Загрузка видео...

Не удалось загрузить видео

На главную

Kimi K3 (2.8T params) running locally on two Mac Studios, pi agent + mlx-lm

kernelpool's profile picture

Tarjei Mandt

17,486 subscribers

59,954 просмотров • 13 дней назад •via X (Twitter)

Наука и технологии
LIVE

Anya Rossi• Live Now

Private livecam show

Комментарии: 0

Нет доступных комментариев

Здесь появятся комментарии из оригинального поста

Похожие видео

The new Kimi K2 1T model (4-bit quant) runs on 2 512GB M3 Ultras with mlx-lm and mx.distributed. 1 trillion params, at a speed that's actually quite usable:
0:37

The new Kimi K2 1T model (4-bit quant) runs on 2 512GB M3 Ultras with mlx-lm and mx.distributed. 1 trillion params, at a speed that's actually quite usable:

Awni Hannun

238,152 просмотров • 1 год назад

Kimi K3's frontend work here is insane. Someone asked a Kimi K3 Max agent swarm to recreate macOS 27 as a web app. It looks so much like a real Mac that I kept forgetting the whole thing was running in a browser.
0:40

Kimi K3's frontend work here is insane. Someone asked a Kimi K3 Max agent swarm to recreate macOS 27 as a web app. It looks so much like a real Mac that I kept forgetting the whole thing was running in a browser.

Kai

270,631 просмотров • 24 дней назад

I'm so in love with antirez' ds4. Patched some slop on it to get better streaming, but I can just install a pi extension on a 128GB mac and it manages everything for me. No need for mlx-lm, ollama or lm studio or finagling pi configs.
1:33

I'm so in love with antirez' ds4. Patched some slop on it to get better streaming, but I can just install a pi extension on a 128GB mac and it manages everything for me. No need for mlx-lm, ollama or lm studio or finagling pi configs.

Armin Ronacher ⇌

56,284 просмотров • 3 месяцев назад

GLM5 running on a cluster of 4 Mac Studios using tensor parallelism thanks to MLX distributed. Yes, those are the Alex drawers.
0:26

GLM5 running on a cluster of 4 Mac Studios using tensor parallelism thanks to MLX distributed. Yes, those are the Alex drawers.

Alex Ziskind

20,594 просмотров • 5 месяцев назад

Kimi K2.6 was released 1h ago, and it looks amazing! Here it's running with MLX (mlx-vlm) on two M3 Ultras (full 1T param VLM) 🔥
0:23

Kimi K2.6 was released 1h ago, and it looks amazing! Here it's running with MLX (mlx-vlm) on two M3 Ultras (full 1T param VLM) 🔥

Pedro Cuenca

65,768 просмотров • 3 месяцев назад

Thanks for the mention TBPN! We're working on making this run at >40 tok/sec on 2 Mac Studios (the full, unquantized Kimi K2.5). I'm already running Kimi K2.5 myself locally with Claude Code and it's impressive - very close to Opus level.
0:21

Thanks for the mention TBPN! We're working on making this run at >40 tok/sec on 2 Mac Studios (the full, unquantized Kimi K2.5). I'm already running Kimi K2.5 myself locally with Claude Code and it's impressive - very close to Opus level.

Alex Cheema

40,471 просмотров • 6 месяцев назад

A perfect coding model for MLX on Apple silicon.. Qwen delivered again. Runs quite fast on an M3 Ultra. Running the 4-bit quantized with mlx-lm:
0:50

A perfect coding model for MLX on Apple silicon.. Qwen delivered again. Runs quite fast on an M3 Ultra. Running the 4-bit quantized with mlx-lm:

Awni Hannun

186,772 просмотров • 1 год назад

This is MiniMax-M2.5 MLX running in LM Studio on an Apple Mac Studio M3 Ultra 512GB. Fast enough out of the box for hosting OpenClaw, n8n workflows, and Open WebUI for the team.
0:53

This is MiniMax-M2.5 MLX running in LM Studio on an Apple Mac Studio M3 Ultra 512GB. Fast enough out of the box for hosting OpenClaw, n8n workflows, and Open WebUI for the team.

Patrick J Kennedy

76,574 просмотров • 5 месяцев назад

Llama 3 running locally on iPhone with MLX Built by exo intern team Mohamed Baioumy h/t Awni Hannun MLX & Prince Canuma for the port
0:24

Llama 3 running locally on iPhone with MLX Built by exo intern team Mohamed Baioumy h/t Awni Hannun MLX & Prince Canuma for the port

Alex Cheema

295,873 просмотров • 2 лет назад

Running Qwen2.5-Coder (0.5B params) locally on a Mac Intel Core i5 with CodeGPT and Ollama 🤩 In seconds, it explains Python code... all private and secure! Download CodeGPT from the VSCode Marketplace! 👏 Qwen ollama CodeGPT
0:27

Running Qwen2.5-Coder (0.5B params) locally on a Mac Intel Core i5 with CodeGPT and Ollama 🤩 In seconds, it explains Python code... all private and secure! Download CodeGPT from the VSCode Marketplace! 👏 Qwen ollama CodeGPT

Daniel San

30,613 просмотров • 1 год назад

MLX: Tom Riddle's diary running locally on an iPad powered by Apple MLX with Gemma 4 E4B behind the scene. Children can go crazy for something like this, no? 🔥
2:49

MLX: Tom Riddle's diary running locally on an iPad powered by Apple MLX with Gemma 4 E4B behind the scene. Children can go crazy for something like this, no? 🔥

Ivan Fioravanti ᯅ

17,820 просмотров • 28 дней назад

Run Qwen-TTS on Your Mac, natively. Blaine Brown has created Qwen3-TTS MLX WebUI Enhanced, a Web UI for running Qwen-TTS using the Mac-native MLX framework, powered by MLX-Audio from Prince Canuma, it runs very smooth! 1-click install on pinokio (Apple Silicon Macs)
0:40

Run Qwen-TTS on Your Mac, natively. Blaine Brown has created Qwen3-TTS MLX WebUI Enhanced, a Web UI for running Qwen-TTS using the Mac-native MLX framework, powered by MLX-Audio from Prince Canuma, it runs very smooth! 1-click install on pinokio (Apple Silicon Macs)

cocktail peanut

168,965 просмотров • 5 месяцев назад

Subagents running locally and simultaneously on MacBook Pro M5 with Codex CLI + LM Studio to review code and find bugs using Qwen 3.6 Powered by the updated MLX engine with batching in beta in the app The batching speed boost is noticeable
1:40

Subagents running locally and simultaneously on MacBook Pro M5 with Codex CLI + LM Studio to review code and find bugs using Qwen 3.6 Powered by the updated MLX engine with batching in beta in the app The batching speed boost is noticeable

Adrien Grondin

75,549 просмотров • 2 месяцев назад

Local agent media superpower. ComfyUI and Hermes Agent running together locally on AMD Ryzen AI Max+ processor based Agent Computer.
0:49

Local agent media superpower. ComfyUI and Hermes Agent running together locally on AMD Ryzen AI Max+ processor based Agent Computer.

AMD Ryzen

23,145 просмотров • 3 месяцев назад

Qwen3-Coder-Flash runs quite fast on an M4 Max with mlx-lm. Running the 4-bit here, generated 4,467 tokens at >107 tokens/sec:
0:21

Qwen3-Coder-Flash runs quite fast on an M4 Max with mlx-lm. Running the 4-bit here, generated 4,467 tokens at >107 tokens/sec:

Awni Hannun

196,508 просмотров • 1 год назад

BOOM! Latest Qwen 30B A3B 2507 running blazingly fast on Mac powered by MLX 💥 mlx_lm.chat --model "lmstudio-community/Qwen3-30B-A3B-Instruct-2507-MLX-4bit" That's it, try it out today!
1:38

BOOM! Latest Qwen 30B A3B 2507 running blazingly fast on Mac powered by MLX 💥 mlx_lm.chat --model "lmstudio-community/Qwen3-30B-A3B-Instruct-2507-MLX-4bit" That's it, try it out today!

Vaibhav (VB) Srivastav

35,873 просмотров • 1 год назад

i tested a fully local ai coding setup: gemma4 from Google DeepMind running through LM Studio, paired with pi which is a minimal open source coding harness this is part 1 of a two part series. here we cover the why and the complete hands-on setup 0:00 - Running a coding agent fully local 0:47 - Why Pi as the coding agent harness 1:39 - Why Gemma 4 and which variant to pick 2:44 - Architecture: Pi, LM Studio and Gemma 4 3:45 - LM Studio setup and model download 5:01 - Starting the local server 5:19 - API sanity check with curl 6:08 - Installing the Pi coding agent 6:20 - Configuring models.json for local models 8:20 - First run: selecting the model in Pi 8:58 - Fixing the context length error 10:16 - Testing the working setup 10:50 - What is coming in Part 2
11:32

i tested a fully local ai coding setup: gemma4 from Google DeepMind running through LM Studio, paired with pi which is a minimal open source coding harness this is part 1 of a two part series. here we cover the why and the complete hands-on setup 0:00 - Running a coding agent fully local 0:47 - Why Pi as the coding agent harness 1:39 - Why Gemma 4 and which variant to pick 2:44 - Architecture: Pi, LM Studio and Gemma 4 3:45 - LM Studio setup and model download 5:01 - Starting the local server 5:19 - API sanity check with curl 6:08 - Installing the Pi coding agent 6:20 - Configuring models.json for local models 8:20 - First run: selecting the model in Pi 8:58 - Fixing the context length error 10:16 - Testing the working setup 10:50 - What is coming in Part 2

Nidhi Singh

16,289 просмотров • 2 месяцев назад

We compared 1-bit Kimi K3 to Claude Opus 5 and GPT 5.6. We gave 4 models the same prompt: Create a glass aquarium whose side panel develops a visible crack and then bursts. 1-bit Kimi K3 GGUF ran locally on 4x B200s at 36 tok/s. GitHub repo:
0:35

We compared 1-bit Kimi K3 to Claude Opus 5 and GPT 5.6. We gave 4 models the same prompt: Create a glass aquarium whose side panel develops a visible crack and then bursts. 1-bit Kimi K3 GGUF ran locally on 4x B200s at 36 tok/s. GitHub repo:

Unsloth AI

412,031 просмотров • 12 дней назад