Instructions to use KaedeTai/dflash2-mlx-quantized-draft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use KaedeTai/dflash2-mlx-quantized-draft with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir dflash2-mlx-quantized-draft KaedeTai/dflash2-mlx-quantized-draft
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
File size: 1,480 Bytes
78c877d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 | {
"machine": "Apple M5 Max, 137 GB, macOS 26.4.1",
"stack": {
"mlx": "0.32.0",
"mlx_lm": "0.31.3"
},
"protocol": "interleaved A/B, 90s cooldown before each measurement, greedy, 300 tokens, K=4, GPU verified idle",
"draft_comparison": {
"target": "tozp/Qwen3.8-27B-OBLITERATED-V2-mlx-4bit",
"bf16_draft": {
"repo": "z-lab/Qwen3.8-27B-DFlash2",
"size_gb": 3.85,
"tok_per_s": [
59.8,
60.3
],
"accept_pct": [
87.9,
87.9
]
},
"q4_draft": {
"repo": "ProCreations/Qwen3.8-27B-DFlash2-MLXFast-Q4",
"size_gb": 1.27,
"tok_per_s": [
76.1,
76.0
],
"accept_pct": [
86.9,
86.9
]
},
"delta": {
"tok_per_s_pct": 26.4,
"accept_pp": -1.0,
"memory_gb": -2.58
}
},
"target_comparison_bf16_draft": {
"mxfp4": {
"dense": [
35.4,
35.0,
35.6
],
"dflash": [
54.0,
54.1,
53.8
],
"accept_pct": 82,
"token_exact": true
},
"heretic_ara": {
"dense": [
33.0,
33.3,
33.5
],
"dflash": [
61.7,
62.2,
62.3
],
"accept_pct": 89,
"token_exact": false
},
"obliterated_v2": {
"dense": [
33.0,
33.3,
33.6
],
"dflash": [
61.2,
61.4,
61.6
],
"accept_pct": 88,
"token_exact": true
}
},
"server_verification": {
"load_s": 0.9,
"accept_rate": 0.917,
"tok_per_s": 75.4
},
"thermal_drift_uncontrolled": {
"same_measurement_start": 34.9,
"after_3min": 26.8,
"pct": -23
}
} |