AI Inference Platform Evaluation & Bounded Optimization
GoBlueFlare is choosing hardware for commercial LLM inference on OpenRouter, including unconventional and older-generation accelerators. We find the platform with the best economics once the right serving software is in place.
The approach is simple: get each candidate running, apply a sensible, capped amount of software optimization, measure what that effort actually buys, and stop once the best choice is clear.
Tiered engagement, From $35,000 CAD, stop at any tier. See the tiers ↓
Executive Thesis
Three ways to compare platforms. Only one produces a defensible decision.
Unconventional accelerators are routinely mis-judged because the comparison method is wrong before a single benchmark runs. Our differentiator is the method itself.
Out-of-box shootout
Run each platform on stock, unoptimized software and pick the apparent winner.
Optimize everything first
Fully optimize every candidate to its ceiling, then compare and choose.
Bounded optimization
Baseline, profile, apply capped high-value engineering, measure the response, and stop when the selection is decision-stable.
The positioning: we will determine which unconventional hardware becomes competitive after a commercially sensible amount of targeted software engineering, quantify the engineering required, and identify the point beyond which further optimization is unlikely to change the procurement decision.
Decision Lab
Model the decision before you buy the hardware.
Every input below is editable and every result is computed live in your browser. Values are clearly tagged by provenance. Measured benchmark fields are intentionally blank until real evaluation produces them, it shows Input required rather than inventing a number.