README.md

---
base_model: ValiantLabs/Qwen3-8B-Esper3
datasets:
- sequelbox/Titanium2.1-DeepSeek-R1
- sequelbox/Tachibana2-DeepSeek-R1
- sequelbox/Raiden-DeepSeek-R1
language:
- en
library_name: transformers
license: apache-2.0
mradermacher:
  readme_rev: 1
quantized_by: mradermacher
tags:
- esper
- esper-3
- valiant
- valiant-labs
- qwen
- qwen-3
- qwen-3-8b
- 8b
- reasoning
- code
- code-instruct
- python
- javascript
- dev-ops
- jenkins
- terraform
- scripting
- powershell
- azure
- aws
- gcp
- cloud
- problem-solving
- architect
- engineer
- developer
- creative
- analytical
- expert
- rationality
- conversational
- chat
- instruct
---
## About

<!-- ### quantize_version: 2 -->
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<!-- ### tags: nicoboss -->
weighted/imatrix quants of https://huggingface.co/ValiantLabs/Qwen3-8B-Esper3

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***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#Qwen3-8B-Esper3-i1-GGUF).***

static quants are available at https://huggingface.co/mradermacher/Qwen3-8B-Esper3-GGUF
## Usage

If you are unsure how to use GGUF files, refer to one of [TheBloke's
READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) 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](https://huggingface.co/mradermacher/Qwen3-8B-Esper3-i1-GGUF/resolve/main/Qwen3-8B-Esper3.i1-IQ1_S.gguf) | i1-IQ1_S | 2.2 | for the desperate |
| [GGUF](https://huggingface.co/mradermacher/Qwen3-8B-Esper3-i1-GGUF/resolve/main/Qwen3-8B-Esper3.i1-IQ1_M.gguf) | i1-IQ1_M | 2.4 | mostly desperate |
| [GGUF](https://huggingface.co/mradermacher/Qwen3-8B-Esper3-i1-GGUF/resolve/main/Qwen3-8B-Esper3.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 2.6 |  |
| [GGUF](https://huggingface.co/mradermacher/Qwen3-8B-Esper3-i1-GGUF/resolve/main/Qwen3-8B-Esper3.i1-IQ2_XS.gguf) | i1-IQ2_XS | 2.8 |  |
| [GGUF](https://huggingface.co/mradermacher/Qwen3-8B-Esper3-i1-GGUF/resolve/main/Qwen3-8B-Esper3.i1-IQ2_S.gguf) | i1-IQ2_S | 3.0 |  |
| [GGUF](https://huggingface.co/mradermacher/Qwen3-8B-Esper3-i1-GGUF/resolve/main/Qwen3-8B-Esper3.i1-IQ2_M.gguf) | i1-IQ2_M | 3.2 |  |
| [GGUF](https://huggingface.co/mradermacher/Qwen3-8B-Esper3-i1-GGUF/resolve/main/Qwen3-8B-Esper3.i1-Q2_K_S.gguf) | i1-Q2_K_S | 3.2 | very low quality |
| [GGUF](https://huggingface.co/mradermacher/Qwen3-8B-Esper3-i1-GGUF/resolve/main/Qwen3-8B-Esper3.i1-Q2_K.gguf) | i1-Q2_K | 3.4 | IQ3_XXS probably better |
| [GGUF](https://huggingface.co/mradermacher/Qwen3-8B-Esper3-i1-GGUF/resolve/main/Qwen3-8B-Esper3.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 3.5 | lower quality |
| [GGUF](https://huggingface.co/mradermacher/Qwen3-8B-Esper3-i1-GGUF/resolve/main/Qwen3-8B-Esper3.i1-IQ3_XS.gguf) | i1-IQ3_XS | 3.7 |  |
| [GGUF](https://huggingface.co/mradermacher/Qwen3-8B-Esper3-i1-GGUF/resolve/main/Qwen3-8B-Esper3.i1-Q3_K_S.gguf) | i1-Q3_K_S | 3.9 | IQ3_XS probably better |
| [GGUF](https://huggingface.co/mradermacher/Qwen3-8B-Esper3-i1-GGUF/resolve/main/Qwen3-8B-Esper3.i1-IQ3_S.gguf) | i1-IQ3_S | 3.9 | beats Q3_K* |
| [GGUF](https://huggingface.co/mradermacher/Qwen3-8B-Esper3-i1-GGUF/resolve/main/Qwen3-8B-Esper3.i1-IQ3_M.gguf) | i1-IQ3_M | 4.0 |  |
| [GGUF](https://huggingface.co/mradermacher/Qwen3-8B-Esper3-i1-GGUF/resolve/main/Qwen3-8B-Esper3.i1-Q3_K_M.gguf) | i1-Q3_K_M | 4.2 | IQ3_S probably better |
| [GGUF](https://huggingface.co/mradermacher/Qwen3-8B-Esper3-i1-GGUF/resolve/main/Qwen3-8B-Esper3.i1-Q3_K_L.gguf) | i1-Q3_K_L | 4.5 | IQ3_M probably better |
| [GGUF](https://huggingface.co/mradermacher/Qwen3-8B-Esper3-i1-GGUF/resolve/main/Qwen3-8B-Esper3.i1-IQ4_XS.gguf) | i1-IQ4_XS | 4.7 |  |
| [GGUF](https://huggingface.co/mradermacher/Qwen3-8B-Esper3-i1-GGUF/resolve/main/Qwen3-8B-Esper3.i1-Q4_0.gguf) | i1-Q4_0 | 4.9 | fast, low quality |
| [GGUF](https://huggingface.co/mradermacher/Qwen3-8B-Esper3-i1-GGUF/resolve/main/Qwen3-8B-Esper3.i1-IQ4_NL.gguf) | i1-IQ4_NL | 4.9 | prefer IQ4_XS |
| [GGUF](https://huggingface.co/mradermacher/Qwen3-8B-Esper3-i1-GGUF/resolve/main/Qwen3-8B-Esper3.i1-Q4_K_S.gguf) | i1-Q4_K_S | 4.9 | optimal size/speed/quality |
| [GGUF](https://huggingface.co/mradermacher/Qwen3-8B-Esper3-i1-GGUF/resolve/main/Qwen3-8B-Esper3.i1-Q4_K_M.gguf) | i1-Q4_K_M | 5.1 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/Qwen3-8B-Esper3-i1-GGUF/resolve/main/Qwen3-8B-Esper3.i1-Q4_1.gguf) | i1-Q4_1 | 5.3 |  |
| [GGUF](https://huggingface.co/mradermacher/Qwen3-8B-Esper3-i1-GGUF/resolve/main/Qwen3-8B-Esper3.i1-Q5_K_S.gguf) | i1-Q5_K_S | 5.8 |  |
| [GGUF](https://huggingface.co/mradermacher/Qwen3-8B-Esper3-i1-GGUF/resolve/main/Qwen3-8B-Esper3.i1-Q5_K_M.gguf) | i1-Q5_K_M | 6.0 |  |
| [GGUF](https://huggingface.co/mradermacher/Qwen3-8B-Esper3-i1-GGUF/resolve/main/Qwen3-8B-Esper3.i1-Q6_K.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](https://www.nethype.de/huggingface_embed/quantpplgraph.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](https://www.nethype.de/), for letting
me use its servers and providing upgrades to my workstation to enable
this work in my free time. Additional thanks to [@nicoboss](https://huggingface.co/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.

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