Qwen3.5-35B-A3B — Telco Track A GGUF
GGUF quantizations of a distilled Qwen3.5-35B-A3B fine-tuned on 5G NR drive-test troubleshooting trajectories (Zindi Telco Troubleshooting Agentic Challenge — Track A).
The LoRA adapter was merged into the base weights before quantization.
Files
| File | Quantization | Size | Notes |
|---|---|---|---|
Qwen3.5-35B-A3B.Q4_K_M.gguf |
Q4_K_M | ~20 GB | Recommended — good quality/size trade-off |
Qwen3.5-35B-A3B.Q5_K_M.gguf |
Q5_K_M | ~17 GB | Higher quality |
Qwen3.5-35B-A3B.BF16-*.gguf |
BF16 (sharded) | ~66 GB | Full precision — re-quantize yourself |
*-mmproj.gguf |
BF16 | ~861 MB | Multimodal projection (Unsloth artefact) |
Model Details
| Property | Value |
|---|---|
| Base model | unsloth/Qwen3.5-35B-A3B |
| Architecture | Qwen3.5 MoE — 35B total params, ~3B active |
| Distillation teacher | DeepSeek-V4-Flash |
| LoRA config (pre-merge) | r=16, alpha=32, BF16, targets: q/k/v/o_proj |
| Task | 5G NR drive-test fault diagnosis (multi-choice) |
| Quantization tool | Unsloth save_pretrained_gguf |
How to Run (llama.cpp)
# Q4_K_M — ~24 GB VRAM or RAM
llama-cli -m Qwen3.5-35B-A3B.Q4_K_M.gguf \
--chat-template qwen3 \
-p "You are a 5G NR troubleshooting expert..." \
-n 512
# Q5_K_M
llama-cli -m Qwen3.5-35B-A3B.Q5_K_M.gguf \
--chat-template qwen3 \
-n 512
LoRA Adapter
The raw LoRA adapter (without merging) is available at: andreribeiro87/Qwen3.5-35B-A3B-telco-tracka-lora