Resources

Open Source versus Frontier Labs

Empirical differences between hosting local weights on customer silicon vs remote API dispatch arrays.

Physical Locality Drawbacks & Advantages

Proprietary APIs command near infinite computational resources dynamically. When dispatching to OpenAI or Anthropic, response payloads frequently hit massive Token Per Second velocity curves (100+ TPS). However, they mandate total data surrender and subject developers to systemic multi-hour outages on global load.

Locally served weights (e.g. Meta LlaMA iterations) operate inherently on consumer graphics buffers (VRAM). Their TPS is fiercely capped by local memory bandwidth and GPU matrix multiplication speeds. Yet, they provide permanent uptime capabilities, immunity to privacy auditing, and zero variable API cost billing structures.

  • Proprietary Models: 1 Trillion+ parameters, huge logic capabilities, strictly metered, cloud vulnerable.
  • Local Weights: 8B to 70B parameters, quantization required (Q4/Q8), deeply private, capped by localized memory hardware constraints.