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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

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73,547 次观看 • 5 个月前 •via X (Twitter)

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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:

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 次观看 • 1 年前

Running four high-level OpenCode agents + subagents with mlx_lm.server continuous batching and MiniMax M2.5 (6-bit). Fits easily on a 512GB M3 Ultra. Generation is quite fast. But prefill is still slow compared to cloud servers.

Running four high-level OpenCode agents + subagents with mlx_lm.server continuous batching and MiniMax M2.5 (6-bit). Fits easily on a 512GB M3 Ultra. Generation is quite fast. But prefill is still slow compared to cloud servers.

Awni Hannun

25,535 次观看 • 5 个月前

Mistral Vibe CLI running Devstral-small-2-2512 on M3 Ultra 512GB with LM Studio as backend 🔥 First part of the video 1x and the remaining 2x Great speed overall, 27 toks/s as average tracked on LM Studio console. Details to run it below 🧵

Mistral Vibe CLI running Devstral-small-2-2512 on M3 Ultra 512GB with LM Studio as backend 🔥 First part of the video 1x and the remaining 2x Great speed overall, 27 toks/s as average tracked on LM Studio console. Details to run it below 🧵

Ivan Fioravanti ᯅ

49,682 次观看 • 7 个月前

Open-weight MiniMax M3 filled out a US customs form from a driver's license photo For this test we deployed MiniMax M3 Q4 using MLX-VLM on a Mac Studio M3 Ultra 512GB RAM. The model was tasked with reading a scanned document and an ID card photo, then completing a declaration form Output: 736 tokens · Input: 1,847 tokens · Time: ~31s The model analyzed both inputs, streamed its reasoning, and then called three tools: write_field for text fields, mark for Yes/No checkboxes, and sign for the signature and date. It extracted the required information, mapped it to the correct fields and completed the form without any manual input

Open-weight MiniMax M3 filled out a US customs form from a driver's license photo For this test we deployed MiniMax M3 Q4 using MLX-VLM on a Mac Studio M3 Ultra 512GB RAM. The model was tasked with reading a scanned document and an ID card photo, then completing a declaration form Output: 736 tokens · Input: 1,847 tokens · Time: ~31s The model analyzed both inputs, streamed its reasoning, and then called three tools: write_field for text fields, mark for Yes/No checkboxes, and sign for the signature and date. It extracted the required information, mapped it to the correct fields and completed the form without any manual input

atomic.chat

109,369 次观看 • 1 个月前

MiniMax M3 support added to mlx-vlm with MSA implementation! 🚀 Tested on M3 Ultra 512GB running at 24 tps with peak memory ~240GB. Now working on optimizing performance and adding ton of tests 💪 Model is here: PR is here:

MiniMax M3 support added to mlx-vlm with MSA implementation! 🚀 Tested on M3 Ultra 512GB running at 24 tps with peak memory ~240GB. Now working on optimizing performance and adding ton of tests 💪 Model is here: PR is here:

Ivan Fioravanti ᯅ

24,376 次观看 • 1 个月前

Cyberpunk 2077 reviewed on Apple Mac! Oliver Mackenzie tests out the impressive port on an M4-powered Mac Mini, M4 Max MacBook Pro and the M3 Ultra Mac Studio. Features analysis, performance testing, plus PC head-to-heads and more:

Cyberpunk 2077 reviewed on Apple Mac! Oliver Mackenzie tests out the impressive port on an M4-powered Mac Mini, M4 Max MacBook Pro and the M3 Ultra Mac Studio. Features analysis, performance testing, plus PC head-to-heads and more:

Digital Foundry

47,035 次观看 • 1 年前

I'm getting there folks... Playing with bigger opensource models and getting Sonnet-ish replies within my OpenClaw🦞 for 'free'🔥 Loaded up Qwen3.5-397b-a17b on the mac studio and after learning about MLX and LM studio for a day & finally got it working 🤓

I'm getting there folks... Playing with bigger opensource models and getting Sonnet-ish replies within my OpenClaw🦞 for 'free'🔥 Loaded up Qwen3.5-397b-a17b on the mac studio and after learning about MLX and LM studio for a day & finally got it working 🤓

Jesse Genet

56,928 次观看 • 4 个月前

$Anthropic is starting to ban Pro/Max accounts for using OpenClaw. Don’t risk your main account. 🛑 I’ve been running OpenClaw + Claude Code through the MiniMax M2.5 provider for $20/month. It’s "unlimited" for dev work and completely bypasses the ban wave since you’re using a dedicated API gateway. The setup: - Get the $10/$20 Coding Plan at - Grab the API key from the "Direct Account" sidebar. - Update your settings.json (Windows) or .zshrc (Mac) with the MiniMax endpoint. Claude Code (Windows): Go to ~/username/.claude/settings.json Paste your API key into this JSON: { "env": { "ANTHROPIC_BASE_URL": " "ANTHROPIC_AUTH_TOKEN": " ", "API_TIMEOUT_MS": "3000000", "CLAUDE_CODE_DISABLE_NONESSENTIAL_TRAFFIC": 1, "ANTHROPIC_MODEL": "MiniMax-M2.5", "ANTHROPIC_SMALL_FAST_MODEL": "MiniMax-M2.5", "ANTHROPIC_DEFAULT_SONNET_MODEL": "MiniMax-M2.5", "ANTHROPIC_DEFAULT_OPUS_MODEL": "MiniMax-M2.5", "ANTHROPIC_DEFAULT_HAIKU_MODEL": "MiniMax-M2.5" } } Claude Code (macOS): In ~/.zshrc add: export MINIMAX_API_KEY="your_minimax_api_key_here" export ANTHROPIC_BASE_URL=" export ANTHROPIC_AUTH_TOKEN="$MINIMAX_API_KEY" export ANTHROPIC_MODEL="MiniMax-M2.5" Config details in the video. 👇$

Anthropic is starting to ban Pro/Max accounts for using OpenClaw. Don’t risk your main account. 🛑 I’ve been running OpenClaw + Claude Code through the MiniMax M2.5 provider for $20/month. It’s "unlimited" for dev work and completely bypasses the ban wave since you’re using a dedicated API gateway. The setup: - Get the $10/$20 Coding Plan at - Grab the API key from the "Direct Account" sidebar. - Update your settings.json (Windows) or .zshrc (Mac) with the MiniMax endpoint. Claude Code (Windows): Go to ~/username/.claude/settings.json Paste your API key into this JSON: { "env": { "ANTHROPIC_BASE_URL": " "ANTHROPIC_AUTH_TOKEN": " ", "API_TIMEOUT_MS": "3000000", "CLAUDE_CODE_DISABLE_NONESSENTIAL_TRAFFIC": 1, "ANTHROPIC_MODEL": "MiniMax-M2.5", "ANTHROPIC_SMALL_FAST_MODEL": "MiniMax-M2.5", "ANTHROPIC_DEFAULT_SONNET_MODEL": "MiniMax-M2.5", "ANTHROPIC_DEFAULT_OPUS_MODEL": "MiniMax-M2.5", "ANTHROPIC_DEFAULT_HAIKU_MODEL": "MiniMax-M2.5" } } Claude Code (macOS): In ~/.zshrc add: export MINIMAX_API_KEY="your_minimax_api_key_here" export ANTHROPIC_BASE_URL=" export ANTHROPIC_AUTH_TOKEN="$MINIMAX_API_KEY" export ANTHROPIC_MODEL="MiniMax-M2.5" Config details in the video. 👇

Ziwen

108,516 次观看 • 5 个月前

DeepSeek-R1-0528-5bit on MLX pushing M3 Ultra 512GB to its limits! 501GB used mem visibile on mactop in the video! Context: 4K tokens Prompt: 190.29 t/s Gen: 11.37 t/s Peak Mem: 487.48 GB! THIS IS APPLE MLX!

DeepSeek-R1-0528-5bit on MLX pushing M3 Ultra 512GB to its limits! 501GB used mem visibile on mactop in the video! Context: 4K tokens Prompt: 190.29 t/s Gen: 11.37 t/s Peak Mem: 487.48 GB! THIS IS APPLE MLX!

Ivan Fioravanti ᯅ

102,949 次观看 • 1 年前

Running Minimax M2.1 (MiniMax (official)) with OpenCode (OpenCode) and mlx_lm.server. Works quite well on an M3 Ultra. Once the KV cache is warm the prompt processing is pretty quick. And token generation is very fast.

Running Minimax M2.1 (MiniMax (official)) with OpenCode (OpenCode) and mlx_lm.server. Works quite well on an M3 Ultra. Once the KV cache is warm the prompt processing is pretty quick. And token generation is very fast.

Awni Hannun

32,329 次观看 • 7 个月前

Let me demonstrate the true power of llama.cpp: - Running on Mac Studio M2 Ultra (3 years old) - Gemma 4 26B A4B Q8_0 (full quality) - Built-in WebUI (ships with llama.cpp) - MCP support out of the box (web-search, HF, github, etc.) - Prompt speculative decoding The result: 300t/s (realtime video)

Let me demonstrate the true power of llama.cpp: - Running on Mac Studio M2 Ultra (3 years old) - Gemma 4 26B A4B Q8_0 (full quality) - Built-in WebUI (ships with llama.cpp) - MCP support out of the box (web-search, HF, github, etc.) - Prompt speculative decoding The result: 300t/s (realtime video)

Georgi Gerganov

784,420 次观看 • 4 个月前

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)

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 次观看 • 5 个月前

local LLMs on Mac are getting good. but the workflow around models is still messy. you have models in: •⁠ ⁠LM Studio •⁠ ⁠Ollama •⁠ ⁠Hugging Face cache •⁠ ⁠random folders •⁠ ⁠manual downloads and every runtime expects something slightly different. we built ModelHub to clean up this layer. it’s a native macOS menu bar app for discovering, downloading, and managing local LLMs. not a replacement for Ollama, oMLX or LM Studio. it sits beside them. Ollama = run models MLX = Apple Silicon acceleration LM Studio = local model workspace Hugging Face = model ecosystem ModelHub = model discovery + management layer we’re live on Product Hunt today. would love feedback from people running local models on Mac.

local LLMs on Mac are getting good. but the workflow around models is still messy. you have models in: •⁠ ⁠LM Studio •⁠ ⁠Ollama •⁠ ⁠Hugging Face cache •⁠ ⁠random folders •⁠ ⁠manual downloads and every runtime expects something slightly different. we built ModelHub to clean up this layer. it’s a native macOS menu bar app for discovering, downloading, and managing local LLMs. not a replacement for Ollama, oMLX or LM Studio. it sits beside them. Ollama = run models MLX = Apple Silicon acceleration LM Studio = local model workspace Hugging Face = model ecosystem ModelHub = model discovery + management layer we’re live on Product Hunt today. would love feedback from people running local models on Mac.

sabesh 📟

31,497 次观看 • 2 个月前

I didn't expect DeepSeek v4 PRO (not Flash) to run well on the Mac Studio M3 Ultra with 512GB of RAM. This is 2 bit quantized with the same DwarfStar recipe used for Flash. 433GB GGUF file. 130 t/s prefill, 13 t/s generation. Prefill in the video is low because small prompt.

I didn't expect DeepSeek v4 PRO (not Flash) to run well on the Mac Studio M3 Ultra with 512GB of RAM. This is 2 bit quantized with the same DwarfStar recipe used for Flash. 433GB GGUF file. 130 t/s prefill, 13 t/s generation. Prefill in the video is low because small prompt.

antirez

171,478 次观看 • 2 个月前

GLM-5 runs with mlx-lm on a single 512GB M3 Ultra in Q4. It's quite good in my initial testing and pretty fast as well. It generated a highly functional space invaders game using 7.1k tokens at 15.4 tok/s and 419GB memory. Thanks to Gökdeniz Gülmez and Tarjei Mandt for the port.

GLM-5 runs with mlx-lm on a single 512GB M3 Ultra in Q4. It's quite good in my initial testing and pretty fast as well. It generated a highly functional space invaders game using 7.1k tokens at 15.4 tok/s and 419GB memory. Thanks to Gökdeniz Gülmez and Tarjei Mandt for the port.

Awni Hannun

60,599 次观看 • 5 个月前

Just for fun, here's what 32 simultaneous long-context generations with Qwen3 Next 80B looks like on an M3 Ultra. Using the new batch generation in mlx-lm. Context size for each is about 5k tokens:

Just for fun, here's what 32 simultaneous long-context generations with Qwen3 Next 80B looks like on an M3 Ultra. Using the new batch generation in mlx-lm. Context size for each is about 5k tokens:

Awni Hannun

50,272 次观看 • 10 个月前

PSA: MiniMax (official) M2.5 is freely available on OpenCode Great opportunity to check out the power of open models for coding

PSA: MiniMax (official) M2.5 is freely available on OpenCode Great opportunity to check out the power of open models for coding

Niels Rogge

49,072 次观看 • 5 个月前

Local model update! 🚨 The MiniMax (official) 2.7 model has been powering my homeschool OpenClaw🦞 for a week without any issue 💕 Sooo much cheaper than Anthropic options in general, but with my Mac Studio it’s running for the cost of electricity!

Local model update! 🚨 The MiniMax (official) 2.7 model has been powering my homeschool OpenClaw🦞 for a week without any issue 💕 Sooo much cheaper than Anthropic options in general, but with my Mac Studio it’s running for the cost of electricity!

Jesse Genet

32,912 次观看 • 3 个月前

This is the best Open Source TTS available on Mac right now. Watch Peter break it down. I combined two Qwen3-TTS projects. One for MLX speed & the other for its beautiful UI (but was slow on Mac). Then added a bunch of features. Qwen3-TTS-MLX-WebUI-Enhanced Install via Pinokio

This is the best Open Source TTS available on Mac right now. Watch Peter break it down. I combined two Qwen3-TTS projects. One for MLX speed & the other for its beautiful UI (but was slow on Mac). Then added a bunch of features. Qwen3-TTS-MLX-WebUI-Enhanced Install via Pinokio

Blaine Brown

167,415 次观看 • 5 个月前

MLX GLM 5.2 Distributed on two M3 Ultra 512GB 🔥 One M3 Ultra: 18.8 tokens/sec Two M3 Ultra: 23.4 tokens/sec Context: - PR by Pedro Cuenca is still open and probably there is room for improvement: - basic generation test to measure decoding performance here, I will do a full context benchmarking once PR is more mature - nvfp4 quantization used - Video alternates standard speed and x20, with one Mac first and distributed later. Enjoy! 🙌🏻

MLX GLM 5.2 Distributed on two M3 Ultra 512GB 🔥 One M3 Ultra: 18.8 tokens/sec Two M3 Ultra: 23.4 tokens/sec Context: - PR by Pedro Cuenca is still open and probably there is room for improvement: - basic generation test to measure decoding performance here, I will do a full context benchmarking once PR is more mature - nvfp4 quantization used - Video alternates standard speed and x20, with one Mac first and distributed later. Enjoy! 🙌🏻

Ivan Fioravanti ᯅ

87,805 次观看 • 1 个月前