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Google Turbo Quant running Locally in Atomic Chat MacBook Air M4 16 GB Model: QWEN3.5-9B Context window: 50000 Summarising 20000 words in just seconds.. You can do 3x larger context window, processing 3x faster than before!

436,886 次观看 • 7 个月前 •via X (Twitter)

39 条评论

atomic.chat 的头像
atomic.chat7 个月前

Download for Mac here:

SPIZ 的头像
SPIZ7 个月前

Absolutely mogged by community notes

Chubby♨️ 的头像
Chubby♨️7 个月前

Lets go!

atomic.chat 的头像
atomic.chat7 个月前

Keep building!

bnbature001 的头像
bnbature0017 个月前

The first ever wrapper for local models using google's algorithm

atomic.chat 的头像
atomic.chat7 个月前

and totally FREE for everyone ;)

Tom Turney 的头像
Tom Turney7 个月前

you're welcome lol

Sigma Browser 的头像
Sigma Browser7 个月前

The first ever wrapper for local models using google's algorithm!

Alex 的头像
Alex7 个月前

Atomic has made something huge. They’re the first team who managed to bring Google TurboQuant into local AI setups and actually put it in people’s hands LFG

404 的头像
4047 个月前

Was waiting all day for something like this since the google turboquant post so I wouldn’t have to do it myself thank you lol

LUKSONTEACH 的头像
LUKSONTEACH7 个月前

That’s seriously impressive Running a powerful model like Qwen3.5-9B locally with a 50K context window on a MacBook Air M4 shows how fast on-device AI is evolving. The ability to summarize 20K+ words in seconds — without relying on the cloud — is a huge win for privacy, speed, and cost efficiency. Atomic Chat is really pushing the boundaries here. If this is already 3x faster with larger context, we’re getting closer to a future where local AI can fully compete with cloud-based setups

Lance | WarburgAI 的头像
Lance | WarburgAI7 个月前

Steal someone’s ai project, slap your name on it. Then forget to change the system prompt and get mogged for it Beautiful 2026 slop

Blockhead 的头像
Blockhead7 个月前

These guys are frauds, just a clone of an open source repo, no credit given to actual builders.

jeff spaulding 的头像
jeff spaulding7 个月前

@ollama wen?

atomic.chat 的头像
atomic.chat7 个月前

@ollama It is already inside. Through Atomic Chat, you can use all open-source models, including those from HuggingFace 🤗

nickster 的头像
nickster7 个月前

Whoaaa!!!!! Cool

Konstantin Gladych 的头像
Konstantin Gladych7 个月前

Wow! Can I connect to my OpenClaw?

atomic.chat 的头像
atomic.chat7 个月前

OpenClaw running locally on your own machine very, very soon 👀 but yeah… that’s still a secret 🤫

FrontierMind 的头像
FrontierMind7 个月前

It’s amazing- super fast, and the web search works really well.

Haseeb Mir 的头像
Haseeb Mir7 个月前

@ollama could you please add this also?

Sky 的头像
Sky7 个月前

S+ tier slop ✅Pointless AI video ✅Vibecoded slop website ✅AI generated logo (come on) ✅Badly edited sped up video ✅Vibecoded app that copies ChatGPT UI ✅False claims Also why remove Claude from the contributors on GitHub? There is no way 4 *real* people made this.

Smarvx 的头像
Smarvx7 个月前

That’s actually impressive. Running that level of performance locally changes the game faster, private, and no reliance on external APIs.

Kaps 🇦🇪 | AI • Tech • Life 的头像
Kaps 🇦🇪 | AI • Tech • Life7 个月前

50k context window on a MacBook Air. no API key. no subscription. no cloud. this is what KV cache compression actually means in practice. the paper was impressive. this is what it looks like when it runs in your hands.

Musa Muhammad Juma 的头像
Musa Muhammad Juma7 个月前

That’s honestly impressive for a local setup.

atomicbot.ai 的头像
atomicbot.ai7 个月前

builders gonna love this 🦞

LeGOAT 的头像
LeGOAT7 个月前

could we leverage these models within harnesses like Hermes?

someone you know 的头像
someone you know7 个月前

@Scobleizer have you seen that?

Vision24 的头像
Vision247 个月前

Very cool

kashamashasha 的头像
kashamashasha7 个月前

GJ!!!

Dan Swanson 的头像
Dan Swanson7 个月前

Amazing!

jayousi 的头像
jayousi7 个月前

looks a bit sus ngl

𝕸𝖗. 𝕻𝖎𝖕𝖙𝖔𝖈𝖍𝖆𝖎𝖓🔗 的头像
𝕸𝖗. 𝕻𝖎𝖕𝖙𝖔𝖈𝖍𝖆𝖎𝖓🔗7 个月前

Locked in nd ready

rahulio 的头像
rahulio7 个月前

Total fail trying to install this on 2 machines with 2 LLMs helping. ----------- Subject: Cannot connect to local Ollama server — models not detected Environment: Atomic Chat (latest version, macOS) MacBook Air M4, 24GB RAM, macOS Sequoia Ollama v0.9.x running locally on port 11434 Two models available: qwen3:14b and qwen3.5:9b-q8_0 Ollama API is confirmed working: curl → Returns both models correctly via OpenAI-compatible endpoint What I tried and what failed: OpenAI provider with custom base URLSet Base URL to Set API key to ollama Result: Models dropdown shows only hardcoded OpenAI models (gpt-5, gpt-5-mini, gpt-4.5-preview, etc.). It never fetches from the custom base URL. Clicking Refresh does nothing. Restarting the app does nothing. Foundation-models provider — manual model addAdded qwen3:14b manually under Foundation-models It appeared in the Foundation-models settings list Result: Model never appeared in the main chat "Select a model" dropdown. Cannot actually use it for conversations. Typing model name directly in chat selectorTyped qwen3:14b into the "Select a model" search box Result: "No models found for qwen3:14b" Local API Server toggleEnabled "Start server on launch" in settings Result: No change — this seems to be for serving Atomic Chat as an API, not for connecting to external servers. Expected behavior: Atomic Chat should fetch the model list from the custom base URL ( and display the available Ollama models in the chat selector. Actual behavior: The OpenAI provider ignores the custom base URL for model discovery and shows a hardcoded list. Models added manually via Foundation-models don't surface in the chat UI.

PunkGirl 的头像
PunkGirl7 个月前

This is all free ?

Broooooklyn 的头像
Broooooklyn7 个月前

Check this out — you might want to use my quantized Qwen models as the default

0xInuarashi 的头像
0xInuarashi7 个月前

wild

BlackCat 的头像
BlackCat7 个月前

@grok 這跟 有什麼關係?

iamcryptodad 🥷 🇵🇭 的头像
iamcryptodad 🥷 🇵🇭7 个月前

The context window is the sleeper feature. 50K tokens means you can fit entire codebases, legal documents, or research papers. The MacBook as an AI workstation narrative just got more real.

olajide paris 的头像
olajide paris7 个月前

50,000 context window 😬 what are people even doing with these local models? That’s unusable.

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