New benchmark evidence: completed provider comparisons
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These four captures show why the dashboard keeps provider rows and analysis separate. The same machine can produce a different winner in a different run, and a composite recommendation is never allowed to erase the underlying values.
Interactive gallery: https://lizard-llm.qendryx.com/benchmarks.html
Five rows, five completed measurements
Ollama records 8.56 tok/s, stock llama.cpp Q4 7.85, and Lizard Native Q4 5.61 in this run. Load, warm-up and memory evidence stay visible beside throughput.
A second run changes the order
In this separate 10/10 run, llama.cpp Q4 reaches 6.23 tok/s, Lizard Native Q4 5.28, and Ollama 4.53. The result belongs to this model, machine and run—not a universal ranking.
Leaderboard plus metric-specific winners
Ollama leads the composite score, Lizard Native Q4 takes best native decode and parity among the compared rows, and llama.cpp Q4 leads wall time and end-to-end tokens per second.
Recommendations stay attached to source evidence
Scores, badges, execution lanes and raw provider values remain on the same screen. The recommendation annotates the run; it does not replace it.
Question for you: On your hardware, which decision should come first: shortest wall time, steady decode speed, peak memory, or answer parity?
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