerebras chip had to prove that wafer-scale computing could work. The question now is what that speed makes possible. @seanlie reflects on that shift, and why combining frontier-model intelligence with fast inference opens up a… 11.6K❤ 72🔁 9 Cerebras makes Qwen 3.8 27B goes brrrrr 💨 29.7K❤ 333🔁 22

▶ Radical innovation or "a long hard slog" as @andrewdfeldman likes to put it. 6.4K❤ 22🔁 5

▶ Connecting the dies and working around defects were fundamental challenges for wafer-scale computing. Making it work also came down to power, cooling, and reliability. @seanlie explains how those lessons are shaping @cerebras’ approach to… 12.2K❤ 59🔁 12

▶ AI is already helping write the code that runs on @cerebras hardware. @seanlie describes how the team uses models running on its own systems to generate code that helps bring more models onto those same systems. 7.6K❤ 76🔁 11

💡 Facts

🗓️Joined X in 2016 — 10 years ago.

👁️Averages 7.6K views per post.

📤Posts about 1.9× per week.

💬0.93% engagement rate.

🏅Earned the 10K Followers for passing 10K followers.

🕵️ Fake follower check

Estimated

46/100

Fair Credibility score

69%

Mixed Real audience

Medium Fake-follower risk

High Data confidence

Est. 69% real, active audience · Medium fake-follower risk.
Low engagement (~0.1× of followers engage each post) — a sign of an inflated or inactive audience.
Organic base — far more followers than accounts it follows.
Verified account.
Established account (10+ years old).
0.93% engagement — below the ~8.8% typical for this size.

Heuristic estimate from engagement, follower ratios, account age & growth — a screening signal, not a guarantee.

About

The world's fastest AI inference and training. Try the latest open models at: https://inference.cerebras.ai/

📸 Gallery

🔀 Audience overlap

Estimated

Estimated shared audience with similar creators — useful for avoiding overlap (or doubling down) when planning a campaign.

Elsevier | Scopus 18%

Helius 18%

Andra 14%

STRAPPED! 10%

GE HealthCare 10%

The U.S. Capitol Police 10%

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Frequently asked questions

How much does Cerebras charge for a sponsorship?

Cerebras hasn't published fixed prices yet. Send a proposal through SocialDB and agree terms directly — your payment is held in escrow until the work is approved.

How do I contact Cerebras for a brand deal or collaboration?

Send a paid deal or collab request right here on SocialDB — we notify Cerebras, and once they accept, your payment is held safely in escrow and released when the work is approved. You don't need to track down an email.

How many followers does Cerebras have?

Cerebras has 74,560 followers on X.