README.md

---
quantized_by: anikifoss
pipeline_tag: text-generation
base_model: Qwen/Qwen3-Coder-480B-A35B-Instruct
license: apache-2.0
base_model_relation: quantized
tags:
- conversational
- gguf
- no_imatrix
---

# Model Card

High quality quantization of **Qwen3-Coder-480B-A35B-Instruct** without using imatrix.

# Run

## ik_llama.cpp

See [this detailed guide](https://github.com/ikawrakow/ik_llama.cpp/discussions/258) on how to setup ik_llama and how to make custom quants.

```
./build/bin/llama-server \
    --alias anikifoss/Qwen3-Coder-480B-A35B-Instruct-HQ4_K \
    --model /mnt/data/Models/anikifoss/Qwen3-Coder-480B-A35B-Instruct-HQ4_K/Qwen3-Coder-480B-A35B-Instruct-HQ4_K-00001-of-00007.gguf \
    --no-mmap -rtr \
    --temp 0.5 --top-k 0 --top-p 1.0 --min-p 0.1 --repeat-penalty 1.0 \
    --ctx-size 51000 \
    -ctk f16 -ctv f16 \
    -fa \
    -b 1024 -ub 1024 \
    -fmoe \
    --n-gpu-layers 99 \
    --override-tensor exps=CPU \
    --parallel 1 \
    --threads 32 \
    --threads-batch 64 \
    --host 127.0.0.1 \
    --port 8090
```

## llama.cpp

```
./build/bin/llama-server \
    --alias anikifoss/Qwen3-Coder-480B-A35B-Instruct-HQ4_K \
    --model /mnt/data/Models/anikifoss/Qwen3-Coder-480B-A35B-Instruct-HQ4_K/Qwen3-Coder-480B-A35B-Instruct-HQ4_K-00001-of-00007.gguf \
    --no-mmap \
    --temp 0.5 --top-k 0 --top-p 1.0 --min-p 0.1 --repeat-penalty 1.0 \
    --ctx-size 51000 \
    -ctk f16 -ctv f16 \
    -fa \
    -b 1024 -ub 1024 \
    --n-gpu-layers 99 \
    --override-tensor exps=CPU \
    --parallel 1 \
    --threads 32 \
    --threads-batch 64 \
    --host 127.0.0.1 \
    --port 8090
```

## Quantization Recipe
Quantized with [ik_llama](https://github.com/ikawrakow/ik_llama.cpp), but should work with any GGUF compatible inference framework.

```bash
#!/usr/bin/env bash

custom="
# Token embedding and output tensors
output\.weight=bf16
output_norm\.weight=f32
token_embd\.weight=bf16

blk\.[0-9]\.attn_k\.weight=q8_0
blk\.[0-9]\.attn_k_norm\.weight=f32
blk\.[0-9]\.attn_norm\.weight=f32
blk\.[0-9]\.attn_output\.weight=q8_0
blk\.[0-9]\.attn_q\.weight=q8_0
blk\.[0-9]\.attn_q_norm\.weight=f32
blk\.[0-9]\.attn_v\.weight=q8_0
blk\.[0-9]\.ffn_down_exps\.weight=q6_K
blk\.[0-9]\.ffn_gate_exps\.weight=q4_K
blk\.[0-9]\.ffn_up_exps\.weight=q4_K
blk\.[0-9]\.ffn_gate_inp\.weight=f32
blk\.[0-9]\.ffn_norm\.weight=f32
blk\.[1-5][0-9]\.attn_k\.weight=q8_0
blk\.[1-5][0-9]\.attn_k_norm\.weight=f32
blk\.[1-5][0-9]\.attn_norm\.weight=f32
blk\.[1-5][0-9]\.attn_output\.weight=q8_0
blk\.[1-5][0-9]\.attn_q\.weight=q8_0
blk\.[1-5][0-9]\.attn_q_norm\.weight=f32
blk\.[1-5][0-9]\.attn_v\.weight=q8_0
blk\.[1-5][0-9]\.ffn_down_exps\.weight=q6_K
blk\.[1-5][0-9]\.ffn_gate_exps\.weight=q4_K
blk\.[1-5][0-9]\.ffn_up_exps\.weight=q4_K
blk\.[1-5][0-9]\.ffn_gate_inp\.weight=f32
blk\.[1-5][0-9]\.ffn_norm\.weight=f32
blk\.6[0-1]\.attn_k\.weight=q8_0
blk\.6[0-1]\.attn_k_norm\.weight=f32
blk\.6[0-1]\.attn_norm\.weight=f32
blk\.6[0-1]\.attn_output\.weight=q8_0
blk\.6[0-1]\.attn_q\.weight=q8_0
blk\.6[0-1]\.attn_q_norm\.weight=f32
blk\.6[0-1]\.attn_v\.weight=q8_0
blk\.6[0-1]\.ffn_down_exps\.weight=q6_K
blk\.6[0-1]\.ffn_gate_exps\.weight=q4_K
blk\.6[0-1]\.ffn_up_exps\.weight=q4_K
blk\.6[0-1]\.ffn_gate_inp\.weight=f32
blk\.6[0-1]\.ffn_norm\.weight=f32
"

custom=$(
  echo "$custom" | grep -v '^#' | \
  sed -Ez 's:\n+:,:g;s:,$::;s:^,::'
)

echo "Running with: -custom-q $custom"

TARGET_MODEL="Qwen3-Coder-480B-A35B-Instruct-HQ4_K"
mkdir -p ~/Env/models/anikifoss/$TARGET_MODEL
./build/bin/llama-quantize \
    --custom-q "$custom" \
    /mnt/data/Models/Qwen/Qwen3-Coder-480B-A35B-Instruct-GGUF/Qwen3-Coder-480B-A35B-Instruct-BF16-00001-of-00021.gguf \
    ~/Env/models/anikifoss/$TARGET_MODEL/$TARGET_MODEL.gguf \
    Q4_K \
    32
```