ACE-Step 1.5 XL — Task Arithmetic Merged DiT Models (GGUF)

Quantized GGUF versions of task-arithmetic merged ACE-Step v1.5 XL DiT models, ready for use with C++ inference engines.

What Are These?

These are DiT (Diffusion Transformer) models created by merging the official ACE-Step v1.5 XL checkpoints using task arithmetic. Task arithmetic blends the learned "task vectors" of two fine-tuned models at a controlled interpolation ratio, producing models that inherit qualities from both parents.

Each model blends two of the three official XL checkpoints:

λ = 0 means pure Parent A, λ = 1 means pure Parent B.

Why Merge?

• SFT × Turbo blends combine SFT's strong lyric adherence and musical structure with Turbo's faster convergence and energy
• Base × Turbo blends bring Base's raw generative range together with Turbo's efficiency
• Different ratios let you dial the trade-off to taste — lower λ for more structure, higher λ for more speed

Architecture

All three models share the XL architecture:

Available Quantizations

Each model is provided in 5 quantization levels:

File Listing

acestep-v15-merge-base-turbo-xl-ta-0.5-BF16.gguf
acestep-v15-merge-base-turbo-xl-ta-0.5-Q4_K_M.gguf
acestep-v15-merge-base-turbo-xl-ta-0.5-Q5_K_M.gguf
acestep-v15-merge-base-turbo-xl-ta-0.5-Q6_K.gguf
acestep-v15-merge-base-turbo-xl-ta-0.5-Q8_0.gguf

acestep-v15-merge-sft-turbo-xl-ta-0.3-BF16.gguf
acestep-v15-merge-sft-turbo-xl-ta-0.3-Q4_K_M.gguf
acestep-v15-merge-sft-turbo-xl-ta-0.3-Q5_K_M.gguf
acestep-v15-merge-sft-turbo-xl-ta-0.3-Q6_K.gguf
acestep-v15-merge-sft-turbo-xl-ta-0.3-Q8_0.gguf

acestep-v15-merge-sft-turbo-xl-ta-0.7-BF16.gguf
acestep-v15-merge-sft-turbo-xl-ta-0.7-Q4_K_M.gguf
acestep-v15-merge-sft-turbo-xl-ta-0.7-Q5_K_M.gguf
acestep-v15-merge-sft-turbo-xl-ta-0.7-Q6_K.gguf
acestep-v15-merge-sft-turbo-xl-ta-0.7-Q8_0.gguf

Compatibility

These GGUF files are DiT-only — they replace the --dit argument in the inference pipeline. You still need the standard LM, text encoder, and VAE models alongside them.

acestep.cpp

Drop any of these GGUF files into the models/ directory and pass via --dit:

./build/ace-server \
    --host 0.0.0.0 --port 8090 \
    --lm models/acestep-5Hz-lm-4B-Q8_0.gguf \
    --embedding models/Qwen3-Embedding-0.6B-Q8_0.gguf \
    --dit models/acestep-v15-merge-sft-turbo-xl-ta-0.3-Q8_0.gguf \
    --vae models/vae-BF16.gguf

HOT-Step-CPP

Place the GGUF files in the engine's models/ directory. The model will appear in the DiT model dropdown in the web UI automatically.

Required Companion Models

These DiT GGUFs must be used alongside:

Companion models are available from Serveurperso/ACE-Step-1.5-GGUF.

Recommended Settings

Since these are non-turbo (is_turbo: false) merged models, they use base-mode scheduling:

Note: Higher step counts are needed compared to turbo models. These models trade speed for quality and creative range.

How These Were Made

1. Source checkpoints: Official ACE-Step v1.5 XL safetensors (Base, SFT, Turbo)
2. Merge method: Task arithmetic — θ_merged = θ_A + λ(θ_B − θ_A)
3. Conversion: Safetensors → GGUF BF16 via convert.py from acestep.cpp
4. Quantization: BF16 → Q4_K_M / Q5_K_M / Q6_K / Q8_0 via the acestep.cpp quantize tool

License

These models inherit the license from the upstream ACE-Step v1.5 checkpoints. See the ACE-Step repository for details.

Credits

• ACE-Step — Original model architecture and training by the ACE-Step team
• acestep.cpp — C++ inference engine and GGUF tooling by Serveurperso
• HOT-Step-CPP — Full-stack music generation app by scragnog
• Task arithmetic merges — Produced by scragnog