Open-Weights LLM Capability & Local VRAM Simulator

❖ Frontier Capability Radar (Open vs Proprietary)

Index: 89.2/100

HumanEval Coding 88.4%

GSM8K Math 91.2%

ARC Reasoning 86.0%

Context Needle 99.1%

⚡ Hardware & VRAM Memory Allocation

FIT: OK

Model Parameters 70B

Quantization Precision

Context Window (Tokens) 32,768

Batch Size 1

Target Hardware Platform

VRAM Allocation Breakout 39.0 GB / 24.0 GB

Model Weights (35.0 GB)

KV Cache Overhead (4.0 GB)

Headroom / Overcommit

Gen Throughput 25.8 tok/s

Quant Quality Loss 1.8%

📋 Deployment Recommendation & Hardware Fit Brief

Recommended GPU Topologies:

2x RTX 4090 24GB 1x A100 80GB

Architectural Assessment:

Configured 70B parameter model at 4-bit precision consumes 35.0 GB weights + 4.0 GB KV Cache (39.0 GB Total). Exceeds single 24GB VRAM limit. Recommended deployment requires dual 24GB GPUs or a single 80GB accelerator for optimal throughput.