vadikulous-ai/Qwen-AgentWorld-35B-A3B-UD-Q4_K_XL-MTP-GGUF overview
Qwen AgentWorld 35B A3B UD Q4 K XL MTP GGUF This repository contains the Qwen AgentWorld 35B A3B model in UD Q4 K XL quantization with Multi Token Prediction M…
Runs locally from ~861.0 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
Model Details
| Model ID | vadikulous-ai/Qwen-AgentWorld-35B-A3B-UD-Q4_K_XL-MTP-GGUF |
|---|---|
| Author | vadikulous-ai |
| Pipeline | image-text-to-text |
| License | apache-2.0 |
| Base model | Qwen/Qwen-AgentWorld-35B-A3B |
| Last modified | 2026-07-17T15:56:26.000Z |
Model README
---
license: apache-2.0
base_model:
- Qwen/Qwen-AgentWorld-35B-A3B
pipeline_tag: image-text-to-text
tags:
- moe
- multimodal
- vision
- mtp
- gguf
---
Qwen-AgentWorld-35B-A3B-UD-Q4_K_XL-MTP-GGUF
This repository contains the Qwen-AgentWorld-35B-A3B model in UD-Q4_K_XL quantization with Multi-Token Prediction (MTP) support for speculative decoding.
Acknowledgments
- Qwen Team for the original Qwen-AgentWorld-35B-A3B model
- Unsloth for the Qwen3.6-35B-A3B-MTP-GGUF quantization with MTP heads
- Unsloth for the Qwen-AgentWorld-35B-A3B-GGUF quantization
How It Was Made
The MTP heads from Qwen3.6-35B-A3B were extracted and grafted onto the Qwen-AgentWorld-35B-A3B model. Both models share the same architecture (qwen35moe), making this transfer possible. The resulting model includes all base layers from AgentWorld plus the MTP prediction head from the original Qwen3.6 model.
Hardware & Performance
Performance results were achieved on AMD Strix Halo:
- Without MTP: ~60 tokens/s
- With MTP: ~77 tokens/s
- Speed improvement: +28%
- Draft acceptance rate: ~87%
The high acceptance rate indicates that the MTP heads from the base model transfer well to the AgentWorld fine-tune.
Usage
Basic Usage
./llama-server \
-m Qwen-AgentWorld-35B-A3B-UD-Q4_K_XL-MTP.gguf \
-ngl 99 -c 8192 -fa on \
--spec-type draft-mtp \
--spec-draft-n-max 3
Full Multimodal Setup
For multimodal capabilities with reasoning and optimized parameters:
MODEL_PATH="Qwen-AgentWorld-35B-A3B-UD-Q4_K_XL-MTP.gguf"
MMPROJ_PATH="mmproj-BF16.gguf"
./llama-server \
--model "$MODEL_PATH" \
--mmproj "$MMPROJ_PATH" \
-ngl 99 \
--host 0.0.0.0 \
--port 8000 \
--ctx-size 262144 \
--reasoning "on" \
--kv-unified \
-np 2 \
-fa "on" \
--no-mmap \
--image-min-tokens 1024 \
--spec-type "draft-mtp" \
--spec-draft-n-max 3 \
--spec-draft-p-min 0.75 \
-b 2048 \
-ub 512
Parameters:
--mmproj: Multimodal projector for vision capabilities--reasoning "on": Enable reasoning mode--kv-unified: Unified KV cache-np 2: 2 parallel slots--spec-type "draft-mtp": Enable MTP speculative decoding--spec-draft-n-max 3: Generate up to 3 draft tokens per step--spec-draft-p-min 0.75: Minimum probability threshold for draft tokens-b 2048: Batch size-ub 512: U-batch size
Run vadikulous-ai/Qwen-AgentWorld-35B-A3B-UD-Q4_K_XL-MTP-GGUF with guIDE
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