README.md

---
base_model: FINAL-Bench/Darwin-36B-Opus
language:
- en
- zh
- ko
- ja
- de
- fr
- es
- ru
- ar
- multilingual
library_name: transformers
license: apache-2.0
mradermacher:
  readme_rev: 1
quantized_by: mradermacher
tags:
- darwin
- darwin-v7
- evolutionary-merge
- reasoning
- advanced-reasoning
- chain-of-thought
- thinking
- qwen3.6
- qwen
- moe
- mixture-of-experts
- distillation
- multilingual
- gpqa
- benchmark
- open-source
- apache-2.0
- hybrid-vigor
- proto-agi
- vidraft
- eval-results
---
## About

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static quants of https://huggingface.co/FINAL-Bench/Darwin-36B-Opus

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***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#Darwin-36B-Opus-GGUF).***

weighted/imatrix quants are available at https://huggingface.co/mradermacher/Darwin-36B-Opus-i1-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/Darwin-36B-Opus-GGUF/resolve/main/Darwin-36B-Opus.Q2_K.gguf) | Q2_K | 13.0 |  |
| [GGUF](https://huggingface.co/mradermacher/Darwin-36B-Opus-GGUF/resolve/main/Darwin-36B-Opus.Q3_K_S.gguf) | Q3_K_S | 15.3 |  |
| [GGUF](https://huggingface.co/mradermacher/Darwin-36B-Opus-GGUF/resolve/main/Darwin-36B-Opus.Q3_K_M.gguf) | Q3_K_M | 16.9 | lower quality |
| [GGUF](https://huggingface.co/mradermacher/Darwin-36B-Opus-GGUF/resolve/main/Darwin-36B-Opus.Q3_K_L.gguf) | Q3_K_L | 18.2 |  |
| [GGUF](https://huggingface.co/mradermacher/Darwin-36B-Opus-GGUF/resolve/main/Darwin-36B-Opus.IQ4_XS.gguf) | IQ4_XS | 19.0 |  |
| [GGUF](https://huggingface.co/mradermacher/Darwin-36B-Opus-GGUF/resolve/main/Darwin-36B-Opus.Q4_K_S.gguf) | Q4_K_S | 20.0 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/Darwin-36B-Opus-GGUF/resolve/main/Darwin-36B-Opus.Q4_K_M.gguf) | Q4_K_M | 21.3 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/Darwin-36B-Opus-GGUF/resolve/main/Darwin-36B-Opus.Q5_K_S.gguf) | Q5_K_S | 24.1 |  |
| [GGUF](https://huggingface.co/mradermacher/Darwin-36B-Opus-GGUF/resolve/main/Darwin-36B-Opus.Q5_K_M.gguf) | Q5_K_M | 24.8 |  |
| [GGUF](https://huggingface.co/mradermacher/Darwin-36B-Opus-GGUF/resolve/main/Darwin-36B-Opus.Q6_K.gguf) | Q6_K | 28.6 | very good quality |
| [GGUF](https://huggingface.co/mradermacher/Darwin-36B-Opus-GGUF/resolve/main/Darwin-36B-Opus.Q8_0.gguf) | Q8_0 | 37.0 | fast, best quality |

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.

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