Llama 3 Local Guide
Deploy Llama 3 with predictable performance and cost
- Pick the smallest Llama 3 model that reliably solves your tasks
- VRAM fit should drive hardware choices before raw benchmark speed
- Q4/Q5 is a practical default for most local deployments
- Use fixed benchmarks to validate runtime and model changes
- Track operational metrics to prevent hidden regressions
Choose the Right Llama 3 Size
Start with the smallest model that reliably solves your workload. Scale up only when measurable quality gaps appear.
8B Class
Best for low-latency assistants, coding help, and daily local usage. Lower hardware cost and fast responses.
70B Class
Best for higher reasoning quality and long-form tasks, but requires larger VRAM budgets and stricter runtime tuning.
Hardware Targets by Model Size
VRAM remains the first planning constraint when deploying Llama 3 locally.
8B-13B Workflows
RTX 3060 12GB and RTX 4070 Ti Super 16GB are strong baseline options for smooth local throughput.
70B Workflows
RTX 4090 24GB or RTX 5090-class setups are better aligned for large quantized models and sustained inference workloads.
RTX 3060 12GB
RTX 4070 Ti Super
RTX 4090
RTX 5090
Quantization and Quality Tradeoffs
Quantization determines how much model quality you keep versus how much VRAM and throughput you gain.
Default Recommendation
Start with Q4 or Q5 profiles for balanced quality and efficiency, then compare with Q8 only if quality loss is visible on your prompts.
Evaluation Method
Use fixed prompt sets and task-specific scoring to compare quantization levels before standardizing production defaults.
Runtime Setup Checklist
Most stability problems come from runtime mismatch, not model weights.
Checklist
Pin runtime versions, verify GPU acceleration is active, and validate with representative prompts before broad rollout.
Operational Best Practices
Treat local Llama deployment as an operational system with measurable SLOs.
Throughput and Latency Baselines
Track tokens/sec and latency on standard workloads so upgrades and model changes can be evaluated objectively.
Frequently Asked Questions
Related Guides & Resources
Ready to Get Started?
Check our step-by-step setup guides and GPU recommendations.