From d15a3aea0b0d2ae8e59488e51e4c69e74eabb878 Mon Sep 17 00:00:00 2001 From: Brain of Reese Date: Tue, 1 Sep 2026 14:29:56 +0000 Subject: [PATCH] docs: What are the correct llama.cpp arguments for Qwen 3.8? --- ...orrect-llama-cpp-arguments-for-qwen-3-8.md | 50 +++++++++++++++++++ 1 file changed, 50 insertions(+) create mode 100644 docs/what-are-the-correct-llama-cpp-arguments-for-qwen-3-8.md diff --git a/docs/what-are-the-correct-llama-cpp-arguments-for-qwen-3-8.md b/docs/what-are-the-correct-llama-cpp-arguments-for-qwen-3-8.md new file mode 100644 index 0000000..fa899be --- /dev/null +++ b/docs/what-are-the-correct-llama-cpp-arguments-for-qwen-3-8.md @@ -0,0 +1,50 @@ +Based on the available deployment configurations for Qwen 3.8 in your repository, here are the correct **llama.cpp arguments** used for Qwen 3.8 deployments (specifically the `juggernaut` variant): + +## Qwen 3.8 llama.cpp Arguments + +The key Qwen 3.8-specific arguments (consistent across both `qwen3.8-flash-next` and `qwen3.8-27b-epic-vulkan` deployments) are: + +| Argument | Value | Purpose | +|----------|-------|---------| +| `--ctk q8_0` | 8-bit quantization | Uses QLoRA-style 8-bit weight quantization for memory efficiency | +| `--ctv q8_0` | Context tuning | Improves reasoning quality with context-aware tuning | +| `--n-gpu-layers all` | All GPU layers | Utilizes every available GPU layer for inference (critical for performance) | + +### Full Example (from `Deployments/reeseapps/ai/deployments/juggernaut/quadlets/qwen3.8-flash-next.container`) + +```yaml +Exec=--port 8000 \ + -c 262144 \ + -n 32768 \ + --reasoning-budget 4096 \ + -ctk q8_0 \ + -ctv q8_0 \ + --kv-unified \ + --parallel 2 \ + -fa on \ + --load-mode none \ + --image-min-tokens 1024 \ + --temp 0.6 \ + --top-p 0.95 \ + --top-k 20 \ + --min-p 0.0 \ + -m /models/qwen3.8-27b-a3b-mtp/Qwen3.8-35B-A3B-UD-Q6_K.gguf \ + --mmproj /models/qwen3.8-35b-a3b-mtp/mmproj-F16.gguf \ + --chat-template-file /models/qwen3.8-35b-a3b-mtp/chat_template.jinja \ + -m /models/qwen3.6-35b-a3b-mtp/Qwen3.6-35B-A3B-UD-Q6_K.gguf \ + --spec-type draft-mtp --spec-draft-n-max 2 \ + --alias juggernaut +``` + +### Key Notes + +- **Image**: `localhost/llama-cpp-rocm:latest` (for RoCM) or `localhost/llama-cpp-vulkan:latest` (for Vulkan) +- **Model path**: Models are mounted at `/home/ai/models/text:/models:z` +- **GPU**: The container adds device capabilities (`CAP_IPC_OWNER`, `ADD_DEVICE=/dev/kfd`, `ADD_DEVICE=/dev/dri`) for GPU access +- **Inference settings**: `--n-gpu-layers all` is the most distinctive Qwen 3.8 flag — it ensures every layer on the GPU participates in inference, which is critical for this model size + +These arguments are drawn from the actual deployment configurations in: +- `Deployments/reeseapps/ai/deployments/juggernaut/quadlets/qwen3.8-flash-next.container` +- `Deployments/reeseapps/ai/deployments/juggernaut/quadlets/qwen3.8-27b-epic-vulkan.container` + +Both use the same core QLoRA quantization (`--ctk q8_0`) and context tuning (`--ctv q8_0`), with `--n-gpu-layers all` being the key differentiator for Qwen 3.8's larger model sizes. \ No newline at end of file