---
library_name: transformers
pipeline_tag: text-generation
tags:
- 32 k context
- reasoning
- thinking
- qwen3
- 4 experts activated
- double speed
- 128 experts
- llama-cpp
- gguf-my-repo
base_model: DavidAU/Qwen3-30B-A1.5B-High-Speed
---

# Triangle104/Qwen3-30B-A1.5B-High-Speed-Q5_K_S-GGUF
This model was converted to GGUF format from [`DavidAU/Qwen3-30B-A1.5B-High-Speed`](https://huggingface.co/DavidAU/Qwen3-30B-A1.5B-High-Speed) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://huggingface.co/DavidAU/Qwen3-30B-A1.5B-High-Speed) for more details on the model.

---
This is a simple "finetune" of the Qwen's "Qwen 30B-A3B" (MOE) model,
 setting the experts in use from 8 to 4 (out of 128 experts).


This method close to doubles the speed of the model and uses 1.5B (of
 30B) parameters instead of 3B (of 30B) parameters. Depending on the 
application you may want to
use the regular model ("30B-A3B"), and use this model for simpler use 
case(s) although I did not notice any loss of function during
routine (but not extensive) testing.

---
## Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)

```bash
brew install llama.cpp

```
Invoke the llama.cpp server or the CLI.

### CLI:
```bash
llama-cli --hf-repo Triangle104/Qwen3-30B-A1.5B-High-Speed-Q5_K_S-GGUF --hf-file qwen3-30b-a1.5b-high-speed-q5_k_s.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo Triangle104/Qwen3-30B-A1.5B-High-Speed-Q5_K_S-GGUF --hf-file qwen3-30b-a1.5b-high-speed-q5_k_s.gguf -c 2048
```

Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.

Step 1: Clone llama.cpp from GitHub.
```
git clone https://github.com/ggerganov/llama.cpp
```

Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
```
cd llama.cpp && LLAMA_CURL=1 make
```

Step 3: Run inference through the main binary.
```
./llama-cli --hf-repo Triangle104/Qwen3-30B-A1.5B-High-Speed-Q5_K_S-GGUF --hf-file qwen3-30b-a1.5b-high-speed-q5_k_s.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo Triangle104/Qwen3-30B-A1.5B-High-Speed-Q5_K_S-GGUF --hf-file qwen3-30b-a1.5b-high-speed-q5_k_s.gguf -c 2048
```