text model · TinyLlama · Windows
TL Can I run TinyLlama 1.1B on AMD Radeon RX 7900 XTX (24GB)?
Yes. TinyLlama 1.1B runs on AMD Radeon RX 7900 XTX (24GB) at Q4_K_M (~1.8 GB of ~23 GB usable).
Runs at Q4_K_M using ~1.8 GB of ~23 GB usable. You have room for FP16 for higher quality.
- Q4_K_M needed
- ~1.8 GB
- Usable on device
- ~23 GB
- Device memory
- 24 GB
- Best quant
- Q4_K_M
Run it
Pick your tool. All three load the same Q4_K_M weights.
ollama run tinyllama:1.1b llama-cli -hf TheBloke/TinyLlama-1.1B-Chat-v1.0-GGUF:Q4_K_M lms get TheBloke/TinyLlama-1.1B-Chat-v1.0-GGUF AMD GPUs run via Vulkan/ROCm at roughly half CUDA throughput. NVIDIA is the smooth path on Windows.
- Parameters
- 1.1B
- Q4_K_M size
- 0.669 GB
- Q8_0 size
- 1.17 GB
- Context
- 2k
- Ollama tag
- tinyllama:1.1b
- Memory
- 24 GB vram
- Usable for weights
- ~23 GB
- Best runtime
- Ollama (ROCm) / llama.cpp ROCm (Linux)
You could also run
Run TinyLlama 1.1B on other hardware
FAQ
Can AMD Radeon RX 7900 XTX (24GB) run TinyLlama 1.1B?
Yes. TinyLlama 1.1B runs on AMD Radeon RX 7900 XTX (24GB) at Q4_K_M (~1.8 GB of ~23 GB usable).
How much memory does TinyLlama 1.1B need?
AMD Radeon RX 7900 XTX (24GB) has room to spare. At Q4_K_M the weights are ~0.669 GB; with KV cache and runtime overhead, budget ~1.8 GB at a 4k context.
What is the best tool to run TinyLlama 1.1B on Windows?
LM Studio for a simple setup; Ollama (CUDA) for the most speed. AMD GPUs run via Vulkan/ROCm at roughly half CUDA throughput. NVIDIA is the smooth path on Windows.
Sources
Memory figures are estimates. See methodology.