🎡 MiniMax Music 3 (Axon MLQT v1.1a · Dual-Block BLK32/BLK64 Packed Edition)

Engineered by Axon Labs β€” 3-Trit Ternary Quantization + 0-SKIP Sparsity + Outlier-Preserving Dual-Block Routing

πŸ’‘ Overview

MiniMax Music 3 풀솑 생성 λͺ¨λΈμ˜ 검증 μ™„λ£Œ(v1.1a) νŒ¨ν‚Ή μ–‘μžν™” κ°€μ€‘μΉ˜. λͺ¨λ“  μˆ˜μΉ˜λŠ” 2026-08-26 μ‹€μΈ‘κ°’μž…λ‹ˆλ‹€ (RTX 3060 12GB / ComfyUI 0.33.0).

Component Original MLQT v1.1a Packed Ratio
DiT (diffusion transformer) 4.58 GB (FP16) 0.67 GB 14.7%
Text Encoder & AR Qwen3 8.57 GB (INT8 convrot) 3.56 GB 41.6%
Audio VAE (dav) 0.20 GB 0.20 GB (무손싀 보쑴) 100%
Total weights 13.35 GB 4.43 GB 66.8% 절감

λΌμš°νŒ… ν—Œμž₯ (Dual-Block)

  • BLK32 μ •λ°€ (블둝당 독립 μŠ€μΌ€μΌ): μ˜€λ””μ˜€/보컬/크둜슀 μ–΄ν…μ…˜ 경둜 β€” audio 포함 ν…μ„œ μ΅œμš°μ„ , attention 계열, λ―ΈλΆ„λ₯˜ ν…μ„œ(μ•ˆμ „ κΈ°λ³Έ)
  • BLK64 μ΄ˆκ²½λŸ‰: FFN/MLP λŒ€ν˜• ν–‰λ ¬ (ffn, mlp.*, ff.*, gate_/up_/down_proj, gate_up)
  • 민감 ν…μ„œ(norm/bias/embed/head/tokenizer_json U8)λŠ” 원본 dtype 무손싀 보쑴

βœ… 독립 검증 μ„±μ ν‘œ (μ œμž‘μž ν΄λ ˆμž„ μ•„λ‹Œ 제3자 도ꡬ 감사)

Gate κ²°κ³Ό
safetensors ν‘œμ€€ 헀더 역직렬화 PASS (DiT/TE)
νŒ¨ν‚Ή λ°”μ΄νŠΈ μˆ˜ν•™ (codes=ceil(numelΓ—2bit/8), scales=n_blocks) PASS (149+161 κ·Έλ£Ή)
λΌμš°νŒ… μ‹€μΈ‘ vs 메타 ν΄λ ˆμž„ λ“œλ¦¬ν”„νŠΈ 0
int8 λ””μ½˜ μ •ν•©μ„± (vs 원본 bf16, down_proj) cosine 0.999956
tokenizer_json dtype 보쑴 U8 μœ μ§€ PASS
싀생성 음ν–₯ ('λ©ˆμΆ°λ²„λ¦° μ‹œκ³„λ“€' 60s) 클리핑 0건 Β· λ¬΄μŒλΉ„ 0.14% Β· Peak βˆ’7.7 dBFS Β· RMS βˆ’24.74 dBFS Β· 크레슀트 17.03 dB

πŸš€ Quick Start (ComfyUI)

  1. μ»€μŠ€ν…€ λ…Έλ“œ μ„€μΉ˜: ComfyUI-MiniMaxMusic3-MLQT β†’ custom_nodes/
  2. 배치:
    • minimax_music3_dit_3trit_0skip_mlqt.safetensors β†’ models/diffusion_models/
    • minimax_music3_text_encoder_3trit_0skip_mlqt.safetensors β†’ models/text_encoders/
    • minimax_music3_dav.safetensors β†’ models/vae/
  3. μ›Œν¬ν”Œλ‘œμš°μ—μ„œ MiniMax Music 3 (MLQT Direct Loader) 둜 μ„Έ 파일 선택 ν›„ Queue.
    • λ…Έλ“œκ°€ .mlqt_trits νŒ¨ν‚Ήμ„ μžλ™ 감지 β†’ λ‘œλ“œ μ‹œ dense fp16으둜 볡원(κΈ°μ‘΄ μΆ”λ‘  경둜 ν˜Έν™˜).

πŸ“ 파일 포맷 (v1.1a Packed, ν‘œμ€€ safetensors)

<key>.mlqt_trits : U8  2-bit μ½”λ“œ Γ—4/λ°”μ΄νŠΈ ({0:-1, 1:0, 2:+1})
<key>.mlqt_scale : F16 블둝별 alpha
<key>.mlqt_shape : I32 논리 shape
<key>.mlqt_meta  : U8  JSON {"numel": N, "block": 32|64}

⏱️ 생성 μ‹œκ°„ μ‹€μΈ‘ (RTX 3060 12GB, μ €VRAM μ˜€ν”„λ‘œλ“œ ν™œμ„±)

60초 곑 κΈ°μ€€: AR 토큰 μ•½ 27λΆ„ 48초 + DiT 25μŠ€ν… μ•½ 2λΆ„ 30초 + VAE λ””μ½”λ“œ. β€» μ˜€ν”„λ‘œλ“œ λΉ„ν™œμ„± ν™˜κ²½(μ—¬μœ  VRAM β‰₯ 11GB)μ—μ„œλŠ” μœ μ˜ν•˜κ²Œ 단좕될 수 있음.

🧾 μ •μ§ν•œ 벀치마크 λ…ΈνŠΈ

κ³Όκ±° 곡개 ν΄λ ˆμž„(10λΆ„ 생성 λ“±)은 INT8 경둜 κΈ°μ€€ μΆ”μ •μΉ˜λ‘œ ν™•μΈλ˜λ©°, λ³Έ λ¦΄λ¦¬μ¦ˆλΆ€ν„°λŠ” μœ„ μ‹€μΈ‘κ°’λ§Œ μ‚¬μš©ν•©λ‹ˆλ‹€. μž¬ν˜„ 슀크립트: verify_mlqt_v11a.py, run_masterpiece_mlqt_verify.py.


πŸ’Ό Axon Labs Enterprise Quantization Services

  • Website: https://axonlabs.ai Β· Contact: contact@axonlabs.ai
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