dinerburger/qwen3-coder-next-gguf IQ3_S GGUF - Free GGUF Download is indexed on GraySoft with repository links, GGUF quant files, and Hugging Face metadata. This page helps you pick a local model for guIDE or other runtimes. See related models in the same shard below.
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dinerburger/qwen3-coder-next-gguf overview
This is a custom GGUF quantization of Qwen3-Coder-Next, using the unsloth imatrix data with specific focus on retaining quality in embedding, output and attention tensors. IQ4XS quantization script: IQ3S quantization script:
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{
"metadata": {},
"card_data": {
"license": "apache-2.0",
"base_model": [
"Qwen/Qwen3-Coder-Next"
],
"frontmatter": {
"license": "apache-2.0",
"base_model": [
"Qwen/Qwen3-Coder-Next"
]
},
"hero_image_url": "",
"summary": "This is a custom GGUF quantization of Qwen3-Coder-Next, using the unsloth imatrix data with specific focus on retaining quality in embedding, output and attention tensors. IQ4_XS quantization script: `` QUANT=\"IQ4_XS\" llama-quantize \\ --output-tensor-type q8_0 \\ --token-embedding-type q8_0 \\ --tensor-type attn_qkv=bf16 \\ --tensor-type attn_v=bf16 \\ --tensor-type attn_q=bf16 \\ --tensor-type attn_k=bf16 \\ --tensor-type attn_gate=bf16 \\ --tensor-type attn_output=bf16 \\ --tensor-type ssm_ba=bf16 \\ --tensor-type ssm_beta=bf16 \\ --tensor-type ssm_alpha=bf16 \\ --tensor-type ssm_out=bf16 \\ --tensor-type ffn_down_shexp=bf16 \\ --tensor-type ffn_gate_shexp=bf16 \\ --tensor-type ffn_up_shexp=bf16 \\ --tensor-type ffn_down_exps=iq4_nl \\ --imatrix Qwen-Coder-Next-imatrix.gguf_file \\ BF16/Qwen3-Coder-Next-BF16-00001-of-00004.gguf \\ Qwen3-Coder-Next.${QUANT}.gguf \\ ${QUANT} ` IQ3_S quantization script: ` QUANT=\"IQ3_S\" llama-quantize \\ --output-tensor-type q6_k \\ --token-embedding-type q6_k \\ --tensor-type attn_qkv=bf16 \\ --tensor-type attn_v=bf16 \\ --tensor-type attn_q=bf16 \\ --tensor-type attn_k=bf16 \\ --tensor-type attn_gate=bf16 \\ --tensor-type attn_output=bf16 \\ --tensor-type ssm_ba=bf16 \\ --tensor-type ssm_beta=bf16 \\ --tensor-type ssm_alpha=bf16 \\ --tensor-type ssm_out=bf16 \\ --tensor-type ffn_down_shexp=bf16 \\ --tensor-type ffn_gate_shexp=bf16 \\ --tensor-type ffn_up_shexp=bf16 \\ --tensor-type ffn_down_exps=iq4_xs \\ --imatrix Qwen-Coder-Next-imatrix.gguf_file \\ BF16/Qwen3-Coder-Next-BF16-00001-of-00004.gguf \\ Qwen3-Coder-Next.${QUANT}.gguf \\ ${QUANT} ``",
"quick_links": [],
"benchmark_table_html": "",
"readme_markdown": "---\nlicense: apache-2.0\nbase_model:\n- Qwen/Qwen3-Coder-Next\n---\n\nThis is a custom GGUF quantization of [Qwen3-Coder-Next](https://huggingface.co/Qwen/Qwen3-Coder-Next), using the [unsloth imatrix data](https://huggingface.co/unsloth/Qwen3-Coder-Next-GGUF/resolve/main/imatrix_unsloth.gguf_file) with specific focus on retaining quality in embedding, output and attention tensors.\n\nIQ4_XS quantization script:\n```\nQUANT=\"IQ4_XS\"\nllama-quantize \\\n --output-tensor-type q8_0 \\\n --token-embedding-type q8_0 \\\n --tensor-type attn_qkv=bf16 \\\n --tensor-type attn_v=bf16 \\\n --tensor-type attn_q=bf16 \\\n --tensor-type attn_k=bf16 \\\n --tensor-type attn_gate=bf16 \\\n --tensor-type attn_output=bf16 \\\n --tensor-type ssm_ba=bf16 \\\n --tensor-type ssm_beta=bf16 \\\n --tensor-type ssm_alpha=bf16 \\\n --tensor-type ssm_out=bf16 \\\n --tensor-type ffn_down_shexp=bf16 \\\n --tensor-type ffn_gate_shexp=bf16 \\\n --tensor-type ffn_up_shexp=bf16 \\\n --tensor-type ffn_down_exps=iq4_nl \\\n --imatrix Qwen-Coder-Next-imatrix.gguf_file \\\n BF16/Qwen3-Coder-Next-BF16-00001-of-00004.gguf \\\n Qwen3-Coder-Next.${QUANT}.gguf \\\n ${QUANT}\n```\n\nIQ3_S quantization script:\n```\nQUANT=\"IQ3_S\"\nllama-quantize \\\n --output-tensor-type q6_k \\\n --token-embedding-type q6_k \\\n --tensor-type attn_qkv=bf16 \\\n --tensor-type attn_v=bf16 \\\n --tensor-type attn_q=bf16 \\\n --tensor-type attn_k=bf16 \\\n --tensor-type attn_gate=bf16 \\\n --tensor-type attn_output=bf16 \\\n --tensor-type ssm_ba=bf16 \\\n --tensor-type ssm_beta=bf16 \\\n --tensor-type ssm_alpha=bf16 \\\n --tensor-type ssm_out=bf16 \\\n --tensor-type ffn_down_shexp=bf16 \\\n --tensor-type ffn_gate_shexp=bf16 \\\n --tensor-type ffn_up_shexp=bf16 \\\n --tensor-type ffn_down_exps=iq4_xs \\\n --imatrix Qwen-Coder-Next-imatrix.gguf_file \\\n BF16/Qwen3-Coder-Next-BF16-00001-of-00004.gguf \\\n Qwen3-Coder-Next.${QUANT}.gguf \\\n ${QUANT}\n\n```",
"related_quantizations": []
},
"tags": [
"gguf",
"base_model:Qwen/Qwen3-Coder-Next",
"base_model:quantized:Qwen/Qwen3-Coder-Next",
"license:apache-2.0",
"endpoints_compatible",
"region:us",
"imatrix",
"conversational"
],
"likes": 10,
"downloads": 835,
"gated": false,
"private": false,
"last_modified": "2026-03-14T15:09:28.000Z",
"created_at": "2026-03-12T13:47:30.000Z",
"pipeline_tag": "",
"library_name": ""
}
Source payload excerpt (from Hugging Face API)
{
"_id": "69b2c3f22e1af751954b6640",
"id": "dinerburger/Qwen3-Coder-Next-GGUF",
"modelId": "dinerburger/Qwen3-Coder-Next-GGUF",
"sha": "d13a581c2df1578f5b30e94ae709cb83f087f706",
"createdAt": "2026-03-12T13:47:30.000Z",
"lastModified": "2026-03-14T15:09:28.000Z",
"author": "dinerburger",
"downloads": 835,
"likes": 10,
"gated": false,
"private": false,
"pipeline_tag": "",
"library_name": "",
"siblings_count": 4
}