LLMLocal inference
Llama 3.1 8B
VRAM requirements to run Llama 3.1 8B locally at each quantization level. Find the cheapest GPU that fits below.
Q4 VRAM
5 GB
Q8 VRAM
9 GB
FP16 VRAM
16 GB
Context window
128 k tokens
01 // GPUs that can run Llama 3.1 8B
Cheapest compatible hardware by quantization
Sorted cheapest first. All prices are approximate street prices.
Q4Q4_K_M (4-bit)
needs ≥5 GB VRAMGPUVRAMPriceTier
Q8Q8_0 (8-bit)
needs ≥9 GB VRAMGPUVRAMPriceTier
FP16FP16 (full precision)
needs ≥16 GB VRAMGPUVRAMPriceTier
02 // Frequently asked
Llama 3.1 8B GPU questions
How much VRAM does Llama 3.1 8B need?
Llama 3.1 8B requires approximately 5GB VRAM at Q4 quantization, 9GB at Q8, or 16GB at full FP16 precision. Q4 is the most practical choice for consumer hardware.
What is the cheapest GPU to run Llama 3.1 8B?
The cheapest single GPU that fits Llama 3.1 8B at Q4 is the GeForce RTX 3060 12GB (12GB VRAM, ~$249). At Q4 you need at least 5GB.
Can I run Llama 3.1 8B at FP16?
Yes. Llama 3.1 8B at FP16 requires 16GB VRAM. Several workstation GPUs (48–96GB) can handle this on a single card.
What quantization is best for Llama 3.1 8B?
Q4_K_M (5GB) offers the best hardware compatibility and still produces high-quality output. Q8_0 (9GB) is better for tasks needing higher accuracy at the cost of needing more VRAM. FP16 (16GB) is only practical on very high-end workstation hardware.