Meta
Llama 3.1 8B Instruct
Meta's 8B parameter instruction-tuned model. Great balance of performance and efficiency for local deployment.
8B parametersllamallama3.1128K context5.08GB - 17GB VRAM
Check Your Hardware
See which quantizations of Llama 3.1 8B Instruct your hardware can run.
Quantization Options
| Quantization | Bits | File Size | VRAM Needed | RAM Needed | Quality |
|---|---|---|---|---|---|
| Q4_K_M | 4.5 | 4.583 GB | 5.08 GB | 5.58 GB | 85% |
| Q5_K_M | 5.5 | 5.339 GB | 5.84 GB | 6.34 GB | 90% |
| Q8_0 | 8 | 7.954 GB | 8.45 GB | 8.95 GB | 98% |
| FP16 | 16 | 16 GB | 17 GB | 20 GB | 100% |
See It In Action
Real model outputs generated via RunThisModel.com — watch responses stream in real time.
Llama 3.3 70B responding...
Outputs generated by real AI models via RunThisModel.com. Generation speed shown is from cloud inference. Local speeds vary by hardware — check your device.
Frequently Asked Questions
How much VRAM do I need to run Llama 3.1 8B Instruct?
Llama 3.1 8B Instruct requires 5.08GB VRAM minimum with Q4_K_M quantization. For full precision, you need 17GB VRAM.
What is the best quantization for Llama 3.1 8B Instruct?
Q4_K_M offers the best balance of quality and VRAM usage. Q8_0 is near-lossless if you have enough VRAM.