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fix(local-model): the MLX row of Muse Glimmer takes a 5 GB peak, and says what was compared
Three corrections to the row added in 5396e33b, none of which changes where it is offered:
- Its peak. The run gave the process footprint's LIFETIME maximum, read at the end: 3.0 to
3.3 GB above what was held then. That is a floor, because a larger transient during the
earlier, longer prompts would not show in it. The row now takes the first measured row's
5 GB: 36.1 GB at 65,536 tokens (0.960 of a 48 GB Mac's estimate) and 39.0 GB at 131,072
(0.972 of what that Mac's runtime measures).
- What was compared. The two builds were not given the same prompt in OpenCode: the GGUF
build got a one-line task through the skill's sendmark (which adds its answer-file
sentence), the MLX build a plain one-line prompt. And the speeds to set side by side are
the two from the same 300-token request, 15.2 and 30.2.
- Runtime issue 18269: whether the memory fix its maintainer promised predates the pinned
runtime is not known, and the header says so.
Also a stale comment: the catalogue holds eleven models.
Co-Authored-By: Claude Fable 5.2 <noreply@anthropic.com>
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@@ -172,10 +172,10 @@ function mlxComputedPerToken(arch: Architecture): number {
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const MEASURED: [number, number, number] = [37_000, 3_000_000_000, 5_000_000_000];
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/**
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* The figures measured for `muse-glimmer:30b-mlx` on the same MacBook Pro (2026-11-12): the upper
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* end of what stayed held per token, the whole prefix budget plus 0.5 GB, and the peak of the
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* process above what stayed held.
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* end of what stayed held per token, the whole prefix budget plus 0.5 GB, and for the peak the
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* first measured row's 5 GB (its own run gave only a floor of 3.0 to 3.3 GB).
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*/
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const MEASURED_MUSE_MLX: [number, number, number] = [45_000, 8 * GIB + 500_000_000, 3_500_000_000];
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const MEASURED_MUSE_MLX: [number, number, number] = [45_000, 8 * GIB + 500_000_000, 5_000_000_000];
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/** What an estimated `mlx` row's three figures must be: computed, scaled by what the measured row showed. */
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function mlxFigures(arch: Architecture): [number, number, number] {
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@@ -427,8 +427,9 @@ describe('the memory figures of the stock rows: each row has its own', () => {
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'north-mini-code-1.0:q4_k_m': [14_144, 3_698_117_120, 0],
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// The same rule: 39 layers x 2,560 cells x 544 bytes = 54,312,960 per copy.
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'muse-glimmer:30b-q4_k_m': [7_072, 2_562_558_464, 0],
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// Measured: the upper end per token, 8 GiB of prefix snapshots + 0.5 GB, the process peak.
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'muse-glimmer:30b-mlx': [45_000, 9_089_934_592, 3_500_000_000],
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// Measured: the upper end per token, 8 GiB of prefix snapshots + 0.5 GB. The peak is the
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// first measured row's: this run gave only a floor for it (3.0 to 3.3 GB).
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'muse-glimmer:30b-mlx': [45_000, 9_089_934_592, 5_000_000_000],
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// State x (1 live + 2 rollback copies + 8 checkpoints) + 1.0 GB + 1 GiB; the prediction
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// layer's cache in f16 per token. The 27B rows below draft 4 tokens: 4 rollback copies.
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'qwen3.6:35b-a3b-mtp-q4_k_m': [12_928, 2_798_242_304, 0],
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@@ -493,9 +493,9 @@ describe('needBytes', () => {
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'north-mini-code-1.0:q4_k_m': 25_999_848_864,
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// At its own window of 131072 tokens: 18.2 GB + 0.9 GB of K/V cache + 2.6 GB.
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'muse-glimmer:30b-q4_k_m': 21_646_509_900,
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// The MLX build at the same window: 19.1 GB + 5.9 GB of cache (every layer at full length,
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// measured) + the 8 GiB of prefix snapshots and 0.5 GB + 3.5 GB of peak.
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'muse-glimmer:30b-mlx': 37_541_796_584,
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// The MLX build at the same window: 19.1 GB + 5.9 GB of cache (45,000 bytes per token,
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// measured) + the 8 GiB of prefix snapshots and 0.5 GB + 5 GB of peak.
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'muse-glimmer:30b-mlx': 39_041_796_584,
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'qwen3.6:35b-a3b-mtp-q4_k_m': 28_808_554_317,
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'qwen3.6:35b-a3b': 35_955_462_956,
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'qwen3.8:27b-q8_0': 44_292_142_594,
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@@ -659,8 +659,8 @@ describe('the MacBook Pro (Mac17,13: Apple M5 Pro, 48 GB)', () => {
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).toEqual([
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// The same model as a GGUF build: its fixed footprint holds the full window, 28.8 GB.
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['qwen3.6:35b-a3b-mtp-q4_k_m', 262144, 'good', 'ok', 41.8, undefined],
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// Muse Glimmer as the MLX build: 34.6 GB at 65536 tokens (0.920 of the estimate), and
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// 5.4 x 3.07 = 16.6 tokens per second. At 131072 it needs 37.5 GB, 0.998: out.
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// Muse Glimmer as the MLX build: 36.1 GB at 65536 tokens (0.960 of the estimate), and
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// 5.4 x 3.07 = 16.6 tokens per second. At 131072 it needs 39.0 GB, 1.04: out.
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['muse-glimmer:30b-mlx', 65536, 'tight', 'ok', 16.6, 'tight'],
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['north-mini-code-1.0:q4_k_m', 262144, 'good', 'ok', 41.8, undefined],
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['mimo-v2.6:9b-q4_k_m', 131072, 'good', 'ok', 28.6, 'small'],
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@@ -911,7 +911,7 @@ describe('every memory size, with the stock catalogue', () => {
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it('offers Muse Glimmer as the MLX build from 48 GB only, and never as the pick of a Mac whose disk has room', () => {
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// Measured on a 48 GB Mac: 45,000 bytes held per token and up to 8 GiB of prefix snapshots,
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// 34.6 GB at 65536 tokens. Runtime issue 18269 reports this build stuck, and a restart, on
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// 36.1 GB at 65536 tokens. Runtime issue 18269 reports this build stuck, and a restart, on
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// a 32 GB Mac: the figures keep it away from there.
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for (const hw of SWEEP) {
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const result = recommend(hw, STOCK, ALL_INSTALLED);
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@@ -2192,17 +2192,17 @@ describe('the measured budget, end to end', () => {
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// The same models in the same order. The share of each changes, and two models step up a
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// context: the 27B in 8 bits fits 65536 tokens under the estimate (0.975) and 131072 under
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// what the runtime reported (0.976), and Muse Glimmer as the MLX build goes from 65536
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// (0.920) to its whole window of 131072 (0.935).
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// (0.960) to its whole window of 131072 (0.972).
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expect(rows(measured).map((c) => c.modelId)).toEqual(rows(estimated).map((c) => c.modelId));
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const stepped = order(estimated).filter((entry, index) => order(measured)[index] !== entry);
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expect(stepped).toEqual(['muse-glimmer:30b-mlx@65536', 'qwen3.8:27b-q8_0@65536']);
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expect(order(measured)).toContain('qwen3.8:27b-q8_0@131072');
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expect(order(measured)).toContain('muse-glimmer:30b-mlx@131072');
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expect(rows(estimated).map((c) => c.budgetShare)).toEqual([
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0.957, 0.767, 0.92, 0.692, 0.303, 0.278, 0.303, 0.853, 0.975, 0.576,
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0.957, 0.767, 0.96, 0.692, 0.303, 0.278, 0.303, 0.853, 0.975, 0.576,
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]);
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expect(rows(measured).map((c) => c.budgetShare)).toEqual([
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0.895, 0.717, 0.935, 0.647, 0.283, 0.26, 0.283, 0.798, 0.976, 0.539,
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0.895, 0.717, 0.972, 0.647, 0.283, 0.26, 0.283, 0.798, 0.976, 0.539,
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]);
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for (const candidate of rows(measured)) {
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expect(candidate.budgetShare).toBeCloseTo(candidate.needBytes / MACBOOK_MEASURED_TOTAL, 3);
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