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main: anchor-guarded clip + DWQ-A45 rework, atomic swap (prior main preserved on dwq-noclip)

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  1. README.md +16 -14
  2. assets/quality.png +2 -2
  3. assets/quality.svg +6 -6
  4. config.json +0 -0
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README.md CHANGED
@@ -27,16 +27,18 @@ Apple Silicon (MLX) **mixed-precision** quantization of [zai-org/GLM-5.2](https:
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  **New:** the checkpoint now ships GLM-5.2's **native MTP (nextn) layer** for self-speculative decoding (`--mtp` — see [*Native MTP*](#native-mtp--self-speculative-decoding)). Fully backward-compatible: runtimes without MTP support strip the extra layer and behave exactly as before.
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- **Update (2026-07): DWQ-retuned weights.** `main` now carries quantization scales/biases re-tuned with **layerwise DWQ** ([alis-dwq](https://github.com/avlp12/alis-dwq); upstream flag: [mlx-lm#1499](https://github.com/ml-explore/mlx-lm/pull/1499)) against the [4.5 bpw sibling](https://huggingface.co/avlp12/GLM-5.2-Alis-MLX-Dynamic-4.5bpw) as teacher, with a 45%-ZH calibration mix low-bit damage concentrates in the model's Chinese mass, and this targets exactly that. Same recipe, size class and speed; distributional fidelity jumps:
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- | KL / top-1 flip vs the 4.5 bpw reference (T=3072) | pre-DWQ | **DWQ (main)** |
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- |---|---|---|
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- | EN | 0.727 / 24.9% | **0.383 / 15.6%** |
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- | code | 0.252 / 12.7% | **0.193 / 10.2%** |
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- | ZH | 0.987 / 35.7% | **0.562 / 21.9%** |
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- | overall | 0.655 / 24.4% | **0.379 / 15.9% (−42% KL)** |
 
 
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- The pre-DWQ weights remain available on the [`pre-dwq`](https://huggingface.co/avlp12/GLM-5.2-Alis-MLX-Dynamic-2.56bpw/tree/pre-dwq) branch. **The *Quality* and *Benchmarks* figures below are measured on these DWQ weights** — the retune also moves perplexity (strided wikitext 4.34 → 3.77, code 2.20 2.07; `mlx_lm.perplexity` on tulu-3 3.85 → 3.56), not just the KL above.
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  ## Metrics
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@@ -44,7 +46,7 @@ The pre-DWQ weights remain available on the [`pre-dwq`](https://huggingface.co/a
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  |---|---|
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  | Base model | zai-org/GLM-5.2 (744B total / \~40B active) |
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  | Bits/weight | **\~2.56** (per-tensor mixed) |
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- | On-disk size | **246.9 GB** (48 shards, incl. the 4.5 GB native MTP layer) |
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  | Peak memory | \~242 GB (weights, MTP-attached) · \~249 GB (8K) · \~263 GB (26K) · \~293 GB (64K) · \~344 GB (128K) — **measured** (int8 KV); the DSA prefill activation grows with context |
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  | Format | MLX (Apple Silicon) |
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  | Context | 1M-capable architecture (DSA); **machine-limited in practice** — ≈26–32K prefill on a 256 GiB box (see *Long context & memory*) |
@@ -58,7 +60,7 @@ GLM-5.2 is a frontier agentic-coding MoE, but at 744B it is \~1.5 TB in bf16 —
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  ## Quality
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- This is the **≤256 GB** option — the routed experts are 2-bit, so it is deliberately bit-starved. If you have a 512 GB machine, the **[3.5 bpw build](https://huggingface.co/avlp12/GLM-5.2-Alis-MLX-Dynamic-3.5bpw)** is still better on prose/code strided PPL (−25% wikitext, −11% code; the 3.5 bpw sibling is DWQ-retuned against an 8-bit teacher) and runs a full 1M context.
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  ![Perplexity: this 2.56 bpw build vs the 3.5 bpw build — 2.56 bpw is 25% higher (worse) on wikitext, 11% on code](assets/quality.png)
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@@ -70,13 +72,13 @@ Reproduced with `mlx_lm.evaluate` (0-shot) and `mlx_lm.perplexity` (seq 2048, 50
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  | | GLM-5.1 · 2.7 bpw | **GLM-5.2 · 2.56 bpw (this)** | GLM-5.2 · 3.5 bpw |
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  |---|---|---|---|
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- | Perplexity (lower) | 4.165 | **3.564** | 3.630 |
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- | HellaSwag (acc_norm) | 0.606 | **0.652** | 0.604 |
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- | PIQA (acc) | 0.796 | **0.808** | 0.822 |
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  | WinoGrande (acc) | 0.660 | **0.780** | 0.780 |
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  | Generation (tok/s) | 18.35 | **22.87** | 21.29 |
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- Perplexity here is on `allenai/tulu-3-sft-mixture` (the `mlx_lm.perplexity` default) — a different corpus and method from the wikitext strided figure above, so values are not comparable across the two. Task accuracies use a 500-sample limit (CI ±0.02–0.04). GLM-5.1 is a different (older) base model, so cross-generation gaps reflect both the newer model and quantization.
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  **Quantization recipe**
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  **New:** the checkpoint now ships GLM-5.2's **native MTP (nextn) layer** for self-speculative decoding (`--mtp` — see [*Native MTP*](#native-mtp--self-speculative-decoding)). Fully backward-compatible: runtimes without MTP support strip the extra layer and behave exactly as before.
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+ **Update 2 (2026-07): anchor-guarded clip + DWQ re-run.** `main` is now rebuilt from a **Q8 source** with an anchor-guarded clip search (per-group outlier clipping at max-err slack 1.1 that preserves the min-max anchor weights; method in [alis-dwq](https://github.com/avlp12/alis-dwq)), then DWQ-retuned with the same recipe as before (4.5 bpw-teacher targets, 45%-ZH calibration, upstream flag [mlx-lm#1499](https://github.com/ml-explore/mlx-lm/pull/1499)). Held-out perplexity improves or holds everywhere vs the previous DWQ main: strided wikitext **3.774 3.698 (−2.0%)**, code **2.069 → 2.054**, tulu-3 flat (3.564 → 3.571 ±0.027); the clip alone moves the raw pre-DWQ build 4.34 4.17. The checkpoint also sheds 4.5 GB: the MTP layer used to ship twice (a module-named copy inside the base shards plus the standalone MTP shard), and now ships once.
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+ | KL / top-1 flip vs the 4.5 bpw reference (T=3072) | pre-DWQ | first DWQ (`dwq-noclip`) | **clip+DWQ (main)** |
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+ |---|---|---|---|
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+ | EN | 0.727 / 24.9% | 0.383 / 15.6% | 0.464 / 17.3% |
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+ | code | 0.252 / 12.7% | 0.193 / 10.2% | **0.183 / 10.0%** |
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+ | ZH | 0.987 / 35.7% | 0.562 / 21.9% | 0.610 / 24.8% |
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+ | overall | 0.655 / 24.4% | 0.379 / 15.9% | 0.419 / 17.4% |
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+
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+ *How to read this table: the reference is the 4.5 bpw **quantized** sibling, not ground truth. The first DWQ was derived from the same 4-bit-lattice family as that reference, so it sits unusually close to it; the clip step re-derives every tensor from a Q8 source (removing the lattice-resonance failure mode), which drifts slightly away from this particular reference even as held-out perplexity — the metric that tracks real quality — improves. Judge builds by the PPL numbers.* Greedy loop-probe (256 tok × EN/code/ZH): clean, no cycles.
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+ Weights history: original quant on [`pre-dwq`](https://huggingface.co/avlp12/GLM-5.2-Alis-MLX-Dynamic-2.56bpw/tree/pre-dwq) · first DWQ retune on [`dwq-noclip`](https://huggingface.co/avlp12/GLM-5.2-Alis-MLX-Dynamic-2.56bpw/tree/dwq-noclip) · current `main` = clip + DWQ.
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  ## Metrics
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  |---|---|
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  | Base model | zai-org/GLM-5.2 (744B total / \~40B active) |
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  | Bits/weight | **\~2.56** (per-tensor mixed) |
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+ | On-disk size | **242.4 GB** (47 shards: 46 base + the 4.5 GB native MTP layer, which no longer ships twice) |
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  | Peak memory | \~242 GB (weights, MTP-attached) · \~249 GB (8K) · \~263 GB (26K) · \~293 GB (64K) · \~344 GB (128K) — **measured** (int8 KV); the DSA prefill activation grows with context |
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  | Format | MLX (Apple Silicon) |
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  | Context | 1M-capable architecture (DSA); **machine-limited in practice** — ≈26–32K prefill on a 256 GiB box (see *Long context & memory*) |
 
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  ## Quality
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+ This is the **≤256 GB** option — the routed experts are 2-bit, so it is deliberately bit-starved. If you have a 512 GB machine, the **[3.5 bpw build](https://huggingface.co/avlp12/GLM-5.2-Alis-MLX-Dynamic-3.5bpw)** is still better on prose/code strided PPL (−25% wikitext, −11% code; both builds are clip+DWQ retunes, the 3.5 bpw sibling against an 8-bit teacher) and runs a full 1M context.
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  ![Perplexity: this 2.56 bpw build vs the 3.5 bpw build — 2.56 bpw is 25% higher (worse) on wikitext, 11% on code](assets/quality.png)
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  | | GLM-5.1 · 2.7 bpw | **GLM-5.2 · 2.56 bpw (this)** | GLM-5.2 · 3.5 bpw |
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  |---|---|---|---|
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+ | Perplexity (lower) | 4.165 | **3.571** | 3.644 |
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+ | HellaSwag (acc_norm) | 0.606 | **0.652** | 0.626 |
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+ | PIQA (acc) | 0.796 | **0.808** | 0.838 |
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  | WinoGrande (acc) | 0.660 | **0.780** | 0.780 |
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  | Generation (tok/s) | 18.35 | **22.87** | 21.29 |
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+ Perplexity here is on `allenai/tulu-3-sft-mixture` (the `mlx_lm.perplexity` default) — a different corpus and method from the wikitext strided figure above, so values are not comparable across the two. Task accuracies use a 500-sample limit (CI ±0.02–0.04). This column's perplexity is measured on the current `main` (clip+DWQ); its task accuracies were measured on the previous retune (now `dwq-noclip`) — a task-accuracy re-run on the current `main` is queued. The 3.5 bpw column is that build's current `main` (all re-measured). GLM-5.1 is a different (older) base model, so cross-generation gaps reflect both the newer model and quantization.
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  **Quantization recipe**
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