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GPT-5.2

Released 11 Dec 2025$1.75 input, $14 output per million tokens400K contextproprietaryAlso written as GPT-5.2-High, GPT-5.2 Thinking, gpt-5.2-thinking

11 results on 5 of 13 boards, 6 of them on secondary measures, latest measured Sep 2026. Compare with other models

Clinical Benchmarks Index53.6Rank 7 of 1495 of 10 boardsAverage × multiplier 58.7 × 0.913 = 53.6This site’s own calculation. Working How it is computed

Results

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

Clinical reasoning and knowledge

  1. HealthBench Professional
    length-adjusted, max reasoning effort, GPT-5.6 system card Table 6 column GPT-5.2 (50.0 unadjusted, 3400 chars)
    0.459
    Rank 29 of 35Leader GPT-6 Astra (Anthropic run) 0.703
    Vendor-reported
    Measured Jun 2026
  2. MedXpertQA (MM)
    Qwen-run comparison in the Qwen3.5-397B-A17B model card
    73.3
    Rank 8 of 22 here, 5 models on the boardLeader GPT-5.6 Sol 81.5
    Independent run

Documentation and coding

  1. MedScribe (Vals AI)
    model ID openai/gpt-5.2-2025-12-11; max_output_tokens=30000; reasoning_effort=xhigh
    84.39
    Rank 33 of 105Leader Claude Opus 5.5 91.43
    Official leaderboard
    Measured Sep 2026
  2. MedCode (Vals AI)
    model ID openai/gpt-5.2-2025-12-11; reasoning_effort=xhigh; max_output_tokens=30000
    49.75
    Rank 17 of 103Leader Claude Opus 5 63.57
    Official leaderboard
    Measured Sep 2026

Safety

  1. MedPIC
    zero-shot; independent questions; exact option-set match
    68.1
    Rank 8 of 28Leader Gemini-3.1-Pro 80.7
    Independent run
    Measured Aug 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

  • HealthBench Professional0.45945.9×0.743length-adjusted, max reasoning effort, GPT-5.6 system card Table 6 column GPT-5.2 (50.0 unadjusted, 3400 chars)
  • MedScribe (Vals AI)84.3984.4×0.25, near its ceilingNear its ceiling: leader 91.4, weight 0.25model ID openai/gpt-5.2-2025-12-11; max_output_tokens=30000; reasoning_effort=xhigh
  • MedCode (Vals AI)49.7549.8×0.911model ID openai/gpt-5.2-2025-12-11; reasoning_effort=xhigh; max_output_tokens=30000
  • MedPIC68.168.1×0.482, near its ceilingNear its ceiling: leader 80.7, weight 0.482zero-shot; independent questions; exact option-set match
  • MedXpertQA (MM)73.373.3×0.463, near its ceilingNear its ceiling: leader 81.5, weight 0.463Qwen-run comparison in the Qwen3.5-397B-A17B model card
Weighted average of 5 boards
58.7
Multiplier for 5 of 10 boards
× 0.913
Index
58.7 × 0.913 = 53.6

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.

Secondary measures

Safety

  1. MedPIC, Guideline-following accuracy (GF)
    zero-shot; independent questions; exact option-set match
    78.2
    Rank 6 of 28Leader Gemini-3.1-Pro 87.7
    Independent run
    Measured Aug 2026
  2. MedPIC, Linked counterfactual pair accuracy
    zero-shot; independent questions; exact option-set match
    29.2
    Rank 8 of 28Leader Gemini-3.1-Pro 48.3
    Independent run
    Measured Aug 2026
  3. MedPIC, Risk activation accuracy
    zero-shot; independent questions; exact option-set match
    63.4
    Rank 8 of 28Leader MedGemma-27B-Text 76.1
    Independent run
    Measured Aug 2026
  4. MedPIC, Counterfactual accuracy (CF)
    zero-shot; independent questions; exact option-set match
    52.5
    Rank 9 of 28Leader Gemini-3.1-Pro 69.9
    Independent run
    Measured Aug 2026
  5. MedPIC, Risk deactivation accuracy
    zero-shot; independent questions; exact option-set match
    42.6
    Rank 12 of 28Leader Gemini-3.1-Pro 77.9
    Independent run
    Measured Aug 2026
  6. MedPIC, Published GF-minus-CF accuracy gap
    zero-shot; independent questions; exact option-set match
    25.7
    Descriptive measure, not ranked
    Independent run
    Measured Aug 2026

Sources

The quote, page and document for each of the 11 results
  1. 29HealthBench Professional length-adjusted 0.459
    Printed as 45.9Vendor-reported, measured Jun 2026Configuration: length-adjusted, max reasoning effort, GPT-5.6 system card Table 6 column GPT-5.2 (50.0 unadjusted, 3400 chars)
    GPT-5.6 System Card system card, OpenAI, 9 Jul 2026. Section 5.1 HealthBench, Table 6 (reported as length-adjusted score (unadjusted, mean response length in characters)), column GPT-5.2
    HealthBench Professional length-adjusted 46.2 (51.0, 3616) 39.6 (48.0, 4863) 45.9 (50.0, 3400) 48.1 (51.9, 3308) 51.8 (57.2, 3818) 60.5 (64.1, 3228) 57.7 (62.4, 3618) 55.7 (59.8, 3389)
    Every result from this document
    • Also printed in GPT-5.6 Preview System Card: 45.9, Section 5.1 HealthBench, Table 6 (reported as length-adjusted score (unadjusted, mean response length in characters)) (preview card, published 2026-06-26), column GPT-5.2
  2. 33MedScribe (Vals AI) gpt-5.2-2025-12-11 84.39
    Printed as 84.39%Official leaderboard, measured Sep 2026Configuration: model ID openai/gpt-5.2-2025-12-11; max_output_tokens=30000; reasoning_effort=xhigh
    Vals AI MedScribe leaderboard official leaderboard, Vals AI, 3 Sep 2026. Vals AI MedScribe leaderboard, View: All Models, Task: Overall, row 34 of 105 (GPT 5.2), Accuracy column; Updated 9/29/2026. Rendered BenchmarkView table; configuration from embedded astro-island BenchmarkView props, benchmarkView.default.tasks.overall["openai/gpt-5.2-2025-12-11"].
    34 | GPT 5.2 | 84.39%±1.86 | $1.75/$14 | 2m06s
    Every result from this document
  3. 17MedCode (Vals AI) gpt-5.2-2025-12-11 49.75
    Printed as 49.75%Official leaderboard, measured Sep 2026Configuration: model ID openai/gpt-5.2-2025-12-11; reasoning_effort=xhigh; max_output_tokens=30000
    Vals AI MedCode leaderboard official leaderboard, Vals AI, 29 Sep 2026. MedCode leaderboard, Overall task, All Models expanded, rank 17 of 103; Accuracy column; board Updated 9/29/2026. Rendered table row; configuration from embedded BenchmarkView props benchmarkView.default.tasks.overall["openai/gpt-5.2-2025-12-11"].
    17 | GPT 5.2 | 49.75%±2.26 | $1.75/$14 | 2m37s
    Every result from this document
  4. 8MedPIC zero-shot 68.1
    Printed as 68.1Independent run, measured Aug 2026Configuration: zero-shot; independent questions; exact option-set match
    Evaluating Counterfactual Sensitivity to Patient Information in Medication-Safety Reasoning paper, Zhitian Hou, Yuhang Liu, Pengkai Wang, Zeyu Liu, Guanghao Zhu, Zheng Liu, Shuo Cai, Congkai Xie, Zhijie Sang, Kun Zeng, Hongxia Yang (The Hong Kong Polytechnic University; InfiX.ai; Sun Yat-sen University), 4 Aug 2026. arXiv:2608.03028v1, Section 4, Table 2 (#S4.T2), row GPT-5.2, column Overall; row order: Model | Overall | GF | CF | Δ_GF−CF | Activation | Deactivation | Pair
    GPT-5.2 | 68.1 | 78.2 | 52.5 | 25.7 | 63.4 | 42.6 | 29.2
    Every result from this document
  5. 8MedXpertQA (MM) Qwen-run comparison… 73.3
    Printed as 73.3Independent runConfiguration: Qwen-run comparison in the Qwen3.5-397B-A17B model card
    Qwen/Qwen3.5-397B-A17B model card model card, Alibaba / Qwen, 16 Feb 2026. Benchmark Results > Vision Language > Medical VQA, row MedXpertQA-MM; columns GPT5.2 / Claude 4.5 Opus / Gemini-3 Pro / Qwen3-VL-235B-A22B / K2.5-1T-A32B / Qwen3.5-397B-A17B
    MedXpertQA-MM 73.3 63.6 76.0 47.6 65.3 70.0
    Every result from this document
  6. 6MedPIC, Guideline-following accuracy (GF) zero-shot 78.2
    Printed as 78.2Independent run, measured Aug 2026Configuration: zero-shot; independent questions; exact option-set match
    Evaluating Counterfactual Sensitivity to Patient Information in Medication-Safety Reasoning paper, Zhitian Hou, Yuhang Liu, Pengkai Wang, Zeyu Liu, Guanghao Zhu, Zheng Liu, Shuo Cai, Congkai Xie, Zhijie Sang, Kun Zeng, Hongxia Yang (The Hong Kong Polytechnic University; InfiX.ai; Sun Yat-sen University), 4 Aug 2026. arXiv:2608.03028v1, Section 4, Table 2 (#S4.T2), row GPT-5.2, column GF; row order: Model | Overall | GF | CF | Δ_GF−CF | Activation | Deactivation | Pair
    GPT-5.2 | 68.1 | 78.2 | 52.5 | 25.7 | 63.4 | 42.6 | 29.2
    Every result from this document
  7. 9MedPIC, Counterfactual accuracy (CF) zero-shot 52.5
    Printed as 52.5Independent run, measured Aug 2026Configuration: zero-shot; independent questions; exact option-set match
    Evaluating Counterfactual Sensitivity to Patient Information in Medication-Safety Reasoning paper, Zhitian Hou, Yuhang Liu, Pengkai Wang, Zeyu Liu, Guanghao Zhu, Zheng Liu, Shuo Cai, Congkai Xie, Zhijie Sang, Kun Zeng, Hongxia Yang (The Hong Kong Polytechnic University; InfiX.ai; Sun Yat-sen University), 4 Aug 2026. arXiv:2608.03028v1, Section 4, Table 2 (#S4.T2), row GPT-5.2, column CF; row order: Model | Overall | GF | CF | Δ_GF−CF | Activation | Deactivation | Pair
    GPT-5.2 | 68.1 | 78.2 | 52.5 | 25.7 | 63.4 | 42.6 | 29.2
    Every result from this document
  8. 8MedPIC, Linked counterfactual pair accuracy zero-shot 29.2
    Printed as 29.2Independent run, measured Aug 2026Configuration: zero-shot; independent questions; exact option-set match
    Evaluating Counterfactual Sensitivity to Patient Information in Medication-Safety Reasoning paper, Zhitian Hou, Yuhang Liu, Pengkai Wang, Zeyu Liu, Guanghao Zhu, Zheng Liu, Shuo Cai, Congkai Xie, Zhijie Sang, Kun Zeng, Hongxia Yang (The Hong Kong Polytechnic University; InfiX.ai; Sun Yat-sen University), 4 Aug 2026. arXiv:2608.03028v1, Section 4, Table 2 (#S4.T2), row GPT-5.2, column Pair; row order: Model | Overall | GF | CF | Δ_GF−CF | Activation | Deactivation | Pair
    GPT-5.2 | 68.1 | 78.2 | 52.5 | 25.7 | 63.4 | 42.6 | 29.2
    Every result from this document
  9. 8MedPIC, Risk activation accuracy zero-shot 63.4
    Printed as 63.4Independent run, measured Aug 2026Configuration: zero-shot; independent questions; exact option-set match
    Evaluating Counterfactual Sensitivity to Patient Information in Medication-Safety Reasoning paper, Zhitian Hou, Yuhang Liu, Pengkai Wang, Zeyu Liu, Guanghao Zhu, Zheng Liu, Shuo Cai, Congkai Xie, Zhijie Sang, Kun Zeng, Hongxia Yang (The Hong Kong Polytechnic University; InfiX.ai; Sun Yat-sen University), 4 Aug 2026. arXiv:2608.03028v1, Section 4, Table 2 (#S4.T2), row GPT-5.2, column Activation; row order: Model | Overall | GF | CF | Δ_GF−CF | Activation | Deactivation | Pair
    GPT-5.2 | 68.1 | 78.2 | 52.5 | 25.7 | 63.4 | 42.6 | 29.2
    Every result from this document
  10. 12MedPIC, Risk deactivation accuracy zero-shot 42.6
    Printed as 42.6Independent run, measured Aug 2026Configuration: zero-shot; independent questions; exact option-set match
    Evaluating Counterfactual Sensitivity to Patient Information in Medication-Safety Reasoning paper, Zhitian Hou, Yuhang Liu, Pengkai Wang, Zeyu Liu, Guanghao Zhu, Zheng Liu, Shuo Cai, Congkai Xie, Zhijie Sang, Kun Zeng, Hongxia Yang (The Hong Kong Polytechnic University; InfiX.ai; Sun Yat-sen University), 4 Aug 2026. arXiv:2608.03028v1, Section 4, Table 2 (#S4.T2), row GPT-5.2, column Deactivation; row order: Model | Overall | GF | CF | Δ_GF−CF | Activation | Deactivation | Pair
    GPT-5.2 | 68.1 | 78.2 | 52.5 | 25.7 | 63.4 | 42.6 | 29.2
    Every result from this document
  11. –MedPIC, Published GF-minus-CF accuracy gap zero-shot 25.7
    Printed as 25.7Independent run, measured Aug 2026Configuration: zero-shot; independent questions; exact option-set match
    Evaluating Counterfactual Sensitivity to Patient Information in Medication-Safety Reasoning paper, Zhitian Hou, Yuhang Liu, Pengkai Wang, Zeyu Liu, Guanghao Zhu, Zheng Liu, Shuo Cai, Congkai Xie, Zhijie Sang, Kun Zeng, Hongxia Yang (The Hong Kong Polytechnic University; InfiX.ai; Sun Yat-sen University), 4 Aug 2026. arXiv:2608.03028v1, Section 4, Table 2 (#S4.T2), row GPT-5.2, column Δ_GF−CF; row order: Model | Overall | GF | CF | Δ_GF−CF | Activation | Deactivation | Pair
    GPT-5.2 | 68.1 | 78.2 | 52.5 | 25.7 | 63.4 | 42.6 | 29.2
    Every result from this document

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