Clinical Benchmarks
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GLM 5.3

Released 18 Aug 2026$1.4 input, $4.4 output per million tokens1M contextopenAlso written as zai/glm-5.3

2 results on 2 of 13 boards, latest measured Sep 2026. Compare with other models

Clinical Benchmarks Index30.5Rank 55 of 1492 of 10 boardsAverage × multiplier 52.8 × 0.577 = 30.5This site’s own calculation. Working How it is computed

Results

Each line sits on its own board's scale. Tall tick: the board leader.

Documentation and coding

  1. MedScribe (Vals AI)
    model ID zai/glm-5.3; temperature=1; top_p=0.95; max_output_tokens=30000; reasoning_effort=max
    88.81
    Rank 9 of 105Leader Claude Opus 5.5 91.43
    Official leaderboard
    Measured Sep 2026
  2. MedCode (Vals AI)
    model ID zai/glm-5.3; reasoning_effort=max; temperature=1; top_p=0.95; max_output_tokens=30000
    42.86
    Rank 46 of 103Leader Claude Opus 5 63.57
    Official leaderboard
    Measured Sep 2026

Index working

The Clinical Benchmarks Index is this site's own calculation: a weighted average of the board scores times a multiplier for the boards behind it. How it is computed

  • MedScribe (Vals AI)88.8188.8×0.25, near its ceilingNear its ceiling: leader 91.4, weight 0.25model ID zai/glm-5.3; temperature=1; top_p=0.95; max_output_tokens=30000; reasoning_effort=max
  • MedCode (Vals AI)42.8642.9×0.911model ID zai/glm-5.3; reasoning_effort=max; temperature=1; top_p=0.95; max_output_tokens=30000
Weighted average of 2 boards
52.8
Multiplier for 2 of 10 boards
× 0.577
Index
52.8 × 0.577 = 30.5

Score: the result on the board’s own 0 to 100 scale. Dot: this model; tick: the board’s leader. Weight: how much the board counts in the weighted average; bold where the board is near its ceiling and counts for less. Each result links to its quote and page; the line under it is the setting it was measured with.

Sources

The quote, page and document for each of the 2 results
  1. 9MedScribe (Vals AI) glm-5.3 88.81
    Printed as 88.81%Official leaderboard, measured Sep 2026Configuration: model ID zai/glm-5.3; temperature=1; top_p=0.95; max_output_tokens=30000; reasoning_effort=max
    Vals AI MedScribe leaderboard official leaderboard, Vals AI, 3 Sep 2026. Vals AI MedScribe leaderboard, View: All Models, Task: Overall, row 9 of 105 (GLM 5.3), Accuracy column; Updated 9/29/2026. Rendered BenchmarkView table; configuration from embedded astro-island BenchmarkView props, benchmarkView.default.tasks.overall["zai/glm-5.3"].
    9 | GLM 5.3 | 88.81%±2.00 | $1.4/$4.4 | 2m02s
    Every result from this document
  2. 46MedCode (Vals AI) glm-5.3 42.86
    Printed as 42.86%Official leaderboard, measured Sep 2026Configuration: model ID zai/glm-5.3; reasoning_effort=max; temperature=1; top_p=0.95; max_output_tokens=30000
    Vals AI MedCode leaderboard official leaderboard, Vals AI, 29 Sep 2026. MedCode leaderboard, Overall task, All Models expanded, rank 46 of 103; Accuracy column; board Updated 9/29/2026. Rendered table row; configuration from embedded BenchmarkView props benchmarkView.default.tasks.overall["zai/glm-5.3"].
    46 | GLM 5.3 | 42.86%±2.11 | $1.4/$4.4 | 2m49s
    Every result from this document

Other Zhipu models: GLM 4.7, GLM 5.1, GLM 5.2, GLM 5.3 Flash