Versus Engine
Ryzen 5 + RTX 4060 Ti Build vs Threadripper Pro + Dual RTX 4090 Build
Specs, price and the one trade-off that actually decides it — Ryzen 5 + RTX 4060 Ti Build against Threadripper Pro + Dual RTX 4090 Build, side by side.
Cheaper to start
Tie
Both start at a similar price.
Rated higher
Threadripper Pro + Dual RTX 4090 Build
9.2 vs 7.5 on our design scale.
Standout
Ryzen 5 + RTX 4060 Ti Build
16GB VRAM at entry-level pricing
Ryzen 5 + RTX 4060 Ti Build
Entry-tier DIY build for local AI: an AMD Ryzen 5 CPU paired with an NVIDIA GeForce RTX 4060 Ti (16 GB VRAM) and 64 GB of system RAM. Runs small models such as Phi-4-mini (3.8B) and Gemma 3 4B at roughly 90 tokens/s — the lowest-cost path in this index to useful local inference.
Where it wins, where it doesn't
Pros
- 16GB VRAM at entry-level pricing
- Accessible upgrade path
- Low power draw (160W GPU limit)
Cons
- Limited to 8B/14B models for fast inference
- Memory bandwidth restricts larger batch sizes
Specifications
- cpuAMD Ryzen 5
- gpuNVIDIA GeForce RTX 4060 Ti
- tierentry
- ram_gb64
- vram_gb16
- example_modelsPhi-4-mini (3.8B), Gemma 3 4B
- tokens_per_second~90
- vram_gb_total—
Threadripper Pro + Dual RTX 4090 Build
Professional-tier workstation: AMD Ryzen Threadripper Pro with two NVIDIA GeForce RTX 4090s (48 GB VRAM total) and 256 GB of RAM. Runs Llama 3.1 405B and gpt-oss-120b at roughly 10-20 tokens/s — the enterprise end of this index for on-premises inference.
Where it wins, where it doesn't
Pros
- 48GB total VRAM for heavy inference
- Massive PCIe lane bandwidth
- 64-core compute headroom
Cons
- Extreme power consumption (1500W+ peak)
- High noise levels under sustained load
Specifications
- cpuAMD Ryzen Threadripper Pro
- gpu2x NVIDIA GeForce RTX 4090
- tierprofessional
- ram_gb256
- vram_gb—
- example_modelsLlama 3.1 405B, gpt-oss-120b
- tokens_per_second10-20
- vram_gb_total48