Clinical Benchmarks

GLM 4.7

Released 22 Dec 2025$0.6 input, $2.2 output per million tokensopenAlso written as zai/glm-4.7Compare with other models

Clinical Benchmarks Index
42.3rank 91 of 148; 51.8 × 0.816 = 42.3, from 2 of 10 boards
Boards
2 of 13
Results
2
Latest measurement
Sep 2026

Results

Each line is placed on its own board. Dark tick: the board leader.

Documentation and coding

  1. MedScribe (Vals AI)
    model ID zai/glm-4.7; temperature=1; top_p=1; max_output_tokens=30000
    68.63
    Rank 94 of 105Leader Claude Opus 5.5 91.43
    Official leaderboard
    Measured Sep 2026
  2. MedCode (Vals AI)
    model ID zai/glm-4.7; temperature=1; top_p=1; max_output_tokens=30000
    32.77
    Rank 83 of 103Leader Claude Opus 5 63.57
    Official leaderboard
    Measured Sep 2026

Sources

Open a line for the quote and page.

  1. 94MedScribe (Vals AI) model ID zai/glm-4.7; temperature=1; top_p=1; max_output_tokens=30000 68.63
    Printed as 68.63%Official leaderboard, measured Sep 2026Configuration: model ID zai/glm-4.7; temperature=1; top_p=1; max_output_tokens=30000
    Vals AI MedScribe leaderboard official leaderboard, Vals AI, 3 Sep 2026. Vals AI MedScribe leaderboard, View: All Models, Task: Overall, row 94 of 105 (GLM 4.7), Accuracy column; Updated 9/29/2026. Rendered BenchmarkView table; configuration from embedded astro-island BenchmarkView props, benchmarkView.default.tasks.overall["zai/glm-4.7"].
    94 | GLM 4.7 | 68.63%±2.12 | $0.6/$2.2 | 2m47s
    Every result from this document
  2. 83MedCode (Vals AI) model ID zai/glm-4.7; temperature=1; top_p=1; max_output_tokens=30000 32.77
    Printed as 32.77%Official leaderboard, measured Sep 2026Configuration: model ID zai/glm-4.7; temperature=1; top_p=1; max_output_tokens=30000
    Vals AI MedCode leaderboard official leaderboard, Vals AI, 29 Sep 2026. MedCode leaderboard, Overall task, All Models expanded, rank 83 of 103; Accuracy column; board Updated 9/29/2026. Rendered table row; configuration from embedded BenchmarkView props benchmarkView.default.tasks.overall["zai/glm-4.7"].
    83 | GLM 4.7 | 32.77%±2.00 | $0.6/$2.2 | 2m03s
    Every result from this document

Other Zhipu models: GLM 5.1, GLM 5.2, GLM 5.3, GLM 5.3 Flash