atomic.chat ✓

@atomic_chat_hq · California, USA · joined 26 Mar 2026

Local AI chat and Inference Engine. Enhanced by TurboQuant. Team: @gladkos @skinbagwbones @AlexFromAtomic @danyurkin @quantizedden

15 996Followers

65Following

672Posts total

1.3MViews on collected posts

โพสต์ล่าสุด

atomic.chat ✓@atomic_chat_hq17 Sep

@atomic_chat_hq @typesafeai All i see is new drone warfare capabilities 474 views · 7 likes · 0 reposts · 1 replies Open on X →

atomic.chat ✓@atomic_chat_hq17 Sep

@atomic_chat_hq @typesafeai Jev just solved the nuclear threat 561 views · 6 likes · 0 reposts · 1 replies Open on X →

atomic.chat ✓@atomic_chat_hq17 Sep

@atomic_chat_hq @typesafeai I wish it was actually running local. Seems like other labs should be able to replicate this pretty quickly. 746 views · 11 likes · 0 reposts · 1 replies Open on X →

atomic.chat ✓@atomic_chat_hq17 Sep

Jev v1.13 dodges rockets with probability calculation 🚀 @typesafeai's new non-LLM model returns decisions instead of text so we had it calculate a safe tile every 330 ms while rockets fell and it survived 25 of 26 for under a cent Run Jev via API -> https://t.co/RbcCOIgVkj http

0:39

54.1K views · 521 likes · 35 reposts · 11 replies Open on X →

atomic.chat ✓@atomic_chat_hq8 Sep

Run Ling 3.0 flash VL Atomic Quants via Atomic Chat 🌀 @AntLingAGI gave ling 3.0 flash a vision upgrade, now it can view and analyze images, so we passed it a flappy bird picture to re-create the game GGUF: https://t.co/1GHnMTkiSX Run AI models locally: https://t.co/RbcCOIgVkj h

0:28

1K views · 8 likes · 0 reposts · 2 replies Open on X →

atomic.chat ✓@atomic_chat_hq8 Sep

Today, we're open-sourcing Ling-3.0-flash-VL in BF16 and FP8. FP4 and INT4 are coming soon. Beyond visual recognition, it follows visual cues to: - Understand images, video, docs & UIs - Reason, search & verify - Use tools, check results & deliver https://t.co/kImBAjbdV9

274.1K views · 267 likes · 35 reposts · 16 replies Open on X →

atomic.chat ✓@atomic_chat_hq7 Sep

Running MiniCPM5-2B locally on a 16GB MacBook 💻 It beats Qwen3.5-4B on benchmarks, so we asked it to find recent AI news, it called web search, pulled back 10 results and summarized the key developments inside Atomic Chat Run local models via https://t.co/RbcCOIgVkj https:

0:19

54.6K views · 410 likes · 28 reposts · 16 replies Open on X →

atomic.chat ✓@atomic_chat_hq7 Sep

GPT-6 Astra smokes Claude Fable 5.1 in Blender 💨 We compared GPT-6 Astra and Fable 5.1 on a Porsche 911 GT3 RS build and the difference is visible from the very first shot Output: Astra: $132.03 • 2.58 hours Fable: $114.41 • 2.56 hours Astra's model is not only more https://

0:32

124.6K views · 257 likes · 13 reposts · 17 replies Open on X →

atomic.chat ✓@atomic_chat_hq3 Sep

Running Ling 3.0 flash Fin AD quants via Atomic Chat 🌀 It analyzed an .xlsx expenses report and built a markdown table which contains a short per-month summary of all spendings, everything locally GGUF quants: https://t.co/V0WqR3Ql5N https://t.co/SQI3aGxMX0

0:16

8.4K views · 23 likes · 2 reposts · 5 replies Open on X →

atomic.chat ✓@atomic_chat_hq3 Sep

We’re open-sourcing Ling-3.0-flash-Fin, a finance-enhanced model for real-world workflows, and FinFIRST, an expert-built benchmark for financial search agents. Two open releases, one goal: making financial AI more accessible and verifiable. https://t.co/VL1FqGuhiq

632.8K views · 357 likes · 74 reposts · 57 replies Open on X →

atomic.chat ✓@atomic_chat_hq26 Aug

Running 1-bit Qwen 3.8 Flash Next (79GB) on a MacBook Pro M5 Max 64GB at 30 tok/s 🤯 It ran a 8-minute agent loop with 6 web searches, 3 Python runs and 5 sourced tables. Run local models via Atomic Chat! GGUF: https://t.co/IrKMSfMJDt https://t.co/gT2ys7Z8iJ

1:14

101.8K views · 204 likes · 22 reposts · 26 replies Open on X →

เทียบกับบัญชีขนาดเดียวกัน

11 โพสต์จาก 90 วันที่ผ่านมา เทียบกับช่วง 10K–100K ผู้ติดตาม แสดงในวงกว้าง แต่มีผู้ชมตอบสนองน้อย.

ยอดดูมัธยฐาน54 052บัญชีนี้924ค่ามัธยฐานของ 10K–100K

การเข้าถึง, %337.91%บัญชีนี้3.62%ค่ามัธยฐานของ 10K–100K

การมีส่วนร่วม, %0.84%บัญชีนี้1.52%ค่ามัธยฐานของ 10K–100K

ตัวชี้วัด	บัญชีนี้	ค่ามัธยฐานของ 10K–100K	อัตราส่วน
ยอดดูมัธยฐานต่อโพสต์	54 052	924	58.5×
การเข้าถึง (ยอดดู ÷ ผู้ติดตาม)	3.4× audience	3.62%	93.3×
อัตราการมีส่วนร่วม	0.84%	1.52%	0.56×

บัญชีอื่นในช่วงนี้ → เปรียบเทียบกับบัญชีอื่น → ค่าอ้างอิงเหล่านี้คำนวณอย่างไร →

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

101.8K26 Aug

632.8K3 Sep

8.4K

124.6K7 Sep

54.6K

274.1K8 Sep

54.1K17 Sep

746

561

474

Last 11 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.26%26 Aug

0.08%3 Sep

0.40%

0.24%7 Sep

0.84%

0.12%8 Sep

1.00%

1.07%17 Sep

1.61%

1.25%

1.69%

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

What the audience does

Likes59.9%2 071 in total

Reposts6.0%209 in total

Replies4.4%153 in total

Quotes2.7%95 in total

Bookmarks26.9%931 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.

บัญชีที่คล้ายกัน

Frequently asked questions about @atomic_chat_hq

How many followers does @atomic_chat_hq have?

15 996 followers.

How many posts has @atomic_chat_hq published?

672 posts.

How do posts by @atomic_chat_hq perform?

Collected posts: 11. Views: 1 252 997. Likes: 2 071.