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turboquant/benchmarks/reports/dflash_m3max_36gb.md
Alexander Whitestone 636d294896
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feat: add Apple Silicon DFlash benchmark planner (refs #152)
2026-04-21 22:00:22 -04:00

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# 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.