(Rant ;)) Make your benchmarks realistic

Reddit r/LocalLLaMA / 5/8/2026

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Key Points

The post argues that LLM benchmark results can be misleading if they focus on speed alone, because effective real-world LLM use depends on more than latency.
It emphasizes that realistic testing should account for context length, recommending long sessions and sufficient context sizes for agentic, coding, and RAG workloads.
For multimodal models, it urges researchers to benchmark using actual multimodal capabilities (e.g., image processing) rather than text-only or simplified runs.
The author recommends reporting exact hardware configurations and measuring performance under parallel processing, since hardware differences and concurrency matter for agentic work.
Overall, the post encourages the community to make benchmarking posts more useful by reflecting conditions closer to real deployments.

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.

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
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
State your specific hardware config - all cards have different variants
Benchmark also in parallel processing - with agentic work this is also important

Make your posts more usefull for community!

submitted by /u/AdamLangePL
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