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Model: Melvin56/Qwen3-4B-ik_GGUF Source: Original Platform
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README.md
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README.md
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---
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license: apache-2.0
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license_link: https://huggingface.co/Qwen/Qwen3-4B/blob/main/LICENSE
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pipeline_tag: text-generation
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base_model:
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- Qwen/Qwen3-4B
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language:
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- en
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tags:
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- imatrix
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- qwen3
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- conversational
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---
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# Melvin56/Qwen3-4B-ik_GGUF
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# Quant for [ik_llama.cpp](https://github.com/ikawrakow/ik_llama.cpp)
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Build: 3680 (a2d24c97)
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Original Model : [Qwen/Qwen3-4B](https://huggingface.co/Qwen/Qwen3-4B)
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I used imatrix to create all these quants using this [Dataset](https://gist.github.com/tristandruyen/9e207a95c7d75ddf37525d353e00659c/#file-calibration_data_v5_rc-txt).
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<img src="Qwen3-4B.png" alt="Perplexity" width="600">
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<details>
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<summary>Perplexity measurement methodology.</summary>
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I tested all quants using ik_llama.cpp build 3680 (a2d24c97)
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```
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ik_llama.cpp/build/bin/llama-perplexity \
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-m .gguf \
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--ctx-size 512 \
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--ubatch-size 512 \
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-f wikitext-2-raw/wiki.test.raw \
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-fa \
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-ngl 999
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```
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# Raw data
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| Quant | Size (GB) | PPL |
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|---------|-----------|---------------------|
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| BF16 | 8.05 | 14.3308 +/- 0.13259 |
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| IQ6_K | 3.34 | 14.2810 +/- 0.13159 |
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| IQ5_K | 2.82 | 14.5004 +/- 0.13465 |
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| IQ4_K | 2.38 | 14.5280 +/- 0.13414 |
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| IQ4_KS | 2.22 | 15.2121 +/- 0.14294 |
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</details>
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---
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| | CPU (AVX2) | CPU (ARM NEON) | Metal | cuBLAS | rocBLAS | SYCL | CLBlast | Vulkan | Kompute |
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| :------------ | :---------: | :------------: | :---: | :----: | :-----: | :---: | :------: | :----: | :------: |
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| K-quants | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ 🐢5 | ✅ 🐢5 | ❌ |
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| I-quants | ✅ 🐢4 | ✅ 🐢4 | ✅ 🐢4 | ✅ | ✅ | Partial¹ | ❌ | ❌ | ❌ |
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```
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✅: feature works
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🚫: feature does not work
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❓: unknown, please contribute if you can test it youself
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🐢: feature is slow
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¹: IQ3_S and IQ1_S, see #5886
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²: Only with -ngl 0
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³: Inference is 50% slower
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⁴: Slower than K-quants of comparable size
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⁵: Slower than cuBLAS/rocBLAS on similar cards
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⁶: Only q8_0 and iq4_nl
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```
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