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liodon-ai/SmolLM2-360M-Instruct-imatrix-GGUF overview

SmolLM2 360M Instruct — iMatrix GGUF GGUF quantizations of HuggingFaceTB/SmolLM2 360M Instruct https://huggingface.co/HuggingFaceTB/SmolLM2 360M Instruct , pub…

gguflocal-llmllama.cpplm-studioquantizedimatrixsub-4-bitllamatext-generationbase_model:HuggingFaceTB/SmolLM2-360M-Instructbase_model:quantized:HuggingFaceTB/SmolLM2-360M-Instructlicense:otherendpoints_compatibleregion:usconversational

Runs locally from ~201.4 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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Pipeline
text-generation
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Repository Files & Downloads

7 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
SmolLM2-360M-Instruct-IQ2_M.ggufGGUFIQ2_M201.4 MBDownload
SmolLM2-360M-Instruct-IQ3_M.ggufGGUFIQ3_M214.5 MBDownload
SmolLM2-360M-Instruct-IQ4_XS.ggufGGUFIQ4_XS216.2 MBDownload
SmolLM2-360M-Instruct-Q4_K_M.ggufGGUFQ4_K_M258.1 MBDownload
SmolLM2-360M-Instruct-Q5_K_M.ggufGGUFQ5_K_M276.5 MBDownload
SmolLM2-360M-Instruct-Q6_K.ggufGGUFQ6_K350.3 MBDownload
SmolLM2-360M-Instruct-Q8_0.ggufGGUFQ8_0368.5 MBDownload

Model Details

Model IDliodon-ai/SmolLM2-360M-Instruct-imatrix-GGUF
Authorliodon-ai
Pipelinetext-generation
Licenseother
Base modelHuggingFaceTB/SmolLM2-360M-Instruct
Last modified2026-07-26T07:56:10.000Z

Model README

---

license: other

base_model: HuggingFaceTB/SmolLM2-360M-Instruct

pipeline_tag: text-generation

tags:

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

---

SmolLM2-360M-Instruct — iMatrix GGUF

GGUF quantizations of HuggingFaceTB/SmolLM2-360M-Instruct, published by Liodon AI.

Quick Start

llama.cpp

llama-cli -hf liodon-ai/SmolLM2-360M-Instruct-imatrix-GGUF:Q4_K_M

Ollama

ollama run hf.co/liodon-ai/SmolLM2-360M-Instruct-imatrix-GGUF:Q4_K_M

LM Studio / Jan — search liodon-ai/SmolLM2-360M-Instruct-imatrix-GGUF and pick your quant.

Quants

| Quant | Size | VRAM est. | Notes |

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

| IQ2_M | 0.21 GB | ~0 GB | 2-bit, iMatrix — smallest usable |

| IQ3_M | 0.22 GB | ~0 GB | 3-bit, iMatrix — great quality/size tradeoff |

| IQ4_XS | 0.23 GB | ~0 GB | 4-bit extra-small, iMatrix |

| Q4_K_M | 0.27 GB | ~0 GB | 4-bit, iMatrix-calibrated (recommended) |

| Q5_K_M | 0.29 GB | ~0 GB | 5-bit, iMatrix-calibrated |

| Q6_K | 0.37 GB | ~0 GB | 6-bit, iMatrix-calibrated, near-lossless |

| Q8_0 | 0.39 GB | ~0 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/SmolLM2-360M-Instruct-GGUF

Source

---

Quantized by Liodon AI

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