The safest failure happens before the model starts generating.

Lizard evaluates GGUF architecture and quantization support before selecting the native executor. Unsupported combinations can be explained and routed through the compatibility and recommendation flow instead of producing a mysterious partial run.

Compatibility is a user-facing decision, not just an internal exception.

What does your onboarding flow show when a newly released GGUF family is not ready yet?

Engineering fact: Lizard inspects GGUF architecture and quantization compatibility before native execution and can route unsupported combinations to compatible alternatives instead of attempting an unsafe run.

Read the relevant Lizard page

#LizardNative #LizardLLM #LocalAI #GGUF #InferenceEngineering

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