High quality quantization of DeepSeek-V3.1 without using imatrix.
The architecture has not changed, so token generation speed should be the same as DeepSeek-R1-0528, see benchmarks here.
Run
ik_llama.cpp
See this detailed guide on how to setup ik_llama and how to make custom quants.
./build/bin/llama-server \
--alias anikifoss/DeepSeek-V3.1-HQ4_K \
--model /home/gamer/Env/models/anikifoss/DeepSeek-V3.1-HQ4_K/DeepSeek-V3.1-HQ4_K-00001-of-00010.gguf \
--no-mmap \
--temp 0.5 --top-k 0 --top-p 1.0 --min-p 0.1 --repeat-penalty 1.0 \
--ctx-size 82000 \
-ctk f16 \
-mla 3 -fa \
-amb 512 \
-b 1024 -ub 1024 \
-fmoe \
--n-gpu-layers 99 \
--override-tensor exps=CPU \
--parallel 1 \
--threads 32 \
--threads-batch 64 \
--host 127.0.0.1 \
--port 8090
llama.cpp
You can turn on thinking by changing "thinking": false to "thinking": true below.
Currently llama.cpp does not return <think> token in response. If you know how to fix that, please share in the "Community" section!
As a workaround, to inject the token in OpenWebUI, you can use the inject_think_token_filter.txt code included in the repository. You can add filters via Admin Panel -> Functions -> Filter -> + button on the right
./build/bin/llama-server \
--alias anikifoss/DeepSeek-V3.1-HQ4_K \
--model /home/gamer/Env/models/anikifoss/DeepSeek-V3.1-HQ4_K/DeepSeek-V3.1-HQ4_K-00001-of-00010.gguf \
--temp 0.5 --top-k 0 --top-p 1.0 --min-p 0.1 --repeat-penalty 1.0 \
--ctx-size 64000 \
-ctk f16 \
-fa \
--chat-template-kwargs '{"thinking": false }' \
-b 1024 -ub 1024 \
--n-gpu-layers 99 \
--override-tensor exps=CPU \
--parallel 1 \
--threads 32 \
--threads-batch 64 \
--jinja \
--host 127.0.0.1 \
--port 8090
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Hardware compatibility
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Model tree for anikifoss/DeepSeek-V3.1-HQ4_K
Base model
deepseek-ai/DeepSeek-V3.1-Base
Quantized
deepseek-ai/DeepSeek-V3.1