Phi 4 Mini Instruct — Benchmarks
Benchmark scores for Phi 4 Mini Instruct aggregated from public leaderboards (3 boards), with how it ranks among open models and how it compares with its nearest neighbours. See hardware requirements for what you need to run it.
No llmrun Composite Score for Phi 4 Mini Instruct: the score is only published for a model measured on at least 4 of the boards in the score panel, spanning at least 2 benchmark categories and including a reasoning or coding board — or on 3 boards that narrow its score to a 90% range of at most 15.6 points. Either way the results must come from at least two different benchmarks. Its individual scores below stand on their own — see how the llmrun Composite Score gets calculated.
Phi 4 Mini Instruct reasoning benchmarks
Multi-step logic and problem-solving — can the model think through a hard problem rather than recall an answer.
Phi 4 Mini Instruct coding benchmarks
Writing, editing, and fixing real code — measured by whether the resulting program actually runs and passes tests.
Phi 4 Mini Instruct knowledge benchmarks
Breadth and depth of factual knowledge across many subjects, paired with the reasoning to apply it.
Scores aggregated from public benchmark sources (Epoch AI: 2 boards, TIGER-Lab: 1 board) — each linked from the benchmark pages. llmrun does not run these benchmarks. Percentiles and ranks are among open models in the llmrun catalogue; the median and leader marks refer to the same field.