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// SERVICE SPECIFICATION 02

📦 Local LLMs & Cost Slashing (60–90% Inference Savings)

Slashing recurring cloud API bills by 60–90% by deploying private, high-throughput open-weight models via Ollama, vLLM, llama.cpp, and private on-premise model serving.

🚀 Slash Inference Costs with Local LLMs →

1. Service Overview & Scope

  • Cloud Token Spend Audit & TCO Analysis:
    • Quantitative analysis of existing cloud LLM invoices (OpenAI, Anthropic) to isolate high-volume, low-complexity queries suitable for local execution.
    • Calculating Total Cost of Ownership (TCO) comparing cloud API recurring expenses against on-premise hardware capital expenditures.
  • High-Throughput On-Premise Serving:
    • Sizing and provisioning workstation or server GPU clusters (NVIDIA RTX/A-series, Apple Silicon Unified Memory) for maximum tokens/second.
    • Comprehensive training and setup guides for continuous-batching engines (vLLM) and lightweight edge runtimes (Ollama, llama.cpp) delivering multi-user concurrency.
  • Quantization & Memory Optimization:
    • Deploying state-of-the-art quantization formats (GGUF, AWQ, EXL2) enabling massive 70B+ model execution within constrained VRAM budgets.
    • FlashAttention-2 and PagedAttention configuration for sub-second time-to-first-token (TTFT) and high token generation throughput.

2. Standard Architecture & Tools

  • Serving Engines & Compilers:
    • vLLM with PagedAttention demonstrations for high-concurrency API servers.
    • Ollama and llama.cpp for rapid desktop workstation and edge deployment.
    • Docker and Podman containerization with NVIDIA Container Toolkit.
  • Open-Weight Model Portfolio:
    • DeepSeek-R1 & V3, Llama 3.3 (70B/8B), Qwen 2.5 (32B/72B/Coder), Mistral Large, and Gemma 2.
    • Domain-specific SLMs (Qwen 2.5 Coder, Phi-4) fine-tuned for specialized coding and extraction tasks.
  • Networking & Security Isolation:
    • Private reverse proxy with rate limiting, API token authentication, and TLS encryption.
    • Zero data egress architecture: complete air-gap isolation with no telemetry sent to external vendors.

3. Deliverable Examples

  1. Hardware Sizing & Token-Throughput Audit Report:
    • Hardware specification matrix, memory allocation guides, and calculated payback period with 3-year ROI forecasts.
  2. Local Inference Demonstration & Setup Guide Package:
    • Educational Docker Compose templates, Ansible playbook guides, and configuration walkthroughs with automated model caching and health checks.
  3. Drop-in OpenAI-Compatible API Gateway:
    • Fully compliant local REST API endpoint allowing instant drop-in replacement across existing applications with zero code rewrites.

4. Guarantees & Commitments

  • Zero Data Egress Guarantee: 100% of input prompts and generated completions remain strictly confined to your physical hardware or private VPC.
  • Target Throughput SLA: Verified generation speed (tokens/sec) meeting or exceeding agreed performance targets in demonstration benchmarks.
  • 30-Day Operational Handover Training Support: Assistance with driver updates, model re-quantization, and performance tuning post-delivery.

5. Investment & Pricing Quote

  1. Base Investment Range: $2,000 – $4,000 USD (per deployment sprint).
  2. Purchasing Power Parity (PPP) & Custom Pricing Tiers:
    • Adjustments available via Purchasing Power Parity (Tier 1: 100%, Tier 2: 75%, Tier 3: 50%). Tier 4 startup discount (50%) and Tier 5 custom pricing available on request for non-profits, educational institutions, and bootstrapped startups. Inquire during intake.
  3. Payment Schedule:
    • 50% upfront milestone initialization / 50% upon completed delivery, runtime verification, and client sign-off.
Commission Local LLM Cost Slashing → Free LinkedIn Consultation ↗