oMLX 0.7.4.dev1 dev build links two Macs: an M5 Max helps a high-memory Mac process long prompts, up to 2.9x faster at 64K tokens

oMLX 0.7.4.dev1 is out! github.com/jundot/omlx/releases… With the new Prefill Accelerator, connect an M5 Max to your big Mac and prefill up to 2.9x faster! Prefill Accelerator (64K prompt, M3 Ultra 512GB + M5 Max 128GB) - DeepSeek V4.1 Flash: 1,060 -> 3,123 tok/s (+195%) - Qwen3.8 Flash-Next: 1,309 -> 3,666 tok/s (+180%) - GLM-5.3 Flash: 540 -> 1,388 tok/s (+157%) - MiniMax M3.1: 297 -> 569 tok/s (+92%) - An M5 Max 64GB still adds 30-118%, and decode speed stays the same. Faster DeepSeek V4.1 with A8 and buffer pool improvements - Prefill on M5 Ultra is 43-48% faster, 32K goes 2,631 -> 3,779 tok/s (+44%). - oQ4e builds now run INT8 Activation Prefill on M5. Faster Qwen3.8 Flash-Next - FP16 builds get the fused kernels. Decode on M3 Ultra goes 38.9 -> 63.0 tok/s (+62%), and +23% on M2 Max. - Decode after long prompts is 3-5% faster on M5 Max. Better for agents - Parallel tool results from Claude Code reach the model in call order, so Qwen no longer pairs a result with the wrong call. - Agent sessions on a cluster reuse the prompt cache across tool turns, 743 -> 9,266 cached tokens by the fifth turn. - Switch oMLX models inside Codex and Copilot with /model. Also in 0.7.4.dev1 - Ming-3.0 TTS with a 2x faster decode loop. - Ask AI can use an oMLX server on another Mac. - Check for model updates in the macOS app. - German across the web dashboard and the macOS app. - Batched decode with 6 requests on 8-bit models is 16% faster. A big thank you to everyone who sent PRs, reported bugs and tested builds for this release, and a warm welcome to the five new contributors!