--- title: "M-series fleet ablation: M3 Ultra / M1 Ultra / M4 Pro" date: 2026-07-16 device: "M3 Ultra 256GB · M1 Ultra 128GB · M4 Pro mini 24GB · M5 MacBook Pro 16GB (10-core)" script: scripts/bench_optimizations.py (unmodified) + engine-level tiled×compile extension --- # M-series Fleet Ablation Benchmarks Same methodology as the 2026-03-09 wave2 doc (`--sweep ablation --resolution 512 1024 2048`, checkpoint weights, 3 warmup + 10 bench runs), executed on three machines spanning the Apple Silicon range. Contributed from a 3-Mac render-farm setup; happy to run follow-ups. ## Headline findings 1. **`sdpa` is a ~4.5× regression on M1-class GPUs at 2048 — and free on M3.** Single-toggle isolation at 2048 (median of 6, all-off baseline): | toggle | M1 Ultra | M3 Ultra | |---|---|---| | all off | 4139 ms | 1743 ms | | **bf16 only** | **4120 ms (neutral!)** | 1766 ms | | **sdpa only** | **18592 ms (4.5× slower)** | 1763 ms | | bf16+sdpa | 6388 ms | 1767 ms | The suspected M1 danger (bf16 emulation — M1 lacks hardware bf16) is **innocent** on this workload. **Root cause (follow-up, same day):** it is *not* the SDPA kernel. Instrumenting a real 2048 forward shows the model's attention shapes are `head_dim=56` (global blocks `(1,8,16384,56)` ×15, `(1,16,4096,56)` ×3; windowed `(4096,·,·,56)`). At head_dim 56, `mx.fast.scaled_dot_product_attention` **silently falls back to the unfused path** — fused == unfused within 1 % on every shape on both M1 and M3 Ultra. So `use_sdpa=True` currently buys zero kernel benefit on any machine, while its branch pays extra 5-D transpose/reshape choreography — which is what costs ~4.5× on M1 (layout-sensitive), ~free on M3. **The actionable win: pad head_dim 56 → 64.** The fast path then engages and beats unfused decisively — *despite ~14 % more FLOPs* (fp32, exact model shapes): | shape (hdim 64) | M3 fused/unfused | M1 fused/unfused | |---|---|---| | (1, 8, 16384, ·) | 28.6 / 63.1 ms → **2.2×** | 53.8 / 144.5 ms → **2.7×** | | (1, 16, 4096, ·) | 3.8 / 7.2 ms → 1.9× | 7.5 / 11.1 ms → 1.5× | | (4096, 2, 64, ·) | 1.3 / 2.5 ms → 1.9× | 1.5 / 2.6 ms → 1.7× | **…and on M5 it's worth ~5×, i.e. this fix matters MOST for laptop users.** Same experiment on an M5 MacBook Pro (10-core GPU, 16 GB) — hdim 56 vs 64, fp32: | shape | hdim 56 (today) | hdim 64 (padded) | **speedup from padding** | |---|---|---|---| | (1, 16, 4096) | 44.00 ms *(fallback: 1.05× vs unfused)* | **8.91 ms** *(fast path: 0.21×)* | **4.9×** | | (1, 16, 2048) | 11.44 ms *(1.06×)* | **2.23 ms** *(0.22×)* | **5.1×** | | (4096, 2, 64) | 16.72 ms *(0.97×)* | **5.29 ms** *(0.25×)* | **3.2×** | Why bigger on the laptop: the fused kernel's advantage over unfused scales inversely with GPU width. At seq 4096 fp32 (hdim 64) fused-vs-unfused is **7.1× on M5** vs ~1.9× on M3 Ultra — a 10-core GPU cannot brute-force the materialized N×N path the way an 80-core Ultra can. So the head_dim-56 fallback costs Studio owners ~2× and **MacBook owners ~5×**. Padding is not a big-iron optimization; it's a laptop one. Suggested changes: (a) pad qkv projections to head_dim 64 (at minimum for the global blocks) so sdpa's fast kernel actually engages — M1 benefits *more* than M3; (b) until then, default `use_sdpa=False` (it is currently overhead-only). For MLX upstream: a warning (or doc note) when sdpa silently falls back on unsupported head dims would have made this obvious much sooner. 2. **`stage_gc` is harmful on Ultra-class machines at every resolution** — 0.53× at 512, 0.64× at 1024, 0.66× at 2048 on M3 Ultra, for a 1–5 % peak-memory saving. Wave2 measured a mild 0.79–0.99× on its reference hardware; on big-memory machines it's pure overhead. Suggestion: document as a low-memory-only flag. 3. **Tiled + compile is the best 2048 config on both Ultras** — upstream `engine.py` forced `compile=False` in tiled mode; tiles are fixed-shape, so fused compilation applies (patched in this fork, output bit-identical, verified against ground-truth alpha): | engine config (2048 input) | M3 Ultra | M1 Ultra | peak | alpha MAE* | |---|---|---|---|---| | full-frame 2048 | 2788 ms | 5373 ms | 27.9 GB | 0.00906 | | tiled 512/64 | 2760 ms | 4576 ms | 2.2 GB | **0.00821** | | tiled 512/64 + compile | 2478 ms | 4222 ms | 2.3 GB | **0.00821** | | **tiled 768/64 + compile** | **1949 ms** | **3275 ms** | 2.4 GB | 0.00842 | | tiled 1024/64 + compile | 3475 ms | 5864 ms | 3.7 GB | 0.00915 | \*alpha MAE vs exact ground truth: synthetic 2048² green-screen plates (soft-alpha subject + motion-blur stripes + defocus disk composited over chroma green), hint = 8× downscaled truth. Tiled beats full-frame on *accuracy* as well as memory — the model runs at native tile scale over full-res input. Confirms wave2's tiled-768 pick and adds ~8–13 % from compiling the tile graph. 4. **24 GB Macs must tile at 2048.** On the M4 Pro mini (24 GB), every full-frame 2048 config lands at 20–24 s/run — the ~26 GB working set swaps; toggle choice becomes noise. At ≤1024 the M4 is healthy (218 ms @512, 1149 ms @1024). Tiled 2048 runs in ~2.3 GB. ## Cross-machine baselines (all-off) | res | M3 Ultra | M1 Ultra | M4 Pro 24GB | wave2 reference | |---|---|---|---|---| | 512 | 53.3 ms | 80.8 ms | 218.1 ms | 119.6 ms | | 1024 | 247.0 ms | 350.6 ms | 1149.2 ms | 610.7 ms | | 2048 | 1750.2 ms | 3527.3 ms | 23147 ms (swap) | 4984.7 ms | ### Raw SDPA kernel scaling (pure MLX, no CorridorKey) — fused vs unfused, hdim 64, fp32 Useful context for *why* the head-dim fix matters differently per machine. Fused-vs-unfused ratio (lower = fused is winning by more): | seq | M3 Ultra (80c) | M1 Ultra (64c) | M5 (10c laptop) | |---|---|---|---| | 1024 | 0.46× | 0.54× | 0.28× | | 2048 | 0.53× | 0.71× | **0.21×** | | 4096 | 0.53× | 0.59× | **0.14×** | Absolute fused times at 4096/fp32: M3 3.86 ms · M1 7.19 ms · **M5 7.22 ms** — an M5 laptop matches an M1 Ultra on *fused* attention while being ~4× slower unfused (51.5 ms vs 12.2 ms). The narrower the GPU, the more the fast path is worth. (M5 numbers taken on a machine in active desktop use; treat as indicative, not lab-clean.) ## Full ablation tables ### M3 Ultra 256GB | Config | 512 | 1024 | 2048 | peak @2048 | |---|---|---|---|---| | baseline | 53.3 | 247.0 | 1750.2 | 26689 MB | | slim+sdpa+bf16+fused_decode+gpu_preprocess | 53.5 | 248.2 | 1790.1 | 27245 MB | | slim+stage_gc+bf16+fused_decode+gpu_preprocess | 95.4 | 382.7 | 2644.3 | 26689 MB | | slim+stage_gc+sdpa+fused_decode+gpu_preprocess | 96.3 | 385.9 | 2676.9 | 26661 MB | | slim+stage_gc+sdpa+bf16+gpu_preprocess | 99.4 | 372.1 | 2618.6 | 26661 MB | | slim+stage_gc+sdpa+bf16+fused_decode | 99.0 | 386.5 | 2688.0 | 26661 MB | | stage_gc+sdpa+bf16+fused_decode+gpu_preprocess | 100.1 | 391.4 | 2628.2 | 26661 MB | | slim+stage_gc+sdpa+bf16+fused_decode+gpu_preprocess | 101.0 | 390.9 | 2617.9 | 26661 MB | ### M1 Ultra 128GB | Config | 512 | 1024 | 2048 | peak @2048 | |---|---|---|---|---| | baseline | 80.8 | 350.6 | 3527.3 | 26689 MB | | slim+sdpa+bf16+fused_decode+gpu_preprocess | 79.1 | 353.3 | **33137.8** | 27245 MB | | slim+stage_gc+bf16+fused_decode+gpu_preprocess | 189.5 | 705.5 | 4919.0 | 26689 MB | | slim+stage_gc+sdpa+fused_decode+gpu_preprocess | 195.6 | 711.1 | 4939.2 | 26661 MB | | slim+stage_gc+sdpa+bf16+gpu_preprocess | 198.2 | 681.6 | 4853.8 | 26661 MB | | slim+stage_gc+sdpa+bf16+fused_decode | 197.7 | 714.1 | 4822.9 | 26661 MB | | stage_gc+sdpa+bf16+fused_decode+gpu_preprocess | 194.2 | 733.2 | 6274.1 | 26661 MB | | slim+stage_gc+sdpa+bf16+fused_decode+gpu_preprocess | 193.8 | 737.1 | 5128.2 | 26661 MB | Note the 33.1 s outlier: the only 2048 config *without* `stage_gc` but *with* `sdpa` — sdpa's slow path dominating once nothing throttles it (see headline 1 for the isolation). The sdpa cliff appears only at 2048; 512/1024 are unaffected. ### M4 Pro Mac mini 24GB | Config | 512 | 1024 | 2048 (swap-bound) | |---|---|---|---| | baseline | 218.1 | 1149.2 | 23147.1 | | slim+sdpa+bf16+fused_decode+gpu_preprocess | 221.4 | 1139.0 | 20994.5 | | slim+stage_gc+… (all stage_gc combos) | 266–273 | 1268–1292 | 20233–24253 | At 2048 the ~26 GB working set exceeds 24 GB unified memory; all configs swap and differences are not meaningful. ≤1024 full-frame or tiled-anything is the usable envelope. ## Recommended settings by hardware | Hardware | 2048 recommendation | |---|---| | M3-class (Max/Ultra) | full-frame or tiled 768/64 + compile; every toggle optional; avoid `stage_gc` | | M1/M2-class | **avoid `sdpa`**; tiled 768/64 + compile; avoid `stage_gc` | | ≤24–32 GB any gen | **tiled required** (2.3 GB vs 26 GB); tiled 768/64 + compile | *Environment: MLX (venv per `uv sync --extra mlx`), macOS 26.5, checkpoint v1.0.0. Quality harness (ground-truth plates + scoring) available on request — it's ~150 lines and reproduces the alpha-MAE column.*