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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

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Adrien Grondin

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72,719 görüntüleme • 17 gün önce •via X (Twitter)

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🚨BREAKING: OpenAI's Codex is now completely FREE to run locally with Ollama. No API costs. No rate limits. 100% private on your machine. You can now use both the Codex App and Codex CLI with powerful open-source models like DeepSeek V4, Gemma 4, and Qwen 3.6. Here's how to set it up in minutes:
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🚨BREAKING: OpenAI's Codex is now completely FREE to run locally with Ollama. No API costs. No rate limits. 100% private on your machine. You can now use both the Codex App and Codex CLI with powerful open-source models like DeepSeek V4, Gemma 4, and Qwen 3.6. Here's how to set it up in minutes:

WorldofAI

793,569 görüntüleme • 9 gün önce

I’ve been using the new MacBook Pro M5 since launch and it’s a beast, especially compared to my old M1! It’s good for running the smaller AI models locally but also everything you do is just so fast. Here’s Gemma 3 QAT 12B running with MLX:
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I’ve been using the new MacBook Pro M5 since launch and it’s a beast, especially compared to my old M1! It’s good for running the smaller AI models locally but also everything you do is just so fast. Here’s Gemma 3 QAT 12B running with MLX:

Adrien Grondin

101,950 görüntüleme • 6 ay önce

Pretty cool that with the new Qwen 2.5 models you can ask questions / generate using a reasonably sized code-base as context, all running on a laptop with mlx-lm. The 7B runs pretty fast on an M4 Max using the mlx-lm code base (~16k lines) as context:
0:43

Pretty cool that with the new Qwen 2.5 models you can ask questions / generate using a reasonably sized code-base as context, all running on a laptop with mlx-lm. The 7B runs pretty fast on an M4 Max using the mlx-lm code base (~16k lines) as context:

Awni Hannun

27,442 görüntüleme • 1 yıl önce

The new Qwen 3.5 4B runs incredibly well on M5. The model is close to GPT-4o in benchmarks. Running fully on-device with MLX.
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The new Qwen 3.5 4B runs incredibly well on M5. The model is close to GPT-4o in benchmarks. Running fully on-device with MLX.

Adrien Grondin

230,124 görüntüleme • 3 ay önce

A long time coming but new mlx-lm is here with better batching support in the server and Gemma 4. pip install -U mlx-lm Here is a video where a single M3 Ultra serves 5 opencode sessions with Gemma 4 26B that process ~130k tokens in ~1.5 minutes.
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A long time coming but new mlx-lm is here with better batching support in the server and Gemma 4. pip install -U mlx-lm Here is a video where a single M3 Ultra serves 5 opencode sessions with Gemma 4 26B that process ~130k tokens in ~1.5 minutes.

Angelos Katharopoulos

66,005 görüntüleme • 2 ay önce

Part 02 -- Universal CLI Agent Server Claude Code, Codex CLI, Qwen Code, Gemini CLI, or anything---Use ANY terminal AI agents right in the browser with 1 click, just like web surfing. Reply to help with beta.
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Part 02 -- Universal CLI Agent Server Claude Code, Codex CLI, Qwen Code, Gemini CLI, or anything---Use ANY terminal AI agents right in the browser with 1 click, just like web surfing. Reply to help with beta.

cocktail peanut

12,197 görüntüleme • 7 ay önce

Next mlx-vlm release will ship with continuous batching support on the server 🚀 What's coming: → Continuous batching — new requests join the active batch immediately, no waiting. Mixed image + text batches supported → OpenAI-compatible API — field-for-field match with mlx-lm, reasoning/content split for thinking models, tag-aware streaming → Multi-turn tool calling — full tool use support across streaming and non-streaming, works with Gemma4 and other templates → Vision feature caching — cache image embeddings across turns. Gemma4: 228x speedup, Qwen3.5: 23x on cache hit All running locally on Apple Silicon. Check our this demo running 4 concurrent requests (mixed image + text) to gemma-4-26B-A4B-IT by Google Gemma in bf16 using Pi + MLX-VLM server on my M3 Ultra. One of the requests ingests a 8K resolution image!
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Next mlx-vlm release will ship with continuous batching support on the server 🚀 What's coming: → Continuous batching — new requests join the active batch immediately, no waiting. Mixed image + text batches supported → OpenAI-compatible API — field-for-field match with mlx-lm, reasoning/content split for thinking models, tag-aware streaming → Multi-turn tool calling — full tool use support across streaming and non-streaming, works with Gemma4 and other templates → Vision feature caching — cache image embeddings across turns. Gemma4: 228x speedup, Qwen3.5: 23x on cache hit All running locally on Apple Silicon. Check our this demo running 4 concurrent requests (mixed image + text) to gemma-4-26B-A4B-IT by Google Gemma in bf16 using Pi + MLX-VLM server on my M3 Ultra. One of the requests ingests a 8K resolution image!

Prince Canuma

82,085 görüntüleme • 1 ay önce

Excited to release v1 of /review in the Codex CLI! You can now use gpt-5-codex to investigate and find critical bugs in your code. Check it out and let us know if you have any feedback!
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Excited to release v1 of /review in the Codex CLI! You can now use gpt-5-codex to investigate and find critical bugs in your code. Check it out and let us know if you have any feedback!

daniel

742,520 görüntüleme • 8 ay önce

I’ve tried driving Qwen 3.6 on my MacBook Pro with a few different agent harnesses: Claude Code: too slow. It moves like a turtle. Codex: Qwen stopped in the middle of tasks, probably due to tool-call mismatches between them. Qwen Code: so far the best experience. Very smooth. Qwen Code sometimes even tells a joke while you’re waiting. This video is played at original speed so you can get a real feel for how Qwen works.
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I’ve tried driving Qwen 3.6 on my MacBook Pro with a few different agent harnesses: Claude Code: too slow. It moves like a turtle. Codex: Qwen stopped in the middle of tasks, probably due to tool-call mismatches between them. Qwen Code: so far the best experience. Very smooth. Qwen Code sometimes even tells a joke while you’re waiting. This video is played at original speed so you can get a real feel for how Qwen works.

Michael Guo

20,347 görüntüleme • 19 gün önce

The latest Qwen 3 VL by Qwen running on iPhone 17 Pro with MLX Qwen 3 VL brings upgraded visual understanding, recognition, and OCR capabilities without sacrificing text performance like previous models The 4B model here is close to Qwen 2.5 VL 72B in many benchmarks
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The latest Qwen 3 VL by Qwen running on iPhone 17 Pro with MLX Qwen 3 VL brings upgraded visual understanding, recognition, and OCR capabilities without sacrificing text performance like previous models The 4B model here is close to Qwen 2.5 VL 72B in many benchmarks

Adrien Grondin

109,700 görüntüleme • 7 ay önce

QWEN 3.5 4b MLX running locally with a milk avatar Model by ToxSam
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QWEN 3.5 4b MLX running locally with a milk avatar Model by ToxSam

tensorfish

122,041 görüntüleme • 2 ay önce

The new Qwen 3.5 by Qwen running on-device on iPhone 17 Pro. Qwen 3.5 beats models 4 times its size, has strong visual understanding, and can toggle reasoning on or off. The 2B 6-bit model here is running with MLX optimized for Apple Silicon.
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The new Qwen 3.5 by Qwen running on-device on iPhone 17 Pro. Qwen 3.5 beats models 4 times its size, has strong visual understanding, and can toggle reasoning on or off. The 2B 6-bit model here is running with MLX optimized for Apple Silicon.

Adrien Grondin

3,551,720 görüntüleme • 3 ay önce

Gemma 4 is now in Android Studio! You can use Android Studio Agent mode to develop features, vibe code Android apps, refactor your code, and fix bugs, all locally, and powered by Gemma!
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Gemma 4 is now in Android Studio! You can use Android Studio Agent mode to develop features, vibe code Android apps, refactor your code, and fix bugs, all locally, and powered by Gemma!

Omar Sanseviero

36,878 görüntüleme • 2 ay önce

OpenAI Codex is now integrated directly in Visual Studio Code through the new Agent Sessions view - and can be powered by your GitHub Copilot subscription. Try it out now with VS Code Insiders and a Copilot Pro+ subscription. Happy coding!
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OpenAI Codex is now integrated directly in Visual Studio Code through the new Agent Sessions view - and can be powered by your GitHub Copilot subscription. Try it out now with VS Code Insiders and a Copilot Pro+ subscription. Happy coding!

Visual Studio Code

334,902 görüntüleme • 7 ay önce

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:
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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

186,641 görüntüleme • 10 ay önce

Casual reminder - you can run o1-mini level or better models on your laptop at home. Here's DeepSeek R1 distilled to Qwen 32B running pretty quick on an M4 Max with the MLX back-end in LM Studio
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Casual reminder - you can run o1-mini level or better models on your laptop at home. Here's DeepSeek R1 distilled to Qwen 32B running pretty quick on an M4 Max with the MLX back-end in LM Studio

Awni Hannun

55,342 görüntüleme • 1 yıl önce

Subagents are GA in the Codex App and CLI, it's positively changed the way I work - go give it a shot now!!
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Subagents are GA in the Codex App and CLI, it's positively changed the way I work - go give it a shot now!!

Vaibhav (VB) Srivastav

21,469 görüntüleme • 2 ay önce

CLI coding agents now have first-class support in Warp: • Built-in voice transcription powered by Wispr Flow • Attach images to your prompt easily • Browse files and review code directly in Warp Works with Claude Code, Codex, Amp, Gemini, and Droid 🙌
0:45

CLI coding agents now have first-class support in Warp: • Built-in voice transcription powered by Wispr Flow • Attach images to your prompt easily • Browse files and review code directly in Warp Works with Claude Code, Codex, Amp, Gemini, and Droid 🙌

Warp

122,304 görüntüleme • 4 ay önce

Your Mac is about to run inference like a datacenter. Coming soon to MLX-Swift: Continuous batching: the fastest way to handle multiple inference streams locally. It starts with regular inference and seamlessly upgrades to batched mode when new requests arrive. The best of both worlds. Based on the work of and Awni Hannun
0:25

Your Mac is about to run inference like a datacenter. Coming soon to MLX-Swift: Continuous batching: the fastest way to handle multiple inference streams locally. It starts with regular inference and seamlessly upgrades to batched mode when new requests arrive. The best of both worlds. Based on the work of and Awni Hannun

Ronald Mannak

60,570 görüntüleme • 7 ay önce

I tested Gemma 4 12b on my Macbook Pro M5 Max with 128GB of unified memory. It runs VERY slow for a 12b parameter model. 44 tokens/second. The lava lamp that it produced was also terrible. I would stick to Qwen 3.6 27b or Qwen 3.6 35b. Google is still way behind, even with their local models.
1:36

I tested Gemma 4 12b on my Macbook Pro M5 Max with 128GB of unified memory. It runs VERY slow for a 12b parameter model. 44 tokens/second. The lava lamp that it produced was also terrible. I would stick to Qwen 3.6 27b or Qwen 3.6 35b. Google is still way behind, even with their local models.

BridgeMind

58,903 görüntüleme • 2 gün önce