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Author SHA1 Message Date
Alexander Whitestone
dabb96d315 docs: record Qwen3.5-9B DFlash Metal timeout (refs #152, #154)
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2026-04-21 22:25:25 -04:00
Alexander Whitestone
69cef8a90f bench: record Apple Silicon DFlash pilot result (refs #152)
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Smoke Test / smoke (pull_request) Successful in 18s
2026-04-21 22:20:15 -04:00
Alexander Whitestone
636d294896 feat: add Apple Silicon DFlash benchmark planner (refs #152)
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2026-04-21 22:00:22 -04:00
9 changed files with 539 additions and 6 deletions

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@@ -30,3 +30,4 @@ See [issues](https://forge.alexanderwhitestone.com/Timmy_Foundation/turboquant/i
## Docs
- [Project Status](docs/PROJECT_STATUS.md) — Full project status and build specification
- [DFlash on Apple Silicon](docs/DFLASH_APPLE_SILICON.md) — MLX benchmark planner, setup commands, and report workflow

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@@ -0,0 +1,189 @@
#!/usr/bin/env python3
"""Apple Silicon DFlash planning helpers and CLI (issue #152)."""
from __future__ import annotations
import argparse
import json
import platform
import subprocess
from dataclasses import asdict, dataclass
from pathlib import Path
from typing import Iterable, Optional
@dataclass(frozen=True)
class DFlashPair:
slug: str
base_model: str
draft_model: str
estimated_total_weights_gb: float
minimum_recommended_memory_gb: float
draft_sliding_window_size: int = 4096
SUPPORTED_PAIRS: tuple[DFlashPair, ...] = (
DFlashPair(
slug="qwen35-4b",
base_model="Qwen/Qwen3.5-4B",
draft_model="z-lab/Qwen3.5-4B-DFlash",
estimated_total_weights_gb=9.68,
minimum_recommended_memory_gb=16.0,
),
DFlashPair(
slug="qwen35-9b",
base_model="Qwen/Qwen3.5-9B",
draft_model="z-lab/Qwen3.5-9B-DFlash",
estimated_total_weights_gb=19.93,
minimum_recommended_memory_gb=28.0,
),
)
def detect_total_memory_gb() -> float:
"""Detect total system memory in GiB, rounded to a whole number for planning."""
system = platform.system()
if system == "Darwin":
mem_bytes = int(subprocess.check_output(["sysctl", "-n", "hw.memsize"]).strip())
return round(mem_bytes / (1024 ** 3), 1)
if system == "Linux":
with open("/proc/meminfo", "r", encoding="utf-8") as handle:
for line in handle:
if line.startswith("MemTotal:"):
mem_kb = int(line.split()[1])
return round(mem_kb / (1024 ** 2), 1)
raise RuntimeError(f"Unsupported platform for memory detection: {system}")
def get_pair(slug: str) -> DFlashPair:
for pair in SUPPORTED_PAIRS:
if pair.slug == slug:
return pair
raise ValueError(f"Unknown DFlash pair: {slug}")
def select_pair(total_memory_gb: float, preferred_slug: Optional[str] = None) -> DFlashPair:
"""Pick the strongest upstream-supported pair likely to fit the machine."""
if preferred_slug:
return get_pair(preferred_slug)
fitting = [pair for pair in SUPPORTED_PAIRS if total_memory_gb >= pair.minimum_recommended_memory_gb]
if fitting:
return max(fitting, key=lambda pair: pair.minimum_recommended_memory_gb)
return SUPPORTED_PAIRS[0]
def build_mlx_benchmark_command(
pair: DFlashPair,
*,
dataset: str = "gsm8k",
max_samples: int = 128,
enable_thinking: bool = True,
) -> str:
"""Build the upstream MLX benchmark command from the DFlash README."""
parts = [
"python -m dflash.benchmark --backend mlx",
f"--model {pair.base_model}",
f"--draft-model {pair.draft_model}",
f"--dataset {dataset}",
f"--max-samples {max_samples}",
]
if enable_thinking:
parts.append("--enable-thinking")
parts.append(f"--draft-sliding-window-size {pair.draft_sliding_window_size}")
return " \\\n ".join(parts)
def build_setup_commands(pair: DFlashPair) -> list[str]:
return [
"python3 -m venv .venv-dflash",
"source .venv-dflash/bin/activate",
"git clone https://github.com/z-lab/dflash.git",
"cd dflash",
"pip install -e .[mlx]",
build_mlx_benchmark_command(pair),
]
def render_report_template(machine_label: str, pair: DFlashPair) -> str:
command = build_mlx_benchmark_command(pair)
return f"""# DFlash Apple Silicon Benchmark Report
## Machine
- Label: {machine_label}
- Selected pair: {pair.slug}
- Base model: {pair.base_model}
- Draft model: {pair.draft_model}
- Estimated total weight footprint: {pair.estimated_total_weights_gb:.2f} GB
## Setup
```bash
python3 -m venv .venv-dflash
source .venv-dflash/bin/activate
git clone https://github.com/z-lab/dflash.git
cd dflash
pip install -e .[mlx]
{command}
```
## Baseline comparison
Compare against **plain MLX or llama.cpp speculative decoding** on the same prompt set.
## Results
- Throughput (tok/s):
- Peak memory (GB):
- Notes on acceptance / behavior:
## Verdict
Worth operationalizing locally?
- [ ] Yes
- [ ] No
- [ ] Needs more data
## Recommendation
Explain whether this should become part of the local inference stack.
"""
def build_plan(total_memory_gb: float, preferred_slug: Optional[str] = None) -> dict:
pair = select_pair(total_memory_gb=total_memory_gb, preferred_slug=preferred_slug)
return {
"machine_memory_gb": total_memory_gb,
"selected_pair": asdict(pair),
"setup_commands": build_setup_commands(pair),
"benchmark_command": build_mlx_benchmark_command(pair),
"baseline_note": "Compare against plain MLX or llama.cpp speculative decoding on the same prompt set.",
}
def write_output(path: Path, content: str) -> None:
path.parent.mkdir(parents=True, exist_ok=True)
path.write_text(content, encoding="utf-8")
def main(argv: Optional[Iterable[str]] = None) -> int:
parser = argparse.ArgumentParser(description="Plan Apple Silicon DFlash benchmarks")
parser.add_argument("--memory-gb", type=float, default=None, help="Override detected total memory")
parser.add_argument("--pair", choices=[pair.slug for pair in SUPPORTED_PAIRS], default=None)
parser.add_argument("--machine-label", default="Apple Silicon Mac")
parser.add_argument("--format", choices=["json", "markdown"], default="markdown")
parser.add_argument("--output", default=None, help="Write plan/report to file instead of stdout")
args = parser.parse_args(list(argv) if argv is not None else None)
memory_gb = args.memory_gb if args.memory_gb is not None else detect_total_memory_gb()
pair = select_pair(total_memory_gb=memory_gb, preferred_slug=args.pair)
if args.format == "json":
content = json.dumps(build_plan(memory_gb, preferred_slug=pair.slug), indent=2)
else:
content = render_report_template(args.machine_label, pair)
if args.output:
write_output(Path(args.output), content)
else:
print(content)
return 0
if __name__ == "__main__":
raise SystemExit(main())

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@@ -0,0 +1,41 @@
# DFlash Apple Silicon Benchmark Report
## Machine
- Label: M3 Max 36GB
- Selected pair: qwen35-9b
- Base model: Qwen/Qwen3.5-9B
- Draft model: z-lab/Qwen3.5-9B-DFlash
- Estimated total weight footprint: 19.93 GB
## Setup
```bash
python3 -m venv .venv-dflash
source .venv-dflash/bin/activate
git clone https://github.com/z-lab/dflash.git
cd dflash
pip install -e .[mlx]
python -m dflash.benchmark --backend mlx \
--model Qwen/Qwen3.5-9B \
--draft-model z-lab/Qwen3.5-9B-DFlash \
--dataset gsm8k \
--max-samples 128 \
--enable-thinking \
--draft-sliding-window-size 4096
```
## Baseline comparison
Compare against **plain MLX or llama.cpp speculative decoding** on the same prompt set.
## Results
- Throughput (tok/s):
- Peak memory (GB):
- Notes on acceptance / behavior:
## Verdict
Worth operationalizing locally?
- [ ] Yes
- [ ] No
- [ ] Needs more data
## Recommendation
Explain whether this should become part of the local inference stack.

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@@ -0,0 +1,46 @@
# DFlash Apple Silicon Pilot — Qwen3.5-4B on M3 Max 36GB
Date: 2026-04-21
Machine: Apple M3 Max, 36 GB unified memory
Repo issue: #152
## Command
```bash
source /tmp/dflash-venv/bin/activate
cd /tmp/dflash-upstream
python -m dflash.benchmark --backend mlx \
--model Qwen/Qwen3.5-4B \
--draft-model z-lab/Qwen3.5-4B-DFlash \
--dataset gsm8k \
--max-samples 1 \
--enable-thinking \
--draft-sliding-window-size 4096
```
## Result
- Dataset: `gsm8k`
- Samples: `1`
- Baseline throughput: `22.35 tok/s`
- DFlash throughput: `46.78 tok/s`
- Decoding speedup: `2.09x`
- Average acceptance length: `6.48`
Acceptance length histogram:
```text
['0.3%', '11.1%', '12.7%', '10.4%', '11.7%', '7.6%', '7.0%', '3.8%', '5.1%', '6.3%', '2.8%', '3.8%', '2.2%', '1.9%', '0.9%', '2.5%', '9.8%']
```
## Caveats
- This is a **pilot**, not a decision-grade benchmark.
- Only `1` sample was run, so the throughput number is directional.
- No apples-to-apples baseline against plain MLX or llama.cpp speculative decoding is included yet.
- The planner still recommends trying `Qwen/Qwen3.5-9B + z-lab/Qwen3.5-9B-DFlash` on this machine for the more meaningful fit test.
## Interim takeaway
DFlash is **real on Apple Silicon** and already shows a meaningful local speedup on a small matched pair.
A `2.09x` pilot speedup on `Qwen3.5-4B` is enough evidence to keep pushing toward a proper benchmark slice in this repo.

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@@ -0,0 +1,59 @@
# DFlash on Apple Silicon Failure Report — Qwen3.5-9B on M3 Max 36GB
Date: 2026-04-21
Machine: Apple M3 Max, 36 GB unified memory
Repo issue: #152
## Command
```bash
source /tmp/dflash-venv/bin/activate
cd /tmp/dflash-upstream
python -m dflash.benchmark --backend mlx \
--model Qwen/Qwen3.5-9B \
--draft-model z-lab/Qwen3.5-9B-DFlash \
--dataset gsm8k \
--max-samples 1 \
--enable-thinking \
--draft-sliding-window-size 4096
```
## Outcome
The benchmark did **not** complete successfully on this machine.
### Failure signature
```text
libc++abi: terminating due to uncaught exception of type std::runtime_error:
[METAL] Command buffer execution failed:
Caused GPU Timeout Error (00000002:kIOGPUCommandBufferCallbackErrorTimeout)
```
Additional shutdown noise:
```text
bash: [11285: 1] tcsetattr: Inappropriate ioctl for device
resource_tracker: There appear to be 1 leaked semaphore objects to clean up at shutdown
```
## Interpretation
This is strong evidence that the `Qwen/Qwen3.5-9B + z-lab/Qwen3.5-9B-DFlash` pair is **not currently stable** on an M3 Max 36GB Mac under the upstream MLX benchmark path, at least with the default settings used here.
It may still be salvageable with:
- smaller block size / different benchmark settings
- a shorter generation target
- a different prompt sample
- upstream MLX / Metal fixes
- newer Apple Silicon hardware
But as of this run, it should be treated as **experimental / failing** on this exact machine.
## Recommendation
For this Mac, the working local proof path is still:
- `Qwen/Qwen3.5-4B`
- `z-lab/Qwen3.5-4B-DFlash`
Use the 4B pair for reproducible local validation while the 9B Metal timeout is investigated separately.

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@@ -0,0 +1,125 @@
# DFlash on Apple Silicon
This repo now carries a **Gitea-first benchmark harness** for evaluating whether upstream **DFlash on MLX** is worth adding to the local Apple Silicon inference stack.
## Why
The headline `Kimi K2.6 + DFlash` benchmark was measured on `8x MI300X` with huge RAM and ROCm patches. That exact recipe is not a fit for a `36 GB` Apple Silicon Mac.
What *is* relevant locally is the upstream `z-lab/dflash` MLX path, which can benchmark smaller matched target/draft pairs that fit on Apple Silicon.
## Current repo entry point
Use:
```bash
python3 benchmarks/dflash_apple_silicon.py --machine-label "M3 Max 36GB"
```
This prints a benchmark report template with:
- the selected model/draft pair
- exact setup commands
- the upstream MLX benchmark command
- baseline comparison guidance
Write the template to a file:
```bash
python3 benchmarks/dflash_apple_silicon.py \
--machine-label "M3 Max 36GB" \
--output benchmarks/reports/dflash_m3max_36gb.md
```
Emit the underlying plan as JSON:
```bash
python3 benchmarks/dflash_apple_silicon.py --format json
```
## Selection logic
Today the planner uses two upstream-supported MLX pairs:
- `qwen35-9b`
- base: `Qwen/Qwen3.5-9B`
- draft: `z-lab/Qwen3.5-9B-DFlash`
- chosen for ~28 GB+ machines
- `qwen35-4b`
- base: `Qwen/Qwen3.5-4B`
- draft: `z-lab/Qwen3.5-4B-DFlash`
- fallback for tighter-memory Macs
On a `36 GB` Mac, the default recommendation is `qwen35-9b`.
## Pilot result already landed
A first live Apple Silicon run has already been captured in:
- `benchmarks/reports/dflash_m3max_36gb_qwen35_4b_pilot.md`
Pilot command:
```bash
python -m dflash.benchmark --backend mlx \
--model Qwen/Qwen3.5-4B \
--draft-model z-lab/Qwen3.5-4B-DFlash \
--dataset gsm8k \
--max-samples 1 \
--enable-thinking \
--draft-sliding-window-size 4096
```
Pilot outcome on this Mac:
- baseline throughput: `22.35 tok/s`
- DFlash throughput: `46.78 tok/s`
- decoding speedup: `2.09x`
Treat that as a **directional proof**, not a final decision benchmark. The next step is the fuller comparison slice against plain MLX or llama.cpp speculative decoding.
## Known 9B failure on this machine
A follow-up live run with:
- `Qwen/Qwen3.5-9B`
- `z-lab/Qwen3.5-9B-DFlash`
failed on this same M3 Max 36GB Mac with:
```text
[METAL] Command buffer execution failed:
Caused GPU Timeout Error (00000002:kIOGPUCommandBufferCallbackErrorTimeout)
```
That failure is recorded in:
- `benchmarks/reports/dflash_m3max_36gb_qwen35_9b_timeout.md`
So the current guidance is:
- treat `qwen35-9b` as **experimental** on this machine
- treat `qwen35-4b` as the current **known-working local proof path**
- keep the issue open until we either stabilize the 9B path or clearly rule it out for this hardware tier
## Upstream benchmark command
The harness uses the upstream MLX benchmark syntax from `z-lab/dflash`:
```bash
python -m dflash.benchmark --backend mlx \
--model Qwen/Qwen3.5-9B \
--draft-model z-lab/Qwen3.5-9B-DFlash \
--dataset gsm8k \
--max-samples 128 \
--enable-thinking \
--draft-sliding-window-size 4096
```
## What remains
This PR adds the **planner + report template** so the benchmark is reproducible from the repo.
The issue remains open until a real Apple Silicon run lands with:
- measured throughput
- measured memory
- a baseline comparison against plain MLX or llama.cpp speculative decoding
- a recommendation on whether to operationalize DFlash locally

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@@ -379,8 +379,8 @@ def select_quant_level(
break
if chosen is None:
# Nothing fits — pick the most aggressive compression
chosen = QUANT_LEVELS[-1]
# Nothing fits — pick the most aggressive compression, not the q4_0 fallback.
chosen = max(QUANT_LEVELS, key=lambda level: level.compression_ratio)
logger.warning(f"No quant level fits in {memory_pool_gb:.1f}GB. Using {chosen.name}.")
# Calculate final numbers

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@@ -0,0 +1,58 @@
#!/usr/bin/env python3
"""Tests for Apple Silicon DFlash benchmark planning helpers (issue #152)."""
import os
import sys
from unittest.mock import patch
sys.path.insert(0, os.path.dirname(os.path.dirname(__file__)))
from benchmarks.dflash_apple_silicon import ( # noqa: E402
build_mlx_benchmark_command,
detect_total_memory_gb,
render_report_template,
select_pair,
)
class TestPairSelection:
def test_prefers_qwen35_9b_on_36gb_mac(self):
pair = select_pair(total_memory_gb=36)
assert pair.slug == "qwen35-9b"
assert pair.base_model == "Qwen/Qwen3.5-9B"
assert pair.draft_model == "z-lab/Qwen3.5-9B-DFlash"
def test_falls_back_to_4b_when_memory_is_tight(self):
pair = select_pair(total_memory_gb=20)
assert pair.slug == "qwen35-4b"
assert pair.base_model == "Qwen/Qwen3.5-4B"
class TestCommandGeneration:
def test_builds_upstream_mlx_benchmark_command(self):
pair = select_pair(total_memory_gb=36)
command = build_mlx_benchmark_command(pair, dataset="gsm8k", max_samples=64)
assert "python -m dflash.benchmark --backend mlx" in command
assert "--model Qwen/Qwen3.5-9B" in command
assert "--draft-model z-lab/Qwen3.5-9B-DFlash" in command
assert "--dataset gsm8k" in command
assert "--max-samples 64" in command
assert "--draft-sliding-window-size 4096" in command
class TestReportTemplate:
def test_report_template_mentions_baseline_and_verdict(self):
pair = select_pair(total_memory_gb=36)
report = render_report_template(machine_label="M3 Max 36GB", pair=pair)
assert "DFlash Apple Silicon Benchmark Report" in report
assert "M3 Max 36GB" in report
assert "Qwen/Qwen3.5-9B" in report
assert "plain MLX or llama.cpp speculative decoding" in report
assert "Worth operationalizing locally?" in report
class TestMemoryDetection:
@patch("benchmarks.dflash_apple_silicon.platform.system", return_value="Darwin")
@patch("benchmarks.dflash_apple_silicon.subprocess.check_output", return_value=b"38654705664\n")
def test_detect_total_memory_gb_on_macos(self, _mock_sysctl, _mock_system):
assert detect_total_memory_gb() == 36.0

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@@ -19,10 +19,11 @@ from evolution.quant_selector import (
class TestQuantLevels:
def test_levels_ordered_by_quality(self):
"""Levels should be ordered from best quality to most aggressive."""
for i in range(len(QUANT_LEVELS) - 1):
assert QUANT_LEVELS[i].bits_per_channel > QUANT_LEVELS[i + 1].bits_per_channel
def test_levels_keep_turboquant_quality_order_with_q4_fallback_last(self):
"""TurboQuant levels should lead, with q4_0 reserved as the non-Turbo fallback."""
names = [level.name for level in QUANT_LEVELS]
assert names[:3] == ["turbo4", "turbo3", "turbo2"]
assert names[-1] == "q4_0"
def test_all_levels_have_required_fields(self):
for level in QUANT_LEVELS:
@@ -148,6 +149,19 @@ class TestSelection:
sel = select_quant_level(model_size_gb=16.0, context_length=65536)
assert len(sel.warnings) > 0
def test_falls_back_to_turbo2_when_nothing_fits(self):
with patch("evolution.quant_selector.detect_hardware") as mock_hw:
mock_hw.return_value = HardwareInfo(
total_memory_gb=8,
available_memory_gb=6,
gpu_memory_gb=8,
gpu_name="Tiny GPU",
cpu_cores=4,
detection_method="mock",
)
sel = select_quant_level(model_size_gb=16.0, context_length=131072)
assert sel.level.name == "turbo2"
def test_reasoning_contains_key_info(self):
with patch("evolution.quant_selector.detect_hardware") as mock_hw:
mock_hw.return_value = HardwareInfo(