r/pixel

Pixel 9 Pro XL + Tensor G4 + 16GB LPDDR5X + Mali-G715: The Power of Tri-Synergy!

This tutorial is designed for **Rooted Android Phones + Termux + Mali GPU (e.g., Pixel, Xiaomi, Samsung, etc.)**.

---

# 📱 Complete Guide: Termux + Root + Mali GPU Accelerated llama.cpp

## ⚠️ Prerequisites

**Phone must be rooted** (Magisk/KernelSU).
**Install Termux** (recommended to download the latest version from F-Droid or GitHub).
**Phone GPU must be Mali** (most MediaTek and Tensor chips use Mali; Qualcomm Snapdragon uses Adreno, which requires a different approach).

---

## 🟢 Phase One: Install Basic Environment & Compile llama.cpp

Run the following commands sequentially in Termux:

```bash

# 1. Update and install dependencies

pkg update && pkg upgrade -y

pkg install git cmake clang make vulkan-loader vulkan-tools -y

# 2. Clone llama.cpp

git clone https://github.com/ggml-org/llama.cpp

cd llama.cpp

# 3. Compile (enable Vulkan and ARM NEON optimizations)

mkdir build && cd build

cmake .. -DLLAMA_VULKAN=ON -DLLAMA_ARM_NEON=ON -DCMAKE_BUILD_TYPE=Release

make -j$(nproc)

```

> 💡 **Tip**: Compilation may take 10-20 minutes; please be patient.

---

## 🔵 Phase Two: Extract System GPU Drivers (Core Step)

**This is the most critical step!** We need to "extract" the system drivers for Termux to use.

### 1. Create Storage Directories

```bash

mkdir -p /data/data/com.termux/files/usr/lib/vulkan

mkdir -p /data/data/com.termux/files/usr/share/vulkan/icd.d

```

### 2. Locate Driver File Paths

Paths vary by device. Run the following commands to search:

```bash

# Search for Vulkan driver

su -c "find /vendor /system -name 'vulkan*.so' 2>/dev/null"

# Search for GLES driver

su -c "find /vendor /system -name 'libGLES_mali.so' 2>/dev/null"

# Search for system Vulkan loader (critical!)

su -c "find /apex /system -name 'libvulkan.so' 2>/dev/null"

```

**👇 Example paths found (for Pixel 9 / Tensor G4):**

* Vulkan ICD: `/vendor/lib64/hw/vulkan.mali.so`

* GLES Lib: `/vendor/lib64/egl/libGLES_mali.so`

* Config Lib: `/vendor/lib64/aconfig_gpu_flags_c_lib.so` (if present)

* System Loader: `/system/lib64/libvulkan.so`

### 3. Copy Drivers to Termux

**Please modify the commands below according to your actual paths found above!**

```bash

# Gain root access and copy files (adjust paths as needed)

su << 'EOF'

# 1. Copy Mali-specific driver

cp /vendor/lib64/hw/vulkan.mali.so /data/data/com.termux/files/usr/lib/vulkan/

cp /vendor/lib64/egl/libGLES_mali.so /data/data/com.termux/files/usr/lib/vulkan/

# 2. Copy potential dependency libraries (ignore if file doesn't exist)

cp /vendor/lib64/aconfig_gpu_flags_c_lib.so /data/data/com.termux/files/usr/lib/vulkan/ 2>/dev/null

# 3. [Critical] Copy system-level Vulkan Loader (resolves missing symbol issues)

cp /system/lib64/libvulkan.so /data/data/com.termux/files/usr/lib/

# 4. Copy C++ standard library

cp /vendor/lib64/libc++.so /data/data/com.termux/files/usr/lib/vulkan/

# 5. Set permissions

chmod 755 /data/data/com.termux/files/usr/lib/vulkan/*.so

chmod 755 /data/data/com.termux/files/usr/lib/libvulkan.so

exit

EOF

```

---

## 🟠 Phase Three: Configure Environment Variables

### 1. Create ICD JSON Configuration File

Tell the Vulkan loader where to find the driver.

```bash

su -c "cat > /data/data/com.termux/files/usr/share/vulkan/icd.d/mali_icd.json << 'JSONEOF'

{

\"file_format_version\": \"1.0.1\",

\"ICD\": {

\"library_path\": \"/data/data/com.termux/files/usr/lib/vulkan/vulkan.mali.so\",

\"api_version\": \"1.4.335\"

}

JSONEOF"

chmod 644 /data/data/com.termux/files/usr/share/vulkan/icd.d/mali_icd.json

```

### 2. Set Environment Variables (Permanent)

```bash

# Append to ~/.bashrc

cat >> ~/.bashrc << 'RCPEOF'

# --- Vulkan GPU Acceleration for llama.cpp ---

export LD_LIBRARY_PATH=/system/lib64:/vendor/lib64:/vendor/lib64/egl:/data/data/com.termux/files/usr/lib/vulkan:/data/data/com.termux/files/usr/lib

export VK_ICD_FILENAMES=/data/data/com.termux/files/usr/share/vulkan/icd.d/mali_icd.json

# ---------------------------------------------

RCPEOF

# Apply changes immediately

source ~/.bashrc

```

---

## 🟣 Phase Four: Verification & Testing

### 1. Verify Vulkan Recognizes the GPU

```bash

vulkaninfo | grep -E "deviceName|deviceType"

```

✅ **Success indicator**: You should see `Mali-G715` or `Immortalis` etc., NOT `llvmpipe`.

### 2. Download a Model (e.g., Gemma-4)

Have a friend transfer the model to your phone, e.g., place it in `/storage/emulated/0/Download/`.

### 3. Run Test

```bash

cd ~/llama.cpp/build/bin

./llama-cli \

-m /storage/emulated/0/Download/Gemma-4-E2B--Q5_K_P.gguf \

--temp 1.0 -t 4 -c 4096 --no-mmap -n 20 --verbose 2>&1 | grep -E "Vulkan|GPU|device"

```

✅ **Success indicators**:

* You see `using device Vulkan0 (Mali-...)`

* You see `offloaded 36/36 layers to GPU`

---

## 🔴 Frequently Asked Questions (FAQ)

**Q1: What if my phone uses Qualcomm Snapdragon (Adreno GPU)?**

A: The process is the same, but the driver filename differs.

* Search for drivers: `su -c "find /vendor -name '*adreno*' -o -name '*kgsl*'"`

* The driver is typically named `vulkan.adreno.so`.

**Q2: Getting error `dlopen failed: library xxx not found`?**

A: This indicates missing dependency libraries.

* Use `readelf -d /path/to/vulkan.so | grep NEEDED` to identify missing libraries.

* Locate the corresponding `.so` files in `/vendor/lib64` or `/system/lib64` and copy them over.

**Q3: No speed improvement, still running on CPU?**

A: Check the `llama-cli` output.

* If you see `assigned to device CPU`, the environment variables may be misconfigured.

* Ensure you executed `source ~/.bashrc` before running.

* Verify thatvulkaninfocan detect your GPU.

This proves that:

- ✅ **GPU Model**: Mali-G715 successfully recognized

- ✅ **VRAM Usage**: 15456 MiB (~15 GB) - Indicates the model is fully loaded onto the GPU

- ✅ **Model Footprint**: 1641 MiB - Model weights residing in VRAM

- ✅ **Compute Buffer**: 545 MiB - GPU computation buffers

---

## 📊 Final Scorecard

|--------|----------|----------|-------------|

| **Generation Speed** | 4.1 t/s | **7.3 t/s** | **+78%** 🚀 |

| **Processing Speed** | 8.4 t/s | **10.7 t/s** | **+27%** |

| **Device** | CPU | **Mali-G715** | ✅ |

---

## 🎁 Now You Can:

### 1. **Create a Quick-Launch Script**

```bash

cat > ~/run-gemma.sh << 'EOF'

#!/data/data/com.termux/files/usr/bin/bash

cd ~/llama.cpp/build/bin

./llama-cli \

-m /storage/emulated/0/Download/Gemma-4-E2B--Q5_K_P.gguf \

--simple-io --jinja \

--temp 1.0 --top-p 0.95 --top-k 64 \

-t 4 -c 4096 --no-mmap \

--interactive-first

EOF

chmod +x ~/run-gemma.sh

```

From now on, simply run `~/run-gemma.sh` to launch!

### 2. **Try Larger Models**

Since your GPU has 15GB of VRAM, you can experiment with:

- **Llama-3-8B** (Q4_K_M quantized)

- **Qwen2.5-7B** (Q5_K_M quantized)

- **Mistral-7B** (Q6_K quantized)

> 💡 **Pro Tip**: Larger models with higher quantization levels (like Q6_K) offer better quality but require more VRAM. Monitor your memory usage with `vulkaninfo` or Android's developer options to avoid out-of-memory crashes.

I use a Pixel phone to set up Gemma and run it locally

My new pack is ready!