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824,736+ Combined GitHub Stars Audited Across Local Inference & Agent Runtimes

Local LLM Hardware VRAM & Quantization Calculator

Size exact model weights, GQA KV-cache overhead, and estimated decode throughput (tok/s) across Apple Unified Memory, NVIDIA RTX 4090/5090, H100, and Exo distributed clusters before provisioning hardware.

Local LLM Hardware & Open Weights Architecture
METAL • CUDA • RDMA CLUSTER ZERO TELEMETRY LEAK

1. Configure Model & Context

EMPIRICAL MEMORY & THROUGHPUT READOUT

FITS_NATIVELY (20.1 tok/s)

Engine: ggml-org/llama.cpp (Metal) or ollama/ollama
Model Weights
19.52 GB
KV-Cache Overhead
5.76 GB
Total Required VRAM
26.61 GB
Decode Speed
20.1 tok/s
Wire Local Ollama / vLLM Into Cursor, Cline & Aider ($0 Seat Fee)

Download a starter CLAUDE.md ($0), grab the $4.99 Drop-In Config Pack, or unlock the 9-file Local + LiteLLM fallback router .ZIP ($9.99).

Instant 1-Field Tool Claim & Live Shield Generator Auto-detects GitHub repo or work email

Live Local Inference & Agent Runtime Telemetry (GitHub Baseline)

Includes live Machined Obsidian & Emerald/Amber SVG Shields
Significant-Gravitas/AutoGPT 187,620

Autonomous multi-step AI agent orchestration runtime with local & hybrid model execution.

Significant-Gravitas/AutoGPT Verified PulseForge Shield
Runtime: Python
ollama/ollama 183,243

Get up and running with OpenAI gpt-oss, DeepSeek-R1, Gemma 3 and other models.

Runtime: Go
ggml-org/llama.cpp 131,250

LLM inference in C/C++ with zero dependencies across Metal, CUDA, and Vulkan.

ggml-org/llama.cpp Verified PulseForge Shield
Runtime: C++
vllm-project/vllm 93,851

A high-throughput and memory-efficient inference and serving engine for LLMs.

vllm-project/vllm Verified PulseForge Shield
Runtime: Python
modelcontextprotocol/servers 91,329

Official Model Context Protocol (MCP) reference servers for local filesystem, Git, and DB tool execution.

modelcontextprotocol/servers Verified PulseForge Shield
Runtime: TypeScript
BerriAI/litellm 61,434

Unified LLM proxy and cost-routing gateway across 100+ local (Ollama/vLLM) and frontier APIs.

BerriAI/litellm Verified PulseForge Shield
Runtime: Python
exo-explore/exo 47,901

Run frontier AI locally with distributed Thunderbolt RDMA across consumer devices.

exo-explore/exo Verified PulseForge Shield
Runtime: Python
PrefectHQ/fastmcp 28,108

Fast, Pythonic framework for building zero-latency Model Context Protocol servers and tools.

PrefectHQ/fastmcp Verified PulseForge Shield
Runtime: Python
WORKLOAD, REPO & TOKEN VOLUME WORKBENCH

Configure Team Token Volume & GitHub Repo Security Scan

1-Tap Presets:
Target: ollama/ollama • OWASP LLM01-06 & Bus-Factor Ready
LIVE SIDE-BY-SIDE COST, LATENCY & SWE-BENCH MATRIX

Claude 3.7 Sonnet vs. Gemini 2.5 Pro vs. DeepSeek R1 + 1-Click Fallback Router

65/35 Hybrid Fallback Saves $148/mo (-52%) at 50M Tokens
Claude 3.7 Sonnet70.3% SWE-bench
P50 TTFT: 410ms • $285/mo
Gemini 2.5 Pro68.8% SWE-bench
P50 TTFT: 340ms • $150/mo
DeepSeek R1 (BYOK)65.4% SWE-bench
P50 TTFT: 520ms • $48/mo
+ [litellm_fallback_router.yaml] primary: deepseek-r1 (0.65) | complex_ast: claude-3-7-sonnet (0.35) | fallback_on_429: gemini-2.5-pro (timeout: 12s)
Anodized Aluminum GPU Inference Server Cluster Rack

Bare-Metal H100 & B200 Cluster

Latency, token cost, and SWE-Bench Verified rates measured every 6 hours.

Systems Engineering Telemetry Workstation Desk

Drop-In Repository Guardrails

Compile repository-scoped .cursorrules, CLAUDE.md, and failover rules.

Precision Fiber-Optic Interconnects and CNC Heatsink Architecture

Zero-429 Multi-Provider Cascade

65/35 hybrid routing cutting monthly team inference spend by up to 52%.