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Model profile

GPT-5.1

OpenAIEstablishedReleased Nov 13, 2025
Data verified
Overall Score
53.65Public #94 of 200
Arena Elo
1455
Eligible category ranks
2of 8
Price (1M tokens)
$1.25 in / $10 out
API pricing
Speed
111tok/s
Context
200K

Evidence coverage

21 of 321 tracked benchmarks are published. 4 are verified and 17 provisional. 7 of 8 categories are measured.

Updated July 20, 2026Methodology
Published / tracked
21 / 321
Verified
4
Provisional
17
Categories with evidence
7 / 8

Evidence by category

  • Agentic5 benchmarks
    Mixed evidence
  • Coding3 benchmarks
    Mixed evidence
  • Reasoning2 benchmarks
    Reported
  • Knowledge6 benchmarks
    Reported
  • Math2 benchmarks
    Verified
  • Multilingual0 benchmarks
    Not measured
  • Multimodal2 benchmarks
    Reported
  • Inst. Following1 benchmark
    Reported
ProprietaryReasoning
Confidence:
Low
base

GPT-5.1 ranks #94 out of 200 models on the public leaderboard with an overall score of 53.65/100. It does not yet have enough sourced coverage for BenchLM's verified leaderboard. While not a frontier model, it offers specific advantages depending on the use case.

GPT-5.1 is a proprietary model with a 200K token context window. It uses explicit chain-of-thought reasoning, which typically improves performance on math and complex reasoning tasks at the cost of higher latency and token usage.

This profile currently has 21 of 321 tracked benchmarks. BenchLM only exposes non-generated benchmark rows publicly, so missing categories stay blank until a sourced evaluation is available.

Its strongest category is Coding (#46), while its weakest is Agentic (#56). This performance profile makes it particularly well-suited for software development and code generation tasks.

Peer position

Exact provisional scores and ranks for the closest listed peers. A score can appear before a model clears the evidence threshold for a rank, so equal scores can have different rank states.

Range 53.4354.06

  1. MiMo-V2-Flash
    Xiaomi
    #9154.06
    MiMo-V2-Flash is #91 with a score of 54.06.
    Compare
  2. DeepSeek V4 Flash (High)
    DeepSeek
    #9253.95
    DeepSeek V4 Flash (High) is #92 with a score of 53.95.
    Compare
  3. Qwen3.6-27B
    Alibaba
    #9353.82
    Qwen3.6-27B is #93 with a score of 53.82.
    Compare
  4. GPT-5.1Current model
    OpenAI
    #9453.65
    GPT-5.1 is #94 with a score of 53.65.
  5. DeepSeek V3.1
    DeepSeek
    #9553.64
    DeepSeek V3.1 is #95 with a score of 53.64.
    Compare
  6. Claude Sonnet 4.5
    Anthropic
    #9653.61
    Claude Sonnet 4.5 is #96 with a score of 53.61.
    Compare
  7. DeepSeek V3.1 (Reasoning)
    DeepSeek
    #9753.43
    DeepSeek V3.1 (Reasoning) is #97 with a score of 53.43.
    Compare

Category percentile

More

Relative position among models eligible for each sourced category. A higher percentile means a stronger position within that category's ranked cohort; 100 is highest.

  1. Coding63%
    Eligible cohort rank #46 of 122Category score 52.9
  2. Agentic53%
    Eligible cohort rank #56 of 119Category score 48.6

Category evidence

Scores and ranks appear only where this model has published benchmark evidence. Categories without displayable source records remain not measured.

Category scores, ranks, weighting, benchmark coverage, and evidence status
CategoryScore
AgenticRank #56 of 119Percentile 53rdWeight 22%5 benchmarksMixed sources48.6
CodingRank #46 of 122Percentile 63rdWeight 20%3 benchmarksMixed sources52.9
ReasoningRank Not rankedWeight 17%2 benchmarksReported63.4
KnowledgeRank Not rankedWeight 12%6 benchmarksReported60.4
MathRank Not rankedWeight 5%2 benchmarksVerified49.9
MultilingualWeight 7%0 benchmarksNot measuredNot measured
MultimodalRank Not rankedWeight 12%2 benchmarksReported92.0
Inst. FollowingRank Not rankedWeight 5%1 benchmarkReported89.0

Chatbot Arena performance

Scroll horizontally to inspect confidence intervals and vote counts.

Chatbot Arena Elo, confidence interval, and vote count by evaluation view
ViewEloConfidence intervalVotes
Text Overall1455±3.840,789
Coding1491±7.18,205
Math1455±11.92,489
Instruction Following1448±6.510,729
Creative Writing1430±8.36,042
Multi-turn1463±7.77,116
Hard Prompts1474±5.021,724
Hard Prompts (English)1479±6.610,337
Longer Query1459±6.610,250

Benchmark Details

Rows below have a displayable published verification record. Each source link and provenance note remains in the page HTML while its category is closed. Source-unverified manual rows and generated rows stay hidden.

Agentic5 benchmarks
AA Agentic IndexReported

Artificial Analysis Agentic Index

21.0%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
τ²-bench resultsReported

τ²-Bench Tool-Agent-User Evaluation

81.9%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
Gert LabsBenchmark exact

Gert Labs Composite Game Benchmark

41.24%Display only
Source: Gert Labs rankingsProvenance: Gert Labs reports this composite leaderboard score in the public rankings API. BenchLM scales the source gscore from 0-1 to 0-100 and stores it as a display-only agentic benchmark.
GDPval-AAReported

GDPval-AA normalized

24.4%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
GDPval-AAReported
987Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
Coding3 benchmarks
Vibe Code BenchBenchmark exact

Vibe Code Bench v1.1

24.61%Display only
Source: Vals AI: Vibe Code Bench v1.1Provenance: Vals Vibe Code Bench v1.1 reports this exact row under openai/gpt-5.1-2025-11-13; BenchLM stores it on the local vibeCodeBench key.
AA Coding IndexReported

Artificial Analysis Coding Index

49.4%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
AA-SciCodeReported

Artificial Analysis SciCode

43.3%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
Reasoning2 benchmarks
AA-LCRReported

Artificial Analysis Long Context Reasoning

75.0%Display only
Source: Artificial Analysis: artificial-analysis-long-context-reasoning leaderboardProvenance: Display-only row synced from the current Artificial Analysis evaluation leaderboard. It is excluded from BenchLM weighted scoring.
CritPtReported

Critical Physics Tasks

4.9%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
Knowledge6 benchmarks
Artificial Analysis Intelligence IndexReported
36.9%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
AA-GPQA DiamondReported

Artificial Analysis GPQA Diamond

87.3%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
AA-HLEReported

Artificial Analysis Humanity's Last Exam

26.5%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
AA-Omniscience IndexReported

Artificial Analysis Omniscience Index

5.6%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
AA-Omniscience AccuracyReported

Artificial Analysis Omniscience Accuracy

37.6%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
AA-Omniscience Hallucination RateReported

Artificial Analysis Omniscience Hallucination Rate

51.3%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
Math2 benchmarks
FrontierMath v2 (Tiers 1-3)Benchmark exact

FrontierMath v2 Tiers 1-3

31.034%Weighted 30%
Source: Epoch AI FrontierMath v2 leaderboardProvenance: Epoch AI reports FrontierMath v2 Tiers 1-3 at 31.034% for gpt-5.1-2025-11-13_high. BenchLM selects the highest published thinking effort for the model and stores the v2 benchmark slice separately.
FrontierMath v2 (Tier 4)Benchmark exact

FrontierMath v2 Tier 4

12.500%Weighted 10%
Source: Epoch AI FrontierMath v2 leaderboardProvenance: Epoch AI reports FrontierMath v2 Tier 4 at 12.5% for gpt-5.1-2025-11-13_high. BenchLM selects the highest published thinking effort for the model and stores the v2 benchmark slice separately.
Multimodal2 benchmarks
AA-MMMU-ProReported

Artificial Analysis MMMU-Pro

75.5%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.
Design Arena WebsiteReported

Design Arena Website Elo

1220Display only
Source: OpenRouter model benchmarksProvenance: Display-only Design Arena Website Elo synced from OpenRouter model benchmark metadata. It is excluded from BenchLM weighted scoring.
Inst. Following1 benchmark
AA-IFBenchReported

Artificial Analysis IFBench

72.9%Display only
Source: Artificial Analysis model benchmarksProvenance: Display-only row synced from the current Artificial Analysis model payload. It is excluded from BenchLM weighted scoring.

Frequently Asked Questions

How does GPT-5.1 perform overall in AI benchmarks?

GPT-5.1 has 21 published benchmark scores on BenchLM, but it does not yet have enough non-generated coverage to receive a global overall rank.

Is GPT-5.1 good for knowledge and understanding?

GPT-5.1 has visible benchmark coverage in knowledge and understanding, but BenchLM does not currently assign it a global category rank there.

Is GPT-5.1 good for coding and programming?

GPT-5.1 ranks #46 out of 122 models in coding and programming benchmarks with an average score of 52.9. There are stronger options in this category.

Is GPT-5.1 good for mathematics?

GPT-5.1 has visible benchmark coverage in mathematics, but BenchLM does not currently assign it a global category rank there.

Is GPT-5.1 good for reasoning and logic?

GPT-5.1 has visible benchmark coverage in reasoning and logic, but BenchLM does not currently assign it a global category rank there.

Is GPT-5.1 good for agentic tool use and computer tasks?

GPT-5.1 ranks #56 out of 119 models in agentic tool use and computer tasks benchmarks with an average score of 48.6. There are stronger options in this category.

Is GPT-5.1 good for multimodal and grounded tasks?

GPT-5.1 has visible benchmark coverage in multimodal and grounded tasks, but BenchLM does not currently assign it a global category rank there.

Is GPT-5.1 good for instruction following?

GPT-5.1 has visible benchmark coverage in instruction following, but BenchLM does not currently assign it a global category rank there.

Does GPT-5.1 have full benchmark coverage on BenchLM?

Not yet. GPT-5.1 currently has 21 published benchmark scores out of the 321 benchmarks BenchLM tracks. BenchLM only exposes non-generated public benchmark rows, so missing categories stay blank until a sourced evaluation is available.

What is the context window size of GPT-5.1?

GPT-5.1 has a published context window of 200K, which determines how much text it can process in a single interaction.

Last updated: July 20, 2026 · Runtime metrics stay blank until BenchLM has a sourced snapshot.

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