GraySoft
Projects Models Compare Cloud benchmarks FAQ Download guIDE →
Model Intelligence Sheet

liodon-ai/Mythos-nano-imatrix-GGUF overview

Mythos nano — iMatrix GGUF GGUF quantizations of squ11z1/Mythos nano https://huggingface.co/squ11z1/Mythos nano , published by Liodon AI https://huggingface.co…

ggufollamalocal-llmllama.cpplm-studioquantizedimatrixsub-4-bitqwen2text-generationbase_model:squ11z1/Mythos-nanobase_model:quantized:squ11z1/Mythos-nanolicense:otherendpoints_compatibleregion:usconversational

Runs locally from ~1.06 GB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

Downloads
354
Likes
0
Pipeline
text-generation
Author

Repository Files & Downloads

7 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
Mythos-nano-IQ2_M.ggufGGUFIQ2_M1.06 GBDownload
Mythos-nano-IQ3_M.ggufGGUFIQ3_M1.39 GBDownload
Mythos-nano-IQ4_XS.ggufGGUFIQ4_XS1.62 GBDownload
Mythos-nano-Q4_K_M.ggufGGUFQ4_K_M1.80 GBDownload
Mythos-nano-Q5_K_M.ggufGGUFQ5_K_M2.07 GBDownload
Mythos-nano-Q6_K.ggufGGUFQ6_K2.36 GBDownload
Mythos-nano-Q8_0.ggufGGUFQ8_03.06 GBDownload

Model Details

Model IDliodon-ai/Mythos-nano-imatrix-GGUF
Authorliodon-ai
Pipelinetext-generation
Licenseother
Base modelsqu11z1/Mythos-nano
Last modified2026-07-13T04:56:08.000Z

Model README

---

license: other

base_model: squ11z1/Mythos-nano

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
  • qwen2

quantized_by: liodon-ai

---

Mythos-nano — iMatrix GGUF

GGUF quantizations of squ11z1/Mythos-nano, published by Liodon AI.

Quick Start

llama.cpp

llama-cli -hf liodon-ai/Mythos-nano-imatrix-GGUF:Q4_K_M

Ollama

ollama run hf.co/liodon-ai/Mythos-nano-imatrix-GGUF:Q4_K_M

LM Studio / Jan — search liodon-ai/Mythos-nano-imatrix-GGUF and pick your quant.

Quants

| Quant | Size | VRAM est. | Notes |

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

| IQ2_M | 1.14 GB | ~1 GB | 2-bit, iMatrix — smallest usable |

| IQ3_M | 1.49 GB | ~2 GB | 3-bit, iMatrix — great quality/size tradeoff |

| IQ4_XS | 1.74 GB | ~2 GB | 4-bit extra-small, iMatrix |

| Q4_K_M | 1.93 GB | ~2 GB | 4-bit, iMatrix-calibrated (recommended) |

| Q5_K_M | 2.22 GB | ~3 GB | 5-bit, iMatrix-calibrated |

| Q6_K | 2.54 GB | ~3 GB | 6-bit, iMatrix-calibrated, near-lossless |

| Q8_0 | 3.29 GB | ~4 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/Mythos-nano-GGUF

Source

---

Quantized by Liodon AI

Run liodon-ai/Mythos-nano-imatrix-GGUF with guIDE

Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.

Download guIDE → · Browse 524k+ models · Compare models

Source: Hugging Face · Compare models