Quick Answer: NetworkChuck runs a RTX 4070 Ti Super (16GB VRAM total) configuration for it & ai tutorials. This setup handles Qwen/Qwen2.5-7B-Instruct at 45 tokens/sec optimized for 7B-13B models.
Specs & Performance
| Component | Product | Price | Purchase |
|---|---|---|---|
| GPU | RTX 4070 Ti Super Great value for local AI demos | $799 | View on Amazon |
| CPU | Intel Core i9-13900K 24-core for home lab server | $499 | View on Amazon |
| MOTHERBOARD | ASUS ProArt Z790-CREATOR Creator-focused with Thunderbolt 4 | $500 |
| Model | Quantization | Tokens/sec | VRAM Used |
|---|---|---|---|
| Qwen/Qwen2.5-7B-Instruct | FP16 | 45 tok/s | 16GB |
| facebook/opt-125m | FP16 | 47 tok/s | 15GB |
| bigscience/bloomz-560m | FP16 | 47 tok/s | 15GB |
| microsoft/Phi-3.5-vision-instruct | FP16 | 47 tok/s | 15GB |
| microsoft/Phi-3-mini-128k-instruct | FP16 | 47 tok/s | 15GB |
| deepseek-ai/DeepSeek-V3-0324 | FP16 | 47 tok/s | 15GB |
| tencent/HunyuanVideo-1.5 | FP16 | 47 tok/s | 16GB |
| deepseek-ai/DeepSeek-R1 | FP16 | 47 tok/s | 15GB |
| microsoft/phi-4 | FP16 | 47 tok/s | 15GB |
| trl-internal-testing/tiny-Qwen2ForCausalLM-2.5 | FP16 | 46 tok/s | 15GB |
No. This setup has 16GB VRAM but Llama 70B needs 40GB minimum. It can run Llama 13B and smaller models.
$2,628 total. Budget alternatives: Single RTX 4090 (~$4,200) or RTX 4080 (~$2,400) for smaller models.
Llama 405B and similar 400B+ models need 200GB+ VRAM (requires 8x A100 or H100 GPUs). This 16GB setup handles up to 70B models.
| RAM | 64GB DDR5-5600 Good for running VMs alongside AI | $220 | View on Amazon |
| STORAGE | Samsung 990 Pro 2TB Fast NVMe storage | $180 | View on Amazon |
| PSU | Corsair RM850x 850W 80+ Gold efficiency | $130 | View on Amazon |
| CASE | Lian Li O11 Dynamic Popular case with great aesthetics | $150 | View on Amazon |
| COOLING | NZXT Kraken X63 280mm AIO | $150 | View on Amazon |