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metadata
base_model: ValiantLabs/Qwen3-8B-ShiningValiant3
datasets:
  - sequelbox/Celestia3-DeepSeek-R1-0528
  - sequelbox/Mitakihara-DeepSeek-R1-0528
  - sequelbox/Raiden-DeepSeek-R1
language:
  - en
library_name: transformers
license: apache-2.0
mradermacher:
  readme_rev: 1
quantized_by: mradermacher
tags:
  - shining-valiant
  - shining-valiant-3
  - valiant
  - valiant-labs
  - qwen
  - qwen-3
  - qwen-3-8b
  - 8b
  - reasoning
  - code
  - code-reasoning
  - science
  - science-reasoning
  - physics
  - biology
  - chemistry
  - earth-science
  - astronomy
  - machine-learning
  - artificial-intelligence
  - compsci
  - computer-science
  - information-theory
  - ML-Ops
  - math
  - cuda
  - deep-learning
  - transformers
  - agentic
  - LLM
  - neuromorphic
  - self-improvement
  - complex-systems
  - cognition
  - linguistics
  - philosophy
  - logic
  - epistemology
  - simulation
  - game-theory
  - knowledge-management
  - creativity
  - problem-solving
  - architect
  - engineer
  - developer
  - creative
  - analytical
  - expert
  - rationality
  - conversational
  - chat
  - instruct

About

weighted/imatrix quants of https://huggingface.co/ValiantLabs/Qwen3-8B-ShiningValiant3

For a convenient overview and download list, visit our model page for this model.

static quants are available at https://huggingface.co/mradermacher/Qwen3-8B-ShiningValiant3-GGUF

Usage

If you are unsure how to use GGUF files, refer to one of TheBloke's READMEs for more details, including on how to concatenate multi-part files.

Provided Quants

(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

Link Type Size/GB Notes
GGUF i1-IQ1_S 2.2 for the desperate
GGUF i1-IQ1_M 2.4 mostly desperate
GGUF i1-IQ2_XXS 2.6
GGUF i1-IQ2_XS 2.8
GGUF i1-IQ2_S 3.0
GGUF i1-IQ2_M 3.2
GGUF i1-Q2_K_S 3.2 very low quality
GGUF i1-Q2_K 3.4 IQ3_XXS probably better
GGUF i1-IQ3_XXS 3.5 lower quality
GGUF i1-IQ3_XS 3.7
GGUF i1-Q3_K_S 3.9 IQ3_XS probably better
GGUF i1-IQ3_S 3.9 beats Q3_K*
GGUF i1-IQ3_M 4.0
GGUF i1-Q3_K_M 4.2 IQ3_S probably better
GGUF i1-Q3_K_L 4.5 IQ3_M probably better
GGUF i1-IQ4_XS 4.7
GGUF i1-Q4_0 4.9 fast, low quality
GGUF i1-IQ4_NL 4.9 prefer IQ4_XS
GGUF i1-Q4_K_S 4.9 optimal size/speed/quality
GGUF i1-Q4_K_M 5.1 fast, recommended
GGUF i1-Q4_1 5.3
GGUF i1-Q5_K_S 5.8
GGUF i1-Q5_K_M 6.0
GGUF i1-Q6_K 6.8 practically like static Q6_K

Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):

image.png

And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9

FAQ / Model Request

See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized.

Thanks

I thank my company, nethype GmbH, for letting me use its servers and providing upgrades to my workstation to enable this work in my free time. Additional thanks to @nicoboss for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.