Agents-A1-MTPLX-Q4
4-bit quantized MLX version of InternScience/Agents-A1 with grafted MTP (Multi-Token Prediction) head for speculative decoding on Apple Silicon.
Model Details
- Base model: InternScience/Agents-A1 (Qwen3.5-MoE architecture, 35B total / 3B active parameters)
- Quantization: 4-bit affine (group size 64), router gates at 8-bit
- MTP head: Grafted from Qwen3.5-35B-A3B (4-bit quantized, 1 layer)
- Format: MLX safetensors
- Disk size: ~18 GB (model) + 1.6 GB (MTP sidecar)
Architecture
- Hidden size: 2048
- Layers: 40 (hybrid linear + full attention)
- Experts: 256 total, 8 active per token
- Vocab: 248,320
- Context: 262,144 tokens
Usage with MTPLX
mtplx start --model wang-yang/Agents-A1-MTPLX-Q4
Usage with mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("wang-yang/Agents-A1-MTPLX-Q4")
prompt = "<|im_start|>user\nHello!<|im_end|>\n<|im_start|>assistant\n"
result = generate(model, tokenizer, prompt=prompt, max_tokens=200)
Notes
- EOS token:
<|im_end|>(id 248046) - MTP speculative decoding: ~1.33x speedup (D2 best, 101.8 tok/s vs AR 76.6 tok/s on M3 Max 128GB).
Files
| File | Description |
|---|---|
model-0000X-of-00004.safetensors |
Quantized model weights (4 shards) |
mtp.safetensors |
MTP draft head weights (4-bit quantized) |
config.json |
Model architecture + quantization config |
tokenizer.json |
Tokenizer vocabulary |
tokenizer_config.json |
Tokenizer settings |
chat_template.jinja |
Chat template (no thinking mode) |