RankingEffort benchmarks
MiniMax-M3 · Reasoning effort benchmarks
Compare measured Low, Medium, High and other settings. Every number keeps its source.
MiniMax-M3
40 measured results · 3 reported effort labels · 36 benchmark/harness combinations. Model evidence and sources →
Capability score evidence
MiniMax-M3 · Reasoning: 25.1 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 | 28.4 | +3.3 |
| Datacurve | 22.2 | -2.9 |
| LiveCodeBench | 25.0 | -0.1 |
| Scale | 26.7 | +1.6 |
| Terminal-Bench | 25.2 | +0.1 |
| Cognition | 25.8 | +0.7 |
| LiveBench | 25.5 | +0.4 |
| SWE-rebench | 25.6 | +0.5 |
| Epoch AI | 25.3 | +0.2 |
| Vals AI | 24.5 | -0.6 |
| Provider reports · Anthropic | 25.1 | +0.0 |
| Provider reports · Moonshot AI | 25.1 | -0.0 |
| Provider reports · Meta | 25.1 | -0.0 |
| Provider reports · Mistral | 25.1 | +0.0 |
| All provider reports | 25.0 | -0.1 |
Every benchmark family
| Removed evidence | Recomputed score | Change |
|---|---|---|
| omniscience | 28.7 | +3.5 |
| arc-agi | 28.3 | +3.2 |
| deepswe | 22.3 | -2.9 |
| harvey | 23.6 | -1.5 |
| gpqa | 23.9 | -1.2 |
| ifbench | 23.9 | -1.2 |
| aa-lcr | 24.0 | -1.1 |
| analyst-agent | 26.2 | +1.1 |
| epoch-game-puzzles | 24.4 | -0.7 |
| enterprise-ops | 25.9 | +0.7 |
| briefcase | 24.4 | -0.7 |
| mmmu-pro | 25.8 | +0.7 |
| frontiercode | 25.8 | +0.7 |
| simpleqa | 25.8 | +0.6 |
| gdp-pdf | 25.7 | +0.6 |
| gdpval | 24.5 | -0.6 |
| swe-rebench | 25.6 | +0.5 |
| scicode | 25.5 | +0.4 |
| mmlu-pro | 25.5 | +0.4 |
| critpt | 25.4 | +0.3 |
| multi-swe-bench | 24.8 | -0.3 |
| tau-bench | 25.4 | +0.2 |
| apex-agents | 25.4 | +0.2 |
| livebench-instructions | 25.3 | +0.2 |
| livebench-language | 25.3 | +0.2 |
| hle | 25.3 | +0.2 |
| swe-atlas-qna | 24.9 | -0.2 |
| frontiermath | 25.3 | +0.2 |
| arc-agi-3 | 25.0 | -0.1 |
| livebench-coding | 25.0 | -0.1 |
| vibe-code | 25.0 | -0.1 |
| livebench-reasoning | 25.0 | -0.1 |
| terminal-bench | 25.0 | -0.1 |
| livecodebench | 25.0 | -0.1 |
| vals-finance-agent | 25.0 | -0.1 |
| swe-atlas-test-writing | 25.0 | -0.1 |
| vals-legal-research | 25.0 | -0.1 |
| vals-code-migration | 25.1 | -0.1 |
| gmmlu | 25.2 | +0.0 |
| swe-atlas-refactoring | 25.1 | -0.0 |
| livebench-data | 25.1 | +0.0 |
| math500 | 25.1 | +0.0 |
| livebench-math | 25.1 | +0.0 |
| itbench | 25.1 | -0.0 |
| vals-excel-modeling | 25.1 | -0.0 |
| enigma-eval | 25.1 | +0.0 |
| aime | 25.1 | +0.0 |
| swe-bench-pro | 25.1 | +0.0 |
| automationbench | 25.1 | -0.0 |
What evidence is missing from the fit?
Across all collected settings for this model: 75 observations, 25 contributing, 0 matched without graph weight and 50 excluded. Counts do not establish rank eligibility.
- 1 · Benchmark family or source protocol has not been reviewed
- 2 · The evaluator reports no named effort control. This does not identify a non-reasoning configuration.
- 12 · Effort is not identified
- 13 · No reviewed effort for this catalog observation; any separately collected effort measurement is counted separately
- 22 · Supporting evidence outside the reviewed capability core
Capability profile
One configuration, seven capabilities
- AMiniMax-M3 · Reasoning4 of 7 capabilities supported
Gaps are unknown, not zero. Hollow points are preliminary.
Agentic
A30.1SupportedHard reasoning
A37.6SupportedCoding
A26.9SupportedHuman pref
UnknownKnowledge
A15.6SupportedMultimodal
A35.6PreliminaryLong context
A57.5Preliminary
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 | Reasoning | Non-reasoning | Unspecified |
|---|---|---|---|
AA-AnalystAgentBenchmark detailsShare of tasks solved on all 5 of 5 attempts · 80 tasks, 5 attempts per task · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-09-12. | 10% Reported settingsMiniMax-M3; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/minimax-m3; Mode from evaluator isReasoning metadata; effort budget not specified | Not reported | Not reported |
AA-Briefcase EloBenchmark detailsAA-Briefcase is an agentic knowledge work benchmark developed by Artificial Analysis. AA-Briefcase Elo is a combined metric that aggregates rubric pass rate, analytical quality Elo and presentation Elo · Higher is better · Evaluation results measured independently by Artificial Analysis Unit: elo. Source collected 2026-09-12. | 1,096.03 Elo Reported settingsMiniMax-M3; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/minimax-m3; Mode from evaluator isReasoning metadata; effort budget not specified | Not reported | Not reported |
AA-LCR v1.1Benchmark detailsIndependently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-09-12. | 83% Reported settingsMiniMax-M3; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/minimax-m3; Mode from evaluator isReasoning metadata; effort budget not specified | Not reported | Not reported |
AutomationBench-AABenchmark detailsShare of task objectives completed with no guardrail violations · Higher is better · Benchmark developed by Zapier · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-09-12. | 21.25% Reported settingsMiniMax-M3; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/minimax-m3; Mode from evaluator isReasoning metadata; effort budget not specified | Not reported | Not reported |
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. | 3.71% Reported settingsMiniMax-M3; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/minimax-m3; Mode from evaluator isReasoning metadata; effort budget not specified | Not reported | Not reported |
EnterpriseOps-Gym-AABenchmark detailsOverall task success rate across all eight enterprise domains (oracle tool mode) · Benchmark developed by ServiceNow Research · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-09-12. | 32.11% Reported settingsMiniMax-M3; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/minimax-m3; Mode from evaluator isReasoning metadata; effort budget not specified | Not reported | Not reported |
GDP.pdf: All-passBenchmark detailsShare of attempts where every atomic criterion passed · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-09-12. | 9.8% Reported settingsMiniMax-M3; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/minimax-m3; Mode from evaluator isReasoning metadata; effort budget not specified | Not reported | Not reported |
GDPval-AA v2 LeaderboardBenchmark detailsElo rating for performance on real-world work tasks · Anchored to a human baseline of 1,000 · Higher is better · Evaluation results measured independently by Artificial Analysis Unit: elo. Source collected 2026-09-12. | 1,303.96 Elo Reported settingsMiniMax-M3; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/minimax-m3; Mode from evaluator isReasoning metadata; effort budget not specified | Not reported | Not reported |
GPQA DiamondBenchmark detailsIndependently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-09-12. | 92.93% Reported settingsMiniMax-M3; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/minimax-m3; Mode from evaluator isReasoning metadata; effort budget not specified | Not reported | Not reported |
Harvey LAB-AA: Criterion Pass RateBenchmark detailsShare of atomic pass/fail rubric criteria the deliverables satisfy, graded by a single LLM judge · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-09-12. | 88.41% Reported settingsMiniMax-M3; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/minimax-m3; Mode from evaluator isReasoning metadata; effort budget not specified | Not reported | Not reported |
Humanity's Last ExamBenchmark detailsIndependently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-09-12. | 38.97% Reported settingsMiniMax-M3; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/minimax-m3; Mode from evaluator isReasoning metadata; effort budget not specified | Not reported | Not reported |
IFBenchBenchmark detailsIndependently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-09-12. | 82.86% Reported settingsMiniMax-M3; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/minimax-m3; Mode from evaluator isReasoning metadata; effort budget not specified | Not reported | Not reported |
MLCR-AABenchmark detailsShare of tasks judged accurate, complete, and concise · Expert + compound (hard) sets · Benchmark developed by Wisedocs · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-09-12. | 17.22% Reported settingsMiniMax-M3; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/minimax-m3; Mode from evaluator isReasoning metadata; effort budget not specified | Not reported | Not reported |
MMMU-ProBenchmark detailsIndependently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-09-12. | 78.55% Reported settingsMiniMax-M3; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/minimax-m3; Mode from evaluator isReasoning metadata; effort budget not specified | Not reported | Not reported |
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. | 1.35 Reported settingsMiniMax-M3; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/minimax-m3; Mode from evaluator isReasoning metadata; effort budget not specified | Not reported | Not reported |
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. | 16.7% Reported settingsMiniMax-M3; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/minimax-m3; Mode from evaluator isReasoning metadata; effort budget not specified | Not reported | Not reported |
SciCodeBenchmark detailsIndependently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-09-12. | 47.11% Reported settingsMiniMax-M3; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/minimax-m3; Mode from evaluator isReasoning metadata; effort budget not specified | Not reported | Not reported |
𝜏²-Bench TelecomBenchmark detailsIndependently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-09-12. | 88.89% Reported settingsMiniMax-M3; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/minimax-m3; Mode from evaluator isReasoning metadata; effort budget not specified | Not reported | Not reported |
𝜏³-BankingBenchmark detailsBenchmark developed by Sierra Research · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-09-12. | 15.26% Reported settingsMiniMax-M3; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/minimax-m3; Mode from evaluator isReasoning metadata; effort budget not specified | Not reported | Not reported |
Terminal-Bench HardBenchmark detailsIndependently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-09-12. | 42.42% Reported settingsMiniMax-M3; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/minimax-m3; Mode from evaluator isReasoning metadata; effort budget not specified | Not reported | Not reported |
Terminal-Bench v2.1Benchmark detailsBenchmark developed by the Laude Institute and open-source contributors · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-09-12. | 65.17% Reported settingsMiniMax-M3; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/minimax-m3; Mode from evaluator isReasoning metadata; effort budget not specified | Not reported | Not reported |
Terminal-Bench v4.0Benchmark detailsBenchmark developed by the Laude Institute, Stanford, and open-source contributors · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-09-12. | 2.02% Reported settingsMiniMax-M3; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/minimax-m3; Mode from evaluator isReasoning metadata; effort budget not specified | Not reported | Not reported |
FrontierCode 1.1 · extended-mini-swe-agentBenchmark detailsFrontierCode 1.1; mini-swe-agent. Open each result for its exact effort, task subset, metric and protocol details. Unit: percent. Source collected 2026-09-12. | Not reported | Not reported | 28.54% Reported settingsFrontierCode 1.1; extended; 150 tasks; mini-swe-agent; source effort none; weighted rubric score, not pass rate; unfair internet runs zeroed by evaluator; flag rate 0.0107 The evaluator reports no named effort control. This does not identify a non-reasoning configuration. |
FrontierCode 1.1 · main-mini-swe-agentBenchmark detailsFrontierCode 1.1; mini-swe-agent. Open each result for its exact effort, task subset, metric and protocol details. Unit: percent. Source collected 2026-09-12. | Not reported | Not reported | 14.7% Reported settingsFrontierCode 1.1; main; 100 tasks; mini-swe-agent; source effort none; weighted rubric score, not pass rate; unfair internet runs zeroed by evaluator; flag rate 0.015 The evaluator reports no named effort control. This does not identify a non-reasoning configuration. |
Epoch · Chess Puzzles · v1.1.6Benchmark detailsEpoch AI internal evaluation. Mean accuracy under the published setting; exact task version and scorer stay separate. Related tasks share a family budget. Data by Epoch AI, CC BY. Unit: percent. Source collected 2026-09-12. | Not reported | 4% Reported settingsEpoch AI Inspect; task 1.1.6; scorer model_extracted_exact_match; model=MiniMax-M3_none; run=jyWVTGV3ZXhotEFLLGQsKi; mean accuracy; https://epoch.ai/data/benchmarks.csv | 14% Reported settingsEpoch AI Inspect; task 1.1.6; scorer model_extracted_exact_match; model=MiniMax-M3; run=XwemU6ABotEuG9o5TRLG2r; mean accuracy; https://epoch.ai/data/benchmarks.csv |
Epoch · GPQA diamond · v1.0.11Benchmark detailsEpoch AI internal evaluation. Mean accuracy under the published setting; exact task version and scorer stay separate. Related tasks share a family budget. Data by Epoch AI, CC BY. Unit: percent. Source collected 2026-09-12. | Not reported | 81.31% Reported settingsEpoch AI Inspect; task 1.0.11; scorer choice; model=MiniMax-M3_none; run=KM4G49tQZB8ce67RxYGyMy; mean accuracy; https://epoch.ai/data/benchmarks.csv | 90.91% Reported settingsEpoch AI Inspect; task 1.0.11; scorer choice; model=MiniMax-M3; run=hDESmyGFrbZDomjff3rqzD; mean accuracy; https://epoch.ai/data/benchmarks.csv |
Epoch · Mystery Game Puzzles · v1.0.4 · Tool submissionBenchmark detailsEpoch AI internal evaluation. Mean accuracy under the published setting; exact task version and scorer stay separate. Related tasks share a family budget. Data by Epoch AI, CC BY. Unit: percent. Source collected 2026-09-12. | Not reported | 8% Reported settingsEpoch AI Inspect; task 1.0.4; scorer agent_submitted_next_move_scorer; model=MiniMax-M3_none; run=jWHk7BTYHQRXk2rXCbnpcS; mean accuracy; https://epoch.ai/data/benchmarks.csv | 7% Reported settingsEpoch AI Inspect; task 1.0.4; scorer agent_submitted_next_move_scorer; model=MiniMax-M3; run=GGpgwGRFVATVJdQr8TgRc9; mean accuracy; https://epoch.ai/data/benchmarks.csv |
Epoch · OTIS Mock AIME 2024-2025 · v1.1.6Benchmark detailsEpoch AI internal evaluation. Mean accuracy under the published setting; exact task version and scorer stay separate. Related tasks share a family budget. Data by Epoch AI, CC BY. Unit: percent. Source collected 2026-09-12. | Not reported | 26.67% Reported settingsEpoch AI Inspect; task 1.1.6; scorer model_extracted_exact_match; model=MiniMax-M3_none; run=97t77hRrNae6Va8fBqBhPy; mean accuracy; https://epoch.ai/data/benchmarks.csv | 71.11% Reported settingsEpoch AI Inspect; task 1.1.6; scorer model_extracted_exact_match; model=MiniMax-M3; run=79ZP6iwoBaF5t9a5VRqPnw; mean accuracy; https://epoch.ai/data/benchmarks.csv |
Vals AI · Finance Agent v2Benchmark detailsOverall weighted rubric accuracy, averaged over three runs on 450 tasks. Dealbreaker failures and timeouts score zero. Related categories and all-pass scores are not additional votes. Three-model judge panel; private test set. Unit: percent. Source collected 2026-09-12. | Not reported | Not reported | 48.27% Reported settings{"checkpoint":"MiniMax-M3","evaluatorModel":"minimax/MiniMax-M3","sourceUpdatedOn":"2026-09-10","reasoning_effort":null,"compute_effort":null,"reasoning":null,"temperature":1,"top_p":0.95,"max_output_tokens":512000,"verbosity":null,"provider":"MiniMax","harness":null} |
Vals AI · Code Migration v1Benchmark detailsHidden behavior-test pass rate, equally weighted across 40 repositories (30 CLI and 10 COBOL-to-Java). Anti-cheat failures score zero. Code-quality ratings and language splits are not additional votes. Unit: percent. Source collected 2026-09-12. | Not reported | Not reported | 19.93% Reported settings{"checkpoint":"MiniMax-M3","evaluatorModel":"minimax/MiniMax-M3","sourceUpdatedOn":"2026-09-10","reasoning_effort":null,"compute_effort":null,"reasoning":null,"temperature":1,"top_p":0.95,"max_output_tokens":512000,"verbosity":null,"provider":"MiniMax","harness":null} |
Vals AI · Legal Research Bench v1Benchmark detailsAll-pass accuracy on 208 private legal research tasks. Every expert rubric check must pass; GPT-5.4 judges responses. Partial-credit scores and practice-area splits are not additional votes. Unit: percent. Source collected 2026-09-12. | Not reported | Not reported | 29.81% Reported settings{"checkpoint":"MiniMax-M3","evaluatorModel":"minimax/MiniMax-M3","sourceUpdatedOn":"2026-09-10","reasoning_effort":null,"compute_effort":null,"reasoning":null,"temperature":1,"top_p":0.95,"max_output_tokens":512000,"verbosity":null,"provider":"MiniMax","harness":null} |
Vals AI · Excel Modeling Benchmark v1Benchmark detailsMean of seven equally weighted task categories. Template submissions use recalculated Excel cell accuracy; scratch submissions use rubric checks judged by GPT-5.4 Mini XHigh. Partial credit does not mean task completion. Unit: percent. Source collected 2026-09-12. | Not reported | Not reported | 47.76% Reported settings{"checkpoint":"MiniMax-M3","evaluatorModel":"minimax/MiniMax-M3","sourceUpdatedOn":"2026-09-10","reasoning_effort":null,"compute_effort":null,"reasoning":null,"temperature":1,"top_p":0.95,"max_output_tokens":512000,"verbosity":null,"provider":"MiniMax","harness":null} |
Vals AI · MMLU-Pro v1Benchmark detailsMean accuracy across 14 subjects under Vals five-shot prompting. Subject splits share one family and are not additional votes. Vals labels this benchmark archived; it is historical corroboration, not ongoing frontier evaluation. Unit: percent. Source collected 2026-09-12. | Not reported | Not reported | 84.22% Reported settings{"checkpoint":"MiniMax-M3","evaluatorModel":"minimax/MiniMax-M3","sourceUpdatedOn":"2026-09-01","reasoning_effort":null,"compute_effort":null,"reasoning":null,"temperature":1,"top_p":0.95,"max_output_tokens":512000,"verbosity":null,"provider":"MiniMax","harness":null} |
Vals AI · Terminal-Bench 2.1Benchmark detailsOverall task pass rate under the shared Terminus 2 configuration. All task tests must pass. Difficulty splits share one family. Fable 5 and Opus 5 mixed-checkpoint fallback runs are excluded. Unit: percent. Source collected 2026-09-12. | Not reported | Not reported | 53.56% Reported settings{"checkpoint":"MiniMax-M3","evaluatorModel":"minimax/MiniMax-M3","sourceUpdatedOn":"2026-09-10","reasoning_effort":null,"compute_effort":null,"reasoning":null,"temperature":1,"top_p":0.95,"max_output_tokens":512000,"verbosity":null,"provider":"MiniMax","harness":null} |
Vals AI · Vibe Code Bench v1.1Benchmark detailsMean app test pass rate on the canonical v1.1 test set. Browser Use executes workflow tests; each test requires at least 90% of its substeps. Automated judging can introduce error. Alternate agents are excluded. Unit: percent. Source collected 2026-09-12. | Not reported | Not reported | 47.57% Reported settings{"checkpoint":"MiniMax-M3","evaluatorModel":"minimax/MiniMax-M3","sourceUpdatedOn":"2026-09-10","reasoning_effort":null,"compute_effort":null,"reasoning":null,"temperature":1,"top_p":0.95,"max_output_tokens":512000,"verbosity":null,"provider":"MiniMax","harness":"OpenHands"} |
Vals AI · Harvey Legal Agent Benchmark v1Benchmark detailsMean task resolution across two judges (GPT-5.5 Medium and Sonnet 4.6), requiring every criterion to pass. Criteria pass rates and practice-area splits do not add votes. Shared Harvey family; Fable 5 fallback run excluded. Unit: percent. Source collected 2026-09-12. | Not reported | Not reported | 4.17% Reported settings{"checkpoint":"MiniMax-M3","evaluatorModel":"minimax/MiniMax-M3","sourceUpdatedOn":"2026-09-10","reasoning_effort":null,"compute_effort":null,"reasoning":null,"temperature":1,"top_p":0.95,"max_output_tokens":512000,"verbosity":null,"provider":"MiniMax","harness":null} |
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