RankingEffort benchmarks

Qwen3.6-plus · Reasoning

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30 measured results · 4 effort settings · 29 benchmark/harness combinations

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Capability profile

One configuration, seven capabilities

Comparison score · 0–100

AQwen3.6-plus · Reasoning3 of 7 capabilities supported

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

Agentic
A28.6Supported
Hard reasoning
A25.7Supported
Coding
A30.2Preliminary
Human pref
Unknown
Knowledge
A21.8Supported
Multimodal
A31.9Preliminary
Long context
A42.1Preliminary

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

Qwen3.6-plus · Reasoning: 17.8 overall comparison score. Meets the overall evidence requirements.

6 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 · 10.7% direct comparison weight
Humanity’s Last Exam · 10.5% direct comparison weight
GPQA · 10.5% direct comparison weight
Critpt · 10.4% direct comparison weight
omniscience · 10.3% direct comparison weight
Other families (5) · 47.6% 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	151 → 149	Up 2	444 remaining / 0 lost	21.9 (+4.2 points)
Datacurve	151 → 152	Down 1	444 remaining / 0 lost	14.6 (-3.2 points)
LiveCodeBench	151 → 151	No movement	444 remaining / 0 lost	17.7 (-0.1 points)
Scale	151 → 152	Down 1	444 remaining / 0 lost	19.8 (+2.1 points)
Terminal-Bench	151 → 152	Down 1	444 remaining / 0 lost	17.7 (-0.1 points)
Cognition	151 → 153	Down 2	444 remaining / 0 lost	17.1 (-0.7 points)
LiveBench	150 → 149	Up 1	443 remaining / 1 lost	18.2 (+0.5 points)
SWE-rebench	151 → 150	Up 1	444 remaining / 0 lost	18.1 (+0.4 points)
Epoch AI	147 → 147	No movement	431 remaining / 13 lost	18.0 (+0.2 points)
Vals AI	151 → 149	Up 2	443 remaining / 1 lost	17.1 (-0.7 points)
Provider reports · Anthropic	151 → 151	No movement	444 remaining / 0 lost	17.8 (-0.0 points)
Provider reports · Moonshot AI	151 → 151	No movement	444 remaining / 0 lost	17.3 (-0.4 points)
Provider reports · Meta	151 → 151	No movement	444 remaining / 0 lost	17.8 (-0.0 points)
Provider reports · Mistral	151 → 151	No movement	444 remaining / 0 lost	17.8 (+0.0 points)
Provider reports · OpenAI	151 → 151	No movement	444 remaining / 0 lost	17.9 (+0.1 points)
All provider reports	151 → 152	Down 1	444 remaining / 0 lost	17.4 (-0.4 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	21.3	+3.5
deepswe	14.6	-3.2
hle	19.3	+1.5
gdpval	18.9	+1.1
omniscience	18.8	+1.0
aa-lcr	16.8	-1.0
tau-bench	17.0	-0.8
gpqa	17.0	-0.8
epoch-game-puzzles	17.0	-0.8
ifbench	17.1	-0.7
frontiercode	17.1	-0.7
simpleqa	18.5	+0.7
critpt	18.4	+0.6
mmmu-pro	18.2	+0.4
mmlu-pro	18.2	+0.4
swe-rebench	18.1	+0.4
livebench-instructions	18.1	+0.3
multi-swe-bench	17.5	-0.3
gdp-pdf	18.0	+0.2
terminal-bench	17.5	-0.2
arc-agi-3	17.6	-0.2
automationbench	17.6	-0.2
livebench-language	18.0	+0.2
apex-agents	18.0	+0.2
briefcase	17.6	-0.2
terminal-bench-science	18.0	+0.2
harvey	17.6	-0.2
swe-atlas-qna	17.6	-0.2
enigma-eval	17.6	-0.2
livebench-coding	17.6	-0.2
gmmlu	17.9	+0.1
itbench	17.7	-0.1
analyst-agent	17.9	+0.1
livebench-reasoning	17.7	-0.1
vibe-code	17.7	-0.1
swe-atlas-test-writing	17.7	-0.1
vals-finance-agent	17.7	-0.1
vals-legal-research	17.7	-0.1
vals-code-migration	17.7	-0.1
vals-tax-agent	17.7	-0.0
enterprise-ops	17.7	-0.0
livecodebench	17.7	-0.0
math500	17.8	+0.0
frontiermath	17.8	+0.0
vals-excel-modeling	17.8	-0.0
livebench-math	17.8	+0.0
swe-atlas-refactoring	17.8	-0.0
livebench-data	17.8	-0.0
aime	17.8	+0.0
swe-bench-pro	17.8	+0.0

What evidence is missing from the fit?

Across all collected settings for this model: 32 observations, 14 contributing, 0 matched without graph weight and 18 excluded. Counts do not establish rank eligibility.

1 · Benchmark family or source protocol has not been reviewed
14 · Effort is not identified
1 · Evaluator has not been reviewed for independent admission
1 · Supporting evidence outside the reviewed capability core
1 · No reviewed effort for this catalog observation; any separately collected effort measurement is counted separately

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-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	78.33% Reported settings Qwen3.6 Plus; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-6-plus; 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	2.86% Reported settings Qwen3.6 Plus; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-6-plus; 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	990.26 Elo Reported settings Qwen3.6 Plus; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-6-plus; 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	88.18% Reported settings Qwen3.6 Plus; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-6-plus; 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	27.85% Reported settings Qwen3.6 Plus; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-6-plus; 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	75.17% Reported settings Qwen3.6 Plus; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-6-plus; Mode from evaluator isReasoning metadata; effort budget not specified	Not reported	Not reported
MMMU-ProArtificial 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	77.98% Reported settings Qwen3.6 Plus; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-6-plus; 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	0.88 Reported settings Qwen3.6 Plus; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-6-plus; 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	26.38% Reported settings Qwen3.6 Plus; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-6-plus; 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	97.66% Reported settings Qwen3.6 Plus; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-6-plus; 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	20.82% Reported settings Qwen3.6 Plus; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-6-plus; 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	43.94% Reported settings Qwen3.6 Plus; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-6-plus; 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	61.42% Reported settings Qwen3.6 Plus; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-6-plus; 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	14% Reported settings Epoch AI Inspect; task 2.0.0; scorer exact; model=qwen3.6-plus; run=SP9UFPzxVnsbzs2kExP2bh; 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	32.28% Reported settings Epoch AI Inspect; task 2.0.0; scorer verification_code; model=qwen3.6-plus_none; run=Z4xfwTke5pR6RrY952bttA; mean accuracy; https://epoch.ai/data/benchmarks.csv	38.25% Reported settings Epoch AI Inspect; task 2.0.0; scorer verification_code; model=qwen3.6-plus; run=jbyVWnEvvFVNNc8AEF6WcQ; 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	88.38% Reported settings Epoch AI Inspect; task 1.0.11; scorer choice; model=qwen3.6-plus; run=f6ZdMtRpdfskGbrBCzrKSn; 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	12% Reported settings Epoch AI Inspect; task 1.0.4; scorer agent_submitted_next_move_scorer; model=qwen3.6-plus_none; run=jGgkDRHbodcaTzQ3Mp6SxS; mean accuracy; https://epoch.ai/data/benchmarks.csv	Not reported
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 2026-10-18.	Not reported	Not reported	Not reported	93.33% Reported settings Epoch AI Inspect; task 1.1.6; scorer model_extracted_exact_match; model=qwen3.6-plus; run=jYiGAFfUQKJuRStPzU3PX3; 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 2026-10-18.	Not reported	Not reported	Not reported	44.14% Reported settings Epoch AI Inspect; task 1.2.0; scorer simpleqa_scorer; model=qwen3.6-plus; run=4LWNorP8Fy8V8doxirNFcH; 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 2026-10-18.	Not reported	Not reported	Not reported	40.85% Reported settings {"checkpoint":"qwen3.6-plus","evaluatorModel":"alibaba/qwen3.6-plus","sourceUpdatedOn":"2026-10-16","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 2026-10-18.	Not reported	Not reported	Not reported	11.1% Reported settings {"checkpoint":"qwen3.6-plus","evaluatorModel":"alibaba/qwen3.6-plus","sourceUpdatedOn":"2026-10-16","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 2026-10-18.	Not reported	Not reported	Not reported	14.9% Reported settings {"checkpoint":"qwen3.6-plus","evaluatorModel":"alibaba/qwen3.6-plus","sourceUpdatedOn":"2026-10-16","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 · 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 2026-10-18.	Not reported	Not reported	Not reported	32.87% Reported settings {"checkpoint":"qwen3.6-plus","evaluatorModel":"alibaba/qwen3.6-plus","sourceUpdatedOn":"2026-10-16","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 2026-10-18.	Not reported	Not reported	Not reported	87.67% Reported settings {"checkpoint":"qwen3.6-plus","evaluatorModel":"alibaba/qwen3.6-plus","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 2026-10-18.	Not reported	Not reported	Not reported	53.18% Reported settings {"checkpoint":"qwen3.6-plus","evaluatorModel":"alibaba/qwen3.6-plus","sourceUpdatedOn":"2026-09-28","reasoning_effort":null,"compute_effort":null,"reasoning":null,"temperature":0.7,"top_p":null,"max_output_tokens":65536,"verbosity":null,"provider":"Alibaba","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 · 8,916 results across 259 models · Collected 2026-10-18

Qwen3.6-plus · Reasoning

Compare with

One configuration, seven capabilities

Agentic

Hard reasoning

Coding

Human pref

Knowledge

Multimodal

Long context

Capability score evidence

Benchmark results