(Rant ;)) Make your benchmarks realistic

Reddit r/LocalLLaMA News

Summary

A community rant urging realistic AI model benchmarks that account for context size, multimodal features, hardware specifics, and parallel processing, rather than just raw speed.

Everybody here is posting their optimizations for running different models - thats good but make these benchmark realistic as speed is not one factor to run llm effectively. 1. Context size is key - with agentic/coding/rag work you need to have proper ctx size, so if you want to benchmark do round trip with long session or bigger context - this is how you will get a proper real life environment 2. If you are testing multimodal models, use this multimodal features - run bechmarking with image processing for example - this will bring more value in real world scenarios 3. State your specific hardware config - all cards have different variants 4. Benchmark also in parallel processing - with agentic work this is also important Make your posts more usefull for community!
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