RankingEffort benchmarks
GPT-4o · Non-reasoning effort benchmarks
Compare measured Low, Medium, High and other settings. Every number keeps its source.
GPT-4o
41 measured results · 1 reported effort labels · 14 benchmark/harness combinations. Model evidence and sources →
Capability score evidence
GPT-4o · Non-reasoning: 2.9 overall comparison score. Meets the overall evidence requirements.
Which sources carry the weight?
- Artificial Analysis · 100.0% direct comparison weight · independent
These shares describe the comparisons entering the fit, not fractions of the final score.
How sensitive is this score?
Remove one evaluator or family and refit the graph against the same overall panel. Values use the matching dataset audited 2026-09-12. These are sensitivity checks, not confidence intervals; ranking eligibility may also change.
| Removed evidence | Recomputed score | Change |
|---|---|---|
| Artificial Analysis | Comparison path lost | — |
| ARC Prize | 3.5 | +0.6 |
| Datacurve | 2.5 | -0.4 |
| LiveCodeBench | 2.9 | -0.0 |
| Scale | 3.2 | +0.3 |
| Terminal-Bench | 2.9 | -0.0 |
| Cognition | 3.0 | +0.2 |
| LiveBench | 3.0 | +0.1 |
| SWE-rebench | 3.0 | +0.1 |
| Epoch AI | 2.9 | +0.0 |
| Vals AI | 2.8 | -0.1 |
| Provider reports · Anthropic | 2.9 | +0.0 |
| Provider reports · Moonshot AI | 2.9 | -0.0 |
| Provider reports · Meta | 2.9 | -0.0 |
| Provider reports · Mistral | 2.9 | +0.0 |
| All provider reports | 2.9 | -0.0 |
Every benchmark family
| Removed evidence | Recomputed score | Change |
|---|---|---|
| arc-agi | 3.5 | +0.6 |
| deepswe | 2.5 | -0.4 |
| terminal-bench | 2.6 | -0.3 |
| critpt | 3.1 | +0.2 |
| mmmu-pro | 3.1 | +0.2 |
| hle | 3.1 | +0.2 |
| frontiercode | 3.0 | +0.2 |
| epoch-game-puzzles | 2.7 | -0.1 |
| simpleqa | 3.0 | +0.1 |
| omniscience | 2.8 | -0.1 |
| mmlu-pro | 3.0 | +0.1 |
| ifbench | 2.8 | -0.1 |
| swe-rebench | 3.0 | +0.1 |
| tau-bench | 2.8 | -0.1 |
| scicode | 3.0 | +0.1 |
| multi-swe-bench | 2.8 | -0.0 |
| livebench-instructions | 2.9 | +0.0 |
| gdp-pdf | 2.9 | +0.0 |
| harvey | 2.9 | -0.0 |
| aa-lcr | 2.9 | -0.0 |
| livebench-language | 2.9 | +0.0 |
| frontiermath | 2.9 | +0.0 |
| apex-agents | 2.9 | +0.0 |
| swe-atlas-qna | 2.9 | -0.0 |
| math500 | 2.9 | +0.0 |
| livebench-coding | 2.9 | -0.0 |
| gmmlu | 2.9 | +0.0 |
| gpqa | 2.9 | -0.0 |
| arc-agi-3 | 2.9 | -0.0 |
| vibe-code | 2.9 | -0.0 |
| livebench-reasoning | 2.9 | -0.0 |
| vals-finance-agent | 2.9 | -0.0 |
| vals-legal-research | 2.9 | -0.0 |
| swe-atlas-test-writing | 2.9 | -0.0 |
| vals-code-migration | 2.9 | -0.0 |
| analyst-agent | 2.9 | +0.0 |
| livecodebench | 2.9 | +0.0 |
| gdpval | 2.9 | +0.0 |
| itbench | 2.9 | -0.0 |
| livebench-data | 2.9 | +0.0 |
| briefcase | 2.9 | -0.0 |
| aime | 2.9 | +0.0 |
| vals-excel-modeling | 2.9 | -0.0 |
| livebench-math | 2.9 | +0.0 |
| enterprise-ops | 2.9 | +0.0 |
| swe-atlas-refactoring | 2.9 | -0.0 |
| enigma-eval | 2.9 | +0.0 |
| automationbench | 2.9 | +0.0 |
| swe-bench-pro | 2.9 | +0.0 |
What evidence is missing from the fit?
Across all collected settings for this model: 43 observations, 5 contributing, 0 matched without graph weight and 38 excluded. Counts do not establish rank eligibility.
- 34 · Conflicting values for this configuration in the same evaluation
- 2 · Benchmark family or source protocol has not been reviewed
- 2 · No reviewed effort for this catalog observation; any separately collected effort measurement is counted separately
Capability profile
One configuration, seven capabilities
- AGPT-4o · Non-reasoning0 of 7 capabilities supported
Gaps are unknown, not zero. Hollow points are preliminary.
Agentic
UnknownHard reasoning
A2.9PreliminaryCoding
A3.7PreliminaryHuman pref
UnknownKnowledge
UnknownMultimodal
A3.5PreliminaryLong context
Unknown
Each profile belongs to the named configuration. Capability scores use a shared panel for all axes, distinct from the overall ranking panel; they are not accuracy percentages or direct head-to-head wins.
Compare this configuration →Explore the model evidence profile →
| Benchmark / source | Non-reasoning |
|---|---|
AIME 2025Benchmark detailsIndependently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-09-12. | 25.67% Reported settingsGPT-4o (March 2025, chatgpt-4o-latest); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o-chatgpt-03-25; Mode from evaluator isReasoning metadata; effort budget not specified 6% Reported settingsGPT-4o (Nov '24); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o; Mode from evaluator isReasoning metadata; effort budget not specified |
AA-LCR v1.1Benchmark detailsIndependently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-09-12. | 41% Reported settingsGPT-4o (Aug '24); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o-2024-08-06; Mode from evaluator isReasoning metadata; effort budget not specified 56% Reported settingsGPT-4o (ChatGPT); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o-chatgpt; Mode from evaluator isReasoning metadata; effort budget not specified 49.33% Reported settingsGPT-4o (Nov '24); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o; Mode from evaluator isReasoning metadata; effort budget not specified |
CritPtBenchmark detailsBenchmark developed by Argonne and UIUC, with contributions from 60+ researchers globally · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-09-12. | 0% Reported settingsGPT-4o (Aug '24); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o-2024-08-06; Mode from evaluator isReasoning metadata; effort budget not specified 0% Reported settingsGPT-4o (Nov '24); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o; Mode from evaluator isReasoning metadata; effort budget not specified |
GPQA DiamondBenchmark detailsIndependently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-09-12. | 52.63% Reported settingsGPT-4o (May '24); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o-2024-05-13; Mode from evaluator isReasoning metadata; effort budget not specified 65.45% Reported settingsGPT-4o (March 2025, chatgpt-4o-latest); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o-chatgpt-03-25; Mode from evaluator isReasoning metadata; effort budget not specified 52.12% Reported settingsGPT-4o (Aug '24); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o-2024-08-06; Mode from evaluator isReasoning metadata; effort budget not specified 51.11% Reported settingsGPT-4o (ChatGPT); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o-chatgpt; Mode from evaluator isReasoning metadata; effort budget not specified 54.34% Reported settingsGPT-4o (Nov '24); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o; Mode from evaluator isReasoning metadata; effort budget not specified |
Humanity's Last ExamBenchmark detailsIndependently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-09-12. | 2.73% Reported settingsGPT-4o (ChatGPT); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o-chatgpt; Mode from evaluator isReasoning metadata; effort budget not specified 3.97% Reported settingsGPT-4o (March 2025, chatgpt-4o-latest); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o-chatgpt-03-25; Mode from evaluator isReasoning metadata; effort budget not specified 2.42% Reported settingsGPT-4o (Nov '24); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o; Mode from evaluator isReasoning metadata; effort budget not specified 1.76% Reported settingsGPT-4o (May '24); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o-2024-05-13; Mode from evaluator isReasoning metadata; effort budget not specified 2.33% Reported settingsGPT-4o (Aug '24); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o-2024-08-06; Mode from evaluator isReasoning metadata; effort budget not specified |
IFBenchBenchmark detailsIndependently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-09-12. | 35.99% Reported settingsGPT-4o (Aug '24); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o-2024-08-06; Mode from evaluator isReasoning metadata; effort budget not specified 34.29% Reported settingsGPT-4o (Nov '24); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o; Mode from evaluator isReasoning metadata; effort budget not specified |
LiveCodeBenchBenchmark detailsIndependently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-09-12. | 31.75% Reported settingsGPT-4o (Aug '24); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o-2024-08-06; Mode from evaluator isReasoning metadata; effort budget not specified 33.44% Reported settingsGPT-4o (May '24); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o-2024-05-13; Mode from evaluator isReasoning metadata; effort budget not specified 42.54% Reported settingsGPT-4o (March 2025, chatgpt-4o-latest); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o-chatgpt-03-25; Mode from evaluator isReasoning metadata; effort budget not specified 30.9% Reported settingsGPT-4o (Nov '24); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o; Mode from evaluator isReasoning metadata; effort budget not specified |
MATH-500Benchmark detailsIndependently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-09-12. | 89.27% Reported settingsGPT-4o (March 2025, chatgpt-4o-latest); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o-chatgpt-03-25; Mode from evaluator isReasoning metadata; effort budget not specified 75.93% Reported settingsGPT-4o (Nov '24); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o; Mode from evaluator isReasoning metadata; effort budget not specified 79.73% Reported settingsGPT-4o (ChatGPT); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o-chatgpt; Mode from evaluator isReasoning metadata; effort budget not specified 79.47% Reported settingsGPT-4o (Aug '24); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o-2024-08-06; Mode from evaluator isReasoning metadata; effort budget not specified 79.13% Reported settingsGPT-4o (May '24); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o-2024-05-13; Mode from evaluator isReasoning metadata; effort budget not specified |
MMLU-ProBenchmark detailsIndependently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-09-12. | 80.29% Reported settingsGPT-4o (March 2025, chatgpt-4o-latest); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o-chatgpt-03-25; Mode from evaluator isReasoning metadata; effort budget not specified 74.77% Reported settingsGPT-4o (Nov '24); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o; Mode from evaluator isReasoning metadata; effort budget not specified 77.34% Reported settingsGPT-4o (ChatGPT); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o-chatgpt; Mode from evaluator isReasoning metadata; effort budget not specified 73.95% Reported settingsGPT-4o (May '24); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o-2024-05-13; Mode from evaluator isReasoning metadata; effort budget not specified |
MMMU-ProBenchmark detailsIndependently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-09-12. | 56.3% Reported settingsGPT-4o (Aug '24); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o-2024-08-06; Mode from evaluator isReasoning metadata; effort budget not specified |
AA-Omniscience IndexBenchmark detailsAA-Omniscience Index (higher is better) measures knowledge reliability and hallucination. It rewards correct answers, penalizes hallucinations, and has no penalty for refusing to answer. Scores range from -100 to 100, where 0 means as many correct as incorrect answers, and negative scores mean more incorrect than correct. · Evaluation results measured independently by Artificial Analysis Unit: index. Source collected 2026-09-12. | -10.52 Reported settingsGPT-4o (Nov '24); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o; Mode from evaluator isReasoning metadata; effort budget not specified -20.87 Reported settingsGPT-4o (Aug '24); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o-2024-08-06; Mode from evaluator isReasoning metadata; effort budget not specified |
AA-Omniscience AccuracyBenchmark detailsAA-Omniscience Accuracy (higher is better) measures the proportion of correctly answered questions out of all questions, regardless of whether the model chooses to answer · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-09-12. | 23.7% Reported settingsGPT-4o (Aug '24); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o-2024-08-06; Mode from evaluator isReasoning metadata; effort budget not specified 19.87% Reported settingsGPT-4o (Nov '24); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o; Mode from evaluator isReasoning metadata; effort budget not specified |
𝜏²-Bench TelecomBenchmark detailsIndependently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-09-12. | 28.95% Reported settingsGPT-4o (Aug '24); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o-2024-08-06; Mode from evaluator isReasoning metadata; effort budget not specified 25.15% Reported settingsGPT-4o (Nov '24); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o; Mode from evaluator isReasoning metadata; effort budget not specified |
Terminal-Bench HardBenchmark detailsIndependently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-09-12. | 8.33% Reported settingsGPT-4o (Nov '24); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o; Mode from evaluator isReasoning metadata; effort budget not specified 8.33% Reported settingsGPT-4o (Aug '24); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/gpt-4o-2024-08-06; Mode from evaluator isReasoning metadata; effort budget not specified |
What these comparisons mean
Each source reports its own effort labels. Matching labels do not establish equal compute budgets or identical fallback behavior. Open Reported settings to inspect the exact model name, agent and task coverage. Multiple results at one level remain visible rather than selecting the best. Source-reported None or Non-reasoning labels are not treated as evidence that an API supports those settings.
These measurements use their own dated source collection. The leaderboard fits identified configurations jointly; it contains no pooled model ratings. Explicit thinking budgets are separate configurations. Read the methodology.
Download all effort benchmark results · 7,424 results across 240 models · Collected 2026-09-12