RankingEffort benchmarks

Qwen3.7-max effort benchmarks

Compare measured Low, Medium, High and other settings. Every number keeps its source.

Qwen3.7-max

37 measured results · 3 reported effort labels · 36 benchmark/harness combinations. Model evidence and sources →

Capability score evidence

Qwen3.7-max · Reasoning: 31.4 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 evidenceRecomputed scoreChange
Artificial AnalysisComparison path lost
ARC Prize34.9+3.5
Datacurve28.1-3.3
LiveCodeBench31.2-0.2
Scale33.0+1.6
Terminal-Bench31.5+0.1
Cognition32.1+0.7
LiveBench31.8+0.4
SWE-rebench31.9+0.5
Epoch AI31.4-0.0
Vals AI30.7-0.7
Provider reports · Anthropic31.4+0.0
Provider reports · Moonshot AI31.4-0.0
Provider reports · Meta31.3-0.1
Provider reports · Mistral31.4+0.0
All provider reports31.3-0.1
Every benchmark family
Removed evidenceRecomputed scoreChange
arc-agi34.8+3.4
deepswe28.2-3.2
gdp-pdf32.8+1.5
enterprise-ops30.1-1.3
itbench30.1-1.3
omniscience32.5+1.1
mmmu-pro32.4+1.0
gpqa30.4-1.0
ifbench30.4-1.0
tau-bench32.2+0.8
epoch-game-puzzles30.6-0.8
frontiercode32.1+0.7
simpleqa32.1+0.7
swe-rebench31.9+0.5
scicode31.9+0.5
mmlu-pro31.8+0.4
briefcase31.8+0.4
aa-lcr31.0-0.4
automationbench31.8+0.4
hle31.7+0.3
analyst-agent31.7+0.3
multi-swe-bench31.1-0.3
apex-agents31.7+0.3
livebench-instructions31.6+0.2
livebench-language31.6+0.2
swe-atlas-qna31.2-0.2
frontiermath31.6+0.2
arc-agi-331.2-0.2
harvey31.2-0.2
critpt31.2-0.1
vibe-code31.3-0.1
livebench-coding31.3-0.1
livebench-reasoning31.3-0.1
livecodebench31.3-0.1
swe-atlas-test-writing31.3-0.1
vals-finance-agent31.3-0.1
vals-legal-research31.3-0.1
vals-code-migration31.3-0.1
gmmlu31.4+0.1
gdpval31.4+0.0
terminal-bench31.4+0.0
swe-atlas-refactoring31.4-0.0
livebench-data31.4+0.0
livebench-math31.4+0.0
math50031.4+0.0
vals-excel-modeling31.4-0.0
enigma-eval31.4+0.0
swe-bench-pro31.4+0.0
aime31.4+0.0
What evidence is missing from the fit?

Across all collected settings for this model: 69 observations, 21 contributing, 0 matched without graph weight and 48 excluded. Counts do not establish rank eligibility.

  • 1 · Benchmark family or source protocol has not been reviewed
  • 15 · Effort is not identified
  • 1 · The Qwen card cites an external leaderboard or release report for this comparator; it is not a new Qwen evaluation.
  • 9 · No reviewed effort for this catalog observation; any separately collected effort measurement is counted separately
  • 22 · Supporting evidence outside the reviewed capability core
Inspect every observation and exclusion →

Capability profile

One configuration, seven capabilities

Comparison score · 0–100
Qwen3.7-max · Reasoning capability radarComparison scores from 0 to 100. Unknown capabilities have no point; lines stop at gaps. Hollow points are preliminary. Exact values and support labels follow the chart.AgenticHard reasoningCodingHuman prefKnowledgeMultimodalLong context50100Qwen3.7-max · Reasoning · Agentic: 35.3 · SupportedQwen3.7-max · Reasoning · Hard reasoning: 44.0 · SupportedQwen3.7-max · Reasoning · Coding: 32.6 · SupportedQwen3.7-max · Reasoning · Knowledge: 34.1 · SupportedQwen3.7-max · Reasoning · Long context: 46.4 · Preliminary

Gaps are unknown, not zero. Hollow points are preliminary.

  • Agentic

    A35.3Supported
  • Hard reasoning

    A44.0Supported
  • Coding

    A32.6Supported
  • Human pref

    Unknown
  • Knowledge

    A34.1Supported
  • Multimodal

    Unknown
  • Long context

    A46.4Preliminary

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.

These are published benchmark scores. Supported effort estimates also appear on the Capability leaderboard. Results from different harnesses occupy different rows. Missing cells stay unknown; no scores are copied between effort levels.

Benchmark / sourceReasoningNon-reasoningUnspecified
AA-AnalystAgentArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings
Benchmark details

Share 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.

18.75%
Reported settings

Qwen3.7 Max; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-7-max; Mode from evaluator isReasoning metadata; effort budget not specified

Not reportedNot reported
AA-Briefcase EloArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings
Benchmark details

AA-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.

917.94 Elo
Reported settings

Qwen3.7 Max; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-7-max; Mode from evaluator isReasoning metadata; effort budget not specified

Not reportedNot reported
AA-LCR v1.1Artificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings
Benchmark details

Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis

Unit: percent. Source collected 2026-09-12.

79%
Reported settings

Qwen3.7 Max; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-7-max; Mode from evaluator isReasoning metadata; effort budget not specified

Not reportedNot reported
AutomationBench-AAArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings
Benchmark details

Share 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.

22.98%
Reported settings

Qwen3.7 Max; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-7-max; Mode from evaluator isReasoning metadata; effort budget not specified

Not reportedNot reported
CritPtArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings
Benchmark details

Benchmark 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.

13.43%
Reported settings

Qwen3.7 Max; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-7-max; Mode from evaluator isReasoning metadata; effort budget not specified

Not reportedNot reported
EnterpriseOps-Gym-AAArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings
Benchmark details

Overall 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.

45%
Reported settings

Qwen3.7 Max; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-7-max; Mode from evaluator isReasoning metadata; effort budget not specified

Not reportedNot reported
GDP.pdf: All-passArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings
Benchmark details

Share 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.

8.6%
Reported settings

Qwen3.7 Max; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-7-max; Mode from evaluator isReasoning metadata; effort budget not specified

Not reportedNot reported
GDPval-AA v2 LeaderboardArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings
Benchmark details

Elo 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.

1,189.86 Elo
Reported settings

Qwen3.7 Max; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-7-max; Mode from evaluator isReasoning metadata; effort budget not specified

Not reportedNot reported
GPQA DiamondArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings
Benchmark details

Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis

Unit: percent. Source collected 2026-09-12.

92.32%
Reported settings

Qwen3.7 Max; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-7-max; Mode from evaluator isReasoning metadata; effort budget not specified

Not reportedNot reported
Harvey LAB-AA: Criterion Pass RateArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings
Benchmark details

Share 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.

83.43%
Reported settings

Qwen3.7 Max; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-7-max; Mode from evaluator isReasoning metadata; effort budget not specified

Not reportedNot reported
Humanity's Last ExamArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings
Benchmark details

Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis

Unit: percent. Source collected 2026-09-12.

40.5%
Reported settings

Qwen3.7 Max; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-7-max; Mode from evaluator isReasoning metadata; effort budget not specified

Not reportedNot reported
IFBenchArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings
Benchmark details

Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis

Unit: percent. Source collected 2026-09-12.

80.54%
Reported settings

Qwen3.7 Max; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-7-max; Mode from evaluator isReasoning metadata; effort budget not specified

Not reportedNot reported
ITBench-AAArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings
Benchmark details

Combined public and private Site Reliability Engineering (SRE) tasks · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis

Unit: percent. Source collected 2026-09-12.

42.47%
Reported settings

Qwen3.7 Max; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-7-max; Mode from evaluator isReasoning metadata; effort budget not specified

Not reportedNot reported
AA-Omniscience IndexArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings
Benchmark details

AA-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.

13.48
Reported settings

Qwen3.7 Max; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-7-max; Mode from evaluator isReasoning metadata; effort budget not specified

Not reportedNot reported
AA-Omniscience AccuracyArtificial Analysis · 6000 questions; 1 attempt; correct-answer share; GPT-5.6 Luna medium grader
Benchmark details

AA-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.

31.13%
Reported settings

Qwen3.7 Max; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-7-max; Mode from evaluator isReasoning metadata; effort budget not specified

Not reportedNot reported
SciCodeArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings
Benchmark details

Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis

Unit: percent. Source collected 2026-09-12.

49.54%
Reported settings

Qwen3.7 Max; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-7-max; Mode from evaluator isReasoning metadata; effort budget not specified

Not reportedNot reported
𝜏²-Bench TelecomArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings
Benchmark details

Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis

Unit: percent. Source collected 2026-09-12.

94.74%
Reported settings

Qwen3.7 Max; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-7-max; Mode from evaluator isReasoning metadata; effort budget not specified

Not reportedNot reported
𝜏³-BankingArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings
Benchmark details

Benchmark developed by Sierra Research · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis

Unit: percent. Source collected 2026-09-12.

11.75%
Reported settings

Qwen3.7 Max; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-7-max; Mode from evaluator isReasoning metadata; effort budget not specified

Not reportedNot reported
Terminal-Bench HardArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings
Benchmark details

Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis

Unit: percent. Source collected 2026-09-12.

50.76%
Reported settings

Qwen3.7 Max; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-7-max; Mode from evaluator isReasoning metadata; effort budget not specified

Not reportedNot reported
Terminal-Bench v2.1Artificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings
Benchmark details

Benchmark 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.

74.53%
Reported settings

Qwen3.7 Max; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-7-max; Mode from evaluator isReasoning metadata; effort budget not specified

Not reportedNot reported
Terminal-Bench v4.0Artificial Analysis · mini-SWE-agent v2.4.6; 66 tasks; pass@1 averaged over 3 repeats; 500 steps; task timeout up to 8 hours
Benchmark details

Benchmark 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.

1.52%
Reported settings

Qwen3.7 Max; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-7-max; Mode from evaluator isReasoning metadata; effort budget not specified

Not reportedNot reported
Epoch · Chess Puzzles · v1.1.6Epoch AI · Epoch AI Inspect; task 1.1.6; scorer model_extracted_exact_match
Benchmark details

Epoch 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 reportedNot reported
19%
Reported settings

Epoch AI Inspect; task 1.1.6; scorer model_extracted_exact_match; model=qwen3.7-max; run=JfkPdo29um2NkxdhT79AK2; mean accuracy; https://epoch.ai/data/benchmarks.csv

Epoch · FrontierMath Tier 4 · v2.0.0Epoch AI · Epoch AI Inspect; task 2.0.0; scorer verification_code
Benchmark details

Epoch 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. FrontierMath was developed with OpenAI funding and unequal access to part of the question set; this result is from Epoch's evaluation.

Unit: percent. Source collected 2026-09-12.

Not reportedNot reported
34.15%
Reported settings

Epoch AI Inspect; task 2.0.0; scorer verification_code; model=qwen3.7-max; run=FHZCKbtfvpKGXU99vZFnXN; mean accuracy; https://epoch.ai/data/benchmarks.csv

Epoch · FrontierMath Tiers 1–3 · v2.0.0Epoch AI · Epoch AI Inspect; task 2.0.0; scorer verification_code
Benchmark details

Epoch 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. FrontierMath was developed with OpenAI funding and unequal access to part of the question set; this result is from Epoch's evaluation.

Unit: percent. Source collected 2026-09-12.

Not reportedNot reported
64.56%
Reported settings

Epoch AI Inspect; task 2.0.0; scorer verification_code; model=qwen3.7-max; run=RG2biwnmGybSVTVxxMdRWa; mean accuracy; https://epoch.ai/data/benchmarks.csv

Epoch · GPQA diamond · v1.0.11Epoch AI · Epoch AI Inspect; task 1.0.11; scorer choice
Benchmark details

Epoch 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 reportedNot reported
90.91%
Reported settings

Epoch AI Inspect; task 1.0.11; scorer choice; model=qwen3.7-max; run=W6mTanyjvXhasFBzHukv4S; mean accuracy; https://epoch.ai/data/benchmarks.csv

Epoch · Mystery Game Puzzles · v1.0.4 · Tool submissionEpoch AI · Epoch AI Inspect; task 1.0.4; scorer agent_submitted_next_move_scorer
Benchmark details

Epoch 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%
Reported settings

Epoch AI Inspect; task 1.0.4; scorer agent_submitted_next_move_scorer; model=qwen3.7-max_none; run=ENh7ZPQj7ihBePjsC8a7HV; mean accuracy; https://epoch.ai/data/benchmarks.csv

32%
Reported settings

Epoch AI Inspect; task 1.0.4; scorer agent_submitted_next_move_scorer; model=qwen3.7-max; run=f7dotY9NheKNKK2zz6bfKZ; mean accuracy; https://epoch.ai/data/benchmarks.csv

Epoch · OTIS Mock AIME 2024-2025 · v1.1.6Epoch AI · Epoch AI Inspect; task 1.1.6; scorer model_extracted_exact_match
Benchmark details

Epoch 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 reportedNot reported
95.56%
Reported settings

Epoch AI Inspect; task 1.1.6; scorer model_extracted_exact_match; model=qwen3.7-max; run=D3YDUZSfEUDsS4frLbEKDu; mean accuracy; https://epoch.ai/data/benchmarks.csv

Epoch · SimpleQA Verified · v1.2.0Epoch AI · Epoch AI Inspect; task 1.2.0; scorer simpleqa_scorer
Benchmark details

Epoch 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 reportedNot reported
55.77%
Reported settings

Epoch AI Inspect; task 1.2.0; scorer simpleqa_scorer; model=qwen3.7-max; run=DMjUrG6eZEqwcQ4SqUoViu; mean accuracy; https://epoch.ai/data/benchmarks.csv

Vals AI · Finance Agent v2Vals AI · Vals FAB v2 shared six-tool harness; two-hour task limit
Benchmark details

Overall 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 reportedNot reported
47.78%
Reported settings

{"checkpoint":"qwen3.7-max","evaluatorModel":"alibaba/qwen3.7-max","sourceUpdatedOn":"2026-09-10","reasoning_effort":null,"compute_effort":null,"reasoning":null,"temperature":0.7,"top_p":null,"max_output_tokens":65536,"verbosity":null,"provider":"Alibaba","harness":null}

Vals AI · Code Migration v1Vals AI · Vals Code Migration shared agent harness
Benchmark details

Hidden 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 reportedNot reported
13.07%
Reported settings

{"checkpoint":"qwen3.7-max","evaluatorModel":"alibaba/qwen3.7-max","sourceUpdatedOn":"2026-09-10","reasoning_effort":null,"compute_effort":null,"reasoning":null,"temperature":0.7,"top_p":null,"max_output_tokens":65536,"verbosity":null,"provider":"Alibaba","harness":null}

Vals AI · Legal Research Bench v1Vals AI · Vals Legal Research shared five-tool harness; three-hour task limit
Benchmark details

All-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 reportedNot reported
Vals AI · Excel Modeling Benchmark v1Vals AI · Vals EMB shared workbook agent harness; 3.5-hour task limit
Benchmark details

Mean 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 reportedNot reported
57.04%
Reported settings

{"checkpoint":"qwen3.7-max","evaluatorModel":"alibaba/qwen3.7-max","sourceUpdatedOn":"2026-09-10","reasoning_effort":null,"compute_effort":null,"reasoning":null,"temperature":0.7,"top_p":null,"max_output_tokens":65536,"verbosity":null,"provider":"Alibaba","harness":null}

Vals AI · MMLU-Pro v1Vals AI · Vals MMLU-Pro five-shot chain-of-thought; regex answer grading
Benchmark details

Mean 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 reportedNot reported
89.31%
Reported settings

{"checkpoint":"qwen3.7-max","evaluatorModel":"alibaba/qwen3.7-max","sourceUpdatedOn":"2026-09-01","reasoning_effort":null,"compute_effort":null,"reasoning":null,"temperature":0.7,"top_p":null,"max_output_tokens":65536,"verbosity":null,"provider":"Alibaba","harness":null}

Vals AI · Terminal-Bench 2.1Vals AI · Vals Terminus 2 harness; pass@1 on 89 tasks
Benchmark details

Overall 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 reportedNot reported
61.05%
Reported settings

{"checkpoint":"qwen3.7-max","evaluatorModel":"alibaba/qwen3.7-max","sourceUpdatedOn":"2026-09-10","reasoning_effort":null,"compute_effort":null,"reasoning":null,"temperature":0.7,"top_p":null,"max_output_tokens":65536,"verbosity":null,"provider":"Alibaba","harness":null}

Vals AI · Vibe Code Bench v1.1Vals AI · Vals modified OpenHands harness; five hours or 1,000 turns per app
Benchmark details

Mean 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 reportedNot reported
47.67%
Reported settings

{"checkpoint":"qwen3.7-max","evaluatorModel":"alibaba/qwen3.7-max","sourceUpdatedOn":"2026-09-10","reasoning_effort":null,"compute_effort":null,"reasoning":null,"temperature":0.7,"top_p":null,"max_output_tokens":65536,"verbosity":null,"provider":"Alibaba","harness":"OpenHands"}

Vals AI · Harvey Legal Agent Benchmark v1Vals AI · Vals Harvey held-out legal file-work protocol; internet disabled
Benchmark details

Mean 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 reportedNot reported
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