llmrun

Yi 6B Chat — Benchmarks

Benchmark scores for Yi 6B Chat aggregated from public leaderboards (4 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 Yi 6B Chat: 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.

Yi 6B Chat reasoning benchmarks

Multi-step logic and problem-solving — can the model think through a hard problem rather than recall an answer.

  • BIG-Bench Hard

    47.2%

    median 50.8%open leader 87.5%

    Overall best: Gemini 1.5 Pro 001 89.2%

    45th percentile · #21 of 38 open · #28 of 50 all

    Lab-reported

    Epoch AI ·

Yi 6B Chat math benchmarks

Symbolic and quantitative problem-solving, from competition math to multi-step calculation.

  • GSM8K

    44.9%

    median 52.3%open leader 94.5%

    44th percentile · #35 of 62 open · #48 of 93 all

    Lab-reported

    Epoch AI ·

Yi 6B Chat knowledge benchmarks

Breadth and depth of factual knowledge across many subjects, paired with the reasoning to apply it.

  • MMLU-Pro

    28.8%

    median 52.0%open leader 88.0%

    Overall best: Gemini-3.1-Pro 91.2%

    16th percentile · #123 of 146 open · #228 of 257 all

    Independent

    TIGER-Lab

Other results (1)

Leaderboard-only, not part of the llmrun Score

  • MMLU

    61.0%

    median 62.5%open leader 87.2%

    Overall best: GPT 4o (Nov 20, 2024) 88.1%

    48th percentile · #45 of 85 open · #87 of 136 all

    Lab-reported

    Epoch AI ·

Scores aggregated from public benchmark sources (Epoch AI: 3 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.