RankingEffort benchmarks

Qwen3.7-max · Reasoning

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39 measured results · 4 effort settings · 38 benchmark/harness combinations

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Choose a second model and its effort to see both profiles and benchmark differences below.

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Capability profile

One configuration, seven capabilities

Comparison score · 0–100

AQwen3.7-max · Reasoning3 of 7 capabilities supported

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

Agentic
A33.4Supported
Hard reasoning
A43.5Supported
Coding
A37.0Preliminary
Human pref
Unknown
Knowledge
A30.2Supported
Multimodal
Unknown
Long context
A45.0Preliminary

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.

Capability score evidence

Qwen3.7-max · Reasoning: 25.4 overall comparison score. Meets the overall evidence requirements.

5 areas measured. The available task mix affects this estimate; missing areas remain unknown.

Which sources carry the weight?

Artificial Analysis · 100.0% direct comparison weight · independent of the model provider

Which benchmark families carry the weight?

IFBench · 7.8% direct comparison weight
Humanity’s Last Exam · 7.6% direct comparison weight
GPQA · 7.6% direct comparison weight
Critpt · 7.6% direct comparison weight
omniscience · 7.6% direct comparison weight
Other families (10) · 61.9% direct comparison weight

These shares describe direct comparison weight, not fractions of the final score or confidence. Source balancing does not give every family equal weight or remove correlations between overlapping sources.

How sensitive is this score?

The audit removes one source at a time and refits against the same overall reference panel. These published results use the matching dataset audited 2026-10-23.

Both ranks use the same surviving configurations for each removal. The cohort starts with 444 configurations supported in the original audit, including separate effort settings. These are diagnostic positions, not the default leaderboard ranks. Eligibility is not rechecked after removal.

What changes when a source is removed?
Removed source	Rank before → after	Rank movement	Cohort remaining / lost support	Score after (change)
Artificial Analysis	Comparison support lost; no rank		203 remaining / 241 lost	Unavailable
ARC Prize	123 → 126	Down 3	444 remaining / 0 lost	30.3 (+4.9 points)
Datacurve	123 → 125	Down 2	444 remaining / 0 lost	21.4 (-4.0 points)
LiveCodeBench	123 → 123	No movement	444 remaining / 0 lost	25.3 (-0.1 points)
Scale	123 → 122	Up 1	444 remaining / 0 lost	27.6 (+2.3 points)
Terminal-Bench	123 → 121	Up 2	444 remaining / 0 lost	25.4 (-0.0 points)
Cognition	123 → 125	Down 2	444 remaining / 0 lost	24.4 (-1.0 points)
LiveBench	122 → 120	Up 2	443 remaining / 1 lost	26.0 (+0.6 points)
SWE-rebench	123 → 123	No movement	444 remaining / 0 lost	25.8 (+0.4 points)
Epoch AI	121 → 121	No movement	431 remaining / 13 lost	25.7 (+0.4 points)
Vals AI	123 → 123	No movement	443 remaining / 1 lost	24.5 (-0.8 points)
Provider reports · Anthropic	123 → 123	No movement	444 remaining / 0 lost	25.4 (-0.0 points)
Provider reports · Moonshot AI	123 → 124	Down 1	444 remaining / 0 lost	24.8 (-0.6 points)
Provider reports · Meta	123 → 123	No movement	444 remaining / 0 lost	25.3 (-0.0 points)
Provider reports · Mistral	123 → 123	No movement	444 remaining / 0 lost	25.4 (+0.0 points)
Provider reports · OpenAI	123 → 123	No movement	444 remaining / 0 lost	25.5 (+0.1 points)
All provider reports	123 → 124	Down 1	444 remaining / 0 lost	24.9 (-0.5 points)

Lost support means a configuration no longer has a comparison path to the complete reference panel. Its rank is unavailable. A surviving path alone does not establish leaderboard eligibility.

Overlapping sources may remain correlated even with source balancing. Leave-one-source-out movement is a sensitivity diagnostic, not a spread of source-specific ranks or a confidence measure. Scoring methodology · Dated configuration audit

Every benchmark family

Removed evidence	Recomputed score	Change
arc-agi	29.5	+4.2
deepswe	21.4	-4.0
gdp-pdf	27.4	+2.0
itbench	23.7	-1.7
enterprise-ops	23.8	-1.6
mmmu-pro	26.7	+1.3
gpqa	24.1	-1.3
ifbench	24.2	-1.2
omniscience	26.6	+1.2
tau-bench	26.5	+1.2
frontiercode	24.4	-1.0
epoch-game-puzzles	24.5	-0.8
simpleqa	26.2	+0.8
analyst-agent	26.2	+0.8
briefcase	26.1	+0.7
aa-lcr	24.8	-0.6
automationbench	25.9	+0.5
hle	25.9	+0.5
mmlu-pro	25.8	+0.4
swe-rebench	25.8	+0.4
critpt	25.0	-0.4
multi-swe-bench	25.0	-0.4
livebench-instructions	25.7	+0.4
apex-agents	25.7	+0.3
terminal-bench-science	25.7	+0.3
livebench-language	25.7	+0.3
arc-agi-3	25.1	-0.2
harvey	25.1	-0.2
swe-atlas-qna	25.2	-0.2
enigma-eval	25.2	-0.2
livebench-coding	25.2	-0.2
vibe-code	25.3	-0.1
livebench-reasoning	25.3	-0.1
swe-atlas-test-writing	25.3	-0.1
aime	25.3	-0.1
terminal-bench	25.3	-0.1
livecodebench	25.3	-0.1
vals-legal-research	25.3	-0.1
vals-finance-agent	25.3	-0.1
vals-code-migration	25.3	-0.1
gdpval	25.4	+0.1
gmmlu	25.4	+0.1
vals-tax-agent	25.3	-0.0
math500	25.4	+0.0
vals-excel-modeling	25.4	-0.0
frontiermath	25.4	+0.0
swe-atlas-refactoring	25.4	-0.0
livebench-math	25.4	+0.0
swe-bench-pro	25.4	+0.0
livebench-data	25.4	-0.0

What evidence is missing from the fit?

Across all collected settings for this model: 73 observations, 19 contributing, 0 matched without graph weight and 54 excluded. Counts do not establish rank eligibility.

1 · Benchmark family or source protocol has not been reviewed
1 · Original SciCode grading defects are under review; retained as supporting evidence, excluded from aggregate and capability scores. Corrected SciCode-Verified requires a separate protocol review. Sources: https://arxiv.org/abs/2608.04975 and https://artificialanalysis.ai/evaluations/scicode
17 · Effort is not identified
1 · Evaluator has not been reviewed for independent admission
2 · 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
21 · Supporting evidence outside the reviewed capability core
1 · The Qwen card cites an external leaderboard or release report for this comparator; it is not a new Qwen evaluation. Historical provider claim; secondary and superseded for current FrontierSWE comparisons by the independent Proximal FrontierSWE v2 mean@5 board at https://www.frontierswe.com/. Version-unspecified claims are not v2 results. Excluded from weighted Overall.
1 · Narrow specialist biological, medical or security evaluation; preserved as raw evidence outside general capability scoring.

Inspect every observation and exclusion →

Benchmark results

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 / source	High	Reasoning	Non-reasoning	Unspecified
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 2026-10-18.	Not reported	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 reported	Not reported
AA-Briefcase EloArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details AA-Briefcase v1.1 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 2026-10-18.	Not reported	916.31 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 reported	Not 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 2026-10-18.	Not reported	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 reported	Not 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 2026-10-18.	Not reported	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 reported	Not 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. CritPt is under review by its authors following external feedback · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-18.	Not reported	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 reported	Not 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 2026-10-18.	Not reported	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 reported	Not reported
GDP.pdf: All-pass RateArtificial 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 2026-10-18.	Not reported	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 reported	Not reported
GDPval-AA v2.1 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 DeepSeek V4.1 Flash (max) at 1600 · Higher is better · Evaluation results measured independently by Artificial Analysis Unit: elo. Source collected 2026-10-18.	Not reported	1,127.65 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 reported	Not 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 2026-10-18.	Not reported	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 reported	Not 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 2026-10-18.	Not reported	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 reported	Not 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 2026-10-18.	Not reported	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 reported	Not 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 2026-10-18.	Not reported	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 reported	Not 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 2026-10-18.	Not reported	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 reported	Not 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 2026-10-18.	Not reported	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 reported	Not reported
SciCodeArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details Benchmark curated by scientists across 16 disciplines. SciCode is under review following an independent audit of the dataset · Independently benchmarked by Artificial Analysis · Evaluation results measured independently by Artificial Analysis Unit: percent. Source collected 2026-10-18.	Not reported	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 reported	Not 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 2026-10-18.	Not reported	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 reported	Not 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 2026-10-18.	Not reported	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 reported	Not 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 2026-10-18.	Not reported	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 reported	Not 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 2026-10-18.	Not reported	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 reported	Not 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 2026-10-18.	Not reported	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 reported	Not reported
Epoch · Chess Puzzles · v2.0.0Epoch AI · Epoch AI Inspect; task 2.0.0; scorer exact 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 2026-10-18.	Not reported	Not reported	Not reported	26% Reported settings Epoch AI Inspect; task 2.0.0; scorer exact; model=qwen3.7-max; run=cbQnfsMSA3aQaBtjm3aFx2; 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 2026-10-18.	Not reported	Not reported	Not 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 2026-10-18.	Not reported	Not reported	Not 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 2026-10-18.	Not reported	Not reported	Not 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 2026-10-18.	Not reported	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

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 · 8,916 results across 259 models · Collected 2026-10-18

Qwen3.7-max · Reasoning

Compare with

One configuration, seven capabilities

Agentic

Hard reasoning

Coding

Human pref

Knowledge

Multimodal

Long context

Capability score evidence

Benchmark results