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Is anyone actually using dflash and ddtree on mlx?

BACKGROUND
1 SIGNALFIRST DETECTED 6 May 2026UPDATED 16 May 2026
The NewsHive View

The question appeared without fanfare on May 6th, and its phrasing tells you everything about its emotional register: not "how do I use dflash and ddtree on MLX," not "here are my benchmarks," just — is anyone actually using them? That particular construction, the one that begins with "is anyone actually," is a developer's way of asking whether they're alone in a room. MLX is Apple's machine learning framework built for Apple Silicon, its core promise being that researchers and practitioners can run models natively on Mac hardware without rerouting everything through CUDA. Dflash and ddtree are components within that ecosystem — attention and tree-structured operations, respectively — that exist in the documentation and in the codebase, but apparently not, or at least not visibly, in the conversations of the people building with MLX day to day. One developer noticed the silence and named it.

If confirmed, here is what this means. When features go unused inside a framework that is itself competing for developer mindshare, the compounding effect is brutal. MLX is already fighting against the gravitational pull of PyTorch and the CUDA ecosystem that most ML practitioners learned on, were hired for, and have years of muscle memory around. If specific optimisation primitives inside MLX — the ones that would theoretically make it faster and more expressive on Apple Silicon — are sitting untouched, it suggests the adoption curve is shallower than Apple's documentation cadence implies. The people who might reach for dflash are the people doing serious attention-mechanism work; if they aren't there yet, or aren't reaching for those tools when they are, that's a signal about where MLX sits in the maturity stack. Not dead. Not irrelevant. But still asking to be taken seriously by the cohort that most needs to take it seriously.

Watch for any response from frequent MLX contributors or Apple-adjacent researchers either confirming active use with concrete examples, or — more telling — offering silence that stretches past the weekend.

How the story developed
6 May
0.0
Other feeds and industry voices
15 Apr
DFlash is real: x2 tg on small context with oMLX

<!-- SC_OFF --><div class="md"><p>Right from the oven with the <a href="https://github.com/jundot/omlx/commit/58b3ca549ab7aba075ecd5f1481911e01d819702">latest commit</a>:</p>

OPINION · WHAT · LocalLLaMAOPEN STORY
15 Apr
DTree on MLX ... tiny win over DFlash on Qwen3.5-4B (M2)..

<!-- SC_OFF --><div class="md"><p>I ported DTree to MLX ... and finally got one setting that seems to beat matched DFlash locally.</p> <pre><code>M2 Max 32GB, Qwen3.5-4B, q4_g64,

OPINION · WHAT · LocalLLaMAOPEN STORY
14 Apr
DDTree - Another layer of speed up on top of Dflash.

<!-- SC_OFF --><div class="md"><p>This is getting ridiculous. </p> <p>DDTreee paper: <a

OPINION · WHAT · LocalLLaMAOPEN STORY
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