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liodon-ai/Qwen3-4B-Thinking-2507-imatrix-GGUF overview

Qwen3 4B Thinking 2507 — iMatrix GGUF GGUF quantizations of Qwen/Qwen3 4B Thinking 2507 https://huggingface.co/Qwen/Qwen3 4B Thinking 2507 , published by Liodo…

ggufollamalocal-llmllama.cpplm-studioquantizedimatrixsub-4-bitqwen3text-generationbase_model:Qwen/Qwen3-4B-Thinking-2507base_model:quantized:Qwen/Qwen3-4B-Thinking-2507license:otherendpoints_compatibleregion:usconversational

Runs locally from ~1.41 GB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

Downloads
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Pipeline
text-generation
Author

Repository Files & Downloads

7 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
Qwen3-4B-Thinking-2507-IQ2_M.ggufGGUFIQ2_M1.41 GBDownload
Qwen3-4B-Thinking-2507-IQ3_M.ggufGGUFIQ3_M1.83 GBDownload
Qwen3-4B-Thinking-2507-IQ4_XS.ggufGGUFIQ4_XS2.11 GBDownload
Qwen3-4B-Thinking-2507-Q4_K_M.ggufGGUFQ4_K_M2.33 GBDownload
Qwen3-4B-Thinking-2507-Q5_K_M.ggufGGUFQ5_K_M2.69 GBDownload
Qwen3-4B-Thinking-2507-Q6_K.ggufGGUFQ6_K3.08 GBDownload
Qwen3-4B-Thinking-2507-Q8_0.ggufGGUFQ8_03.99 GBDownload

Model Details

Model IDliodon-ai/Qwen3-4B-Thinking-2507-imatrix-GGUF
Authorliodon-ai
Pipelinetext-generation
Licenseother
Base modelQwen/Qwen3-4B-Thinking-2507
Last modified2026-07-13T04:55:19.000Z

Model README

---

license: other

base_model: Qwen/Qwen3-4B-Thinking-2507

base_model_relation: quantized

pipeline_tag: text-generation

library_name: gguf

tags:

  • gguf
  • ollama
  • local-llm
  • llama.cpp
  • lm-studio
  • quantized
  • imatrix
  • sub-4-bit
  • qwen3

quantized_by: liodon-ai

---

Qwen3-4B-Thinking-2507 — iMatrix GGUF

GGUF quantizations of Qwen/Qwen3-4B-Thinking-2507, published by Liodon AI.

Quick Start

llama.cpp

llama-cli -hf liodon-ai/Qwen3-4B-Thinking-2507-imatrix-GGUF:Q4_K_M

Ollama

ollama run hf.co/liodon-ai/Qwen3-4B-Thinking-2507-imatrix-GGUF:Q4_K_M

LM Studio / Jan — search liodon-ai/Qwen3-4B-Thinking-2507-imatrix-GGUF and pick your quant.

Quants

| Quant | Size | VRAM est. | Notes |

|-------|------|-----------|-------|

| IQ2_M | 1.51 GB | ~2 GB | 2-bit, iMatrix — smallest usable |

| IQ3_M | 1.96 GB | ~2 GB | 3-bit, iMatrix — great quality/size tradeoff |

| IQ4_XS | 2.27 GB | ~3 GB | 4-bit extra-small, iMatrix |

| Q4_K_M | 2.50 GB | ~3 GB | 4-bit, iMatrix-calibrated (recommended) |

| Q5_K_M | 2.89 GB | ~3 GB | 5-bit, iMatrix-calibrated |

| Q6_K | 3.31 GB | ~4 GB | 6-bit, iMatrix-calibrated, near-lossless |

| Q8_0 | 4.28 GB | ~5 GB | 8-bit, essentially lossless |

What is iMatrix?

Standard quantization treats all weights equally. iMatrix runs 128 calibration chunks through

the full-precision model to find which weights matter most, then allocates more precision where

it counts. At Q2/Q3/Q4 this means noticeably better coherence and instruction-following —

same file size, better output.

Calibration: 2M tokens of WikiText-103.

> Also see plain (non-iMatrix) quants: liodon-ai/Qwen3-4B-Thinking-2507-GGUF

Source

---

Quantized by Liodon AI

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