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Gemini 2.5 Flash (7/17)

Also written as google/gemini-2.5-flash-thinking, Gemini 2.5 Flash (7/17) (Thinking), google/gemini-2.5-flash, Gemini 2.5 Flash (7/17) (Nonthinking)

2 results on 1 of 13 boards, latest measured Sep 2026. Compare with other models

Clinical Benchmarks Index16.5Rank 130 of 1491 of 10 boardsAverage × multiplier 40.4 × 0.408 = 16.5This 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. MedCode (Vals AI)
    model ID google/gemini-2.5-flash-thinking; temperature=1; max_output_tokens=30000
    40.36
    Rank 62 of 103Leader Claude Opus 5 63.57
    Official leaderboard
    Measured Sep 2026
  2. MedCode (Vals AI)
    model ID google/gemini-2.5-flash; temperature=1; max_output_tokens=30000
    38.42
    Rank 68 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

  • MedCode (Vals AI)40.3640.4×0.911model ID google/gemini-2.5-flash-thinking; temperature=1; max_output_tokens=30000
One board, so its score
40.4
Multiplier for 1 of 10 boards
× 0.408
Index
40.4 × 0.408 = 16.5

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. 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. 62MedCode (Vals AI) gemini-2.5-flash-thinking 40.36
    Printed as 40.36%Official leaderboard, measured Sep 2026Configuration: model ID google/gemini-2.5-flash-thinking; temperature=1; max_output_tokens=30000
    Vals AI MedCode leaderboard official leaderboard, Vals AI, 29 Sep 2026. MedCode leaderboard, Overall task, All Models expanded, rank 62 of 103; Accuracy column; board Updated 9/29/2026. Rendered table row; configuration from embedded BenchmarkView props benchmarkView.default.tasks.overall["google/gemini-2.5-flash-thinking"].
    62 | Gemini 2.5 Flash (7/17) (Thinking) | 40.36%±1.95 | $0.3/$2.5 | 22.83s
    Every result from this document
  2. 68MedCode (Vals AI) gemini-2.5-flash 38.42
    Printed as 38.42%Official leaderboard, measured Sep 2026Configuration: model ID google/gemini-2.5-flash; temperature=1; max_output_tokens=30000
    Vals AI MedCode leaderboard official leaderboard, Vals AI, 29 Sep 2026. MedCode leaderboard, Overall task, All Models expanded, rank 68 of 103; Accuracy column; board Updated 9/29/2026. Rendered table row; configuration from embedded BenchmarkView props benchmarkView.default.tasks.overall["google/gemini-2.5-flash"].
    68 | Gemini 2.5 Flash (7/17) (Nonthinking) | 38.42%±1.92 | $0.3/$2.5 | 22.14s
    Every result from this document

Other Google models: Gemini 2.0 Flash, Gemini 2.5 Flash, Gemini 2.5 Flash Lite, Gemini 2.5 Flash Lite (9/25), Gemini 2.5 Flash Preview (9/25), Gemini 2.5 Pro, Gemini 3.1 Flash Lite Preview, Gemini 3.1 Pro, Gemini 3.5 Flash, Gemini 3.5 Flash Lite, Gemini 3.6 Flash, Gemini 3.7 Flash, Gemini 3.8 Flash, Gemini 3 Flash, Gemini 3 Pro, Gemini 3 Pro (11/25), Gemma 3 12B, Gemma 3 27B, Gemma 4 12B, Gemma 4 26B A4B, Gemma 4 31B, Gemma 4 E2B, Gemma 4 E4B, MedGemma 27B Text, MedGemma 4B