RankingEffort benchmarks

Qwen3-max effort benchmarks

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

Model

Qwen3-max

25 measured results · 1 reported effort labels · 13 benchmark/harness combinations. Model evidence and sources →

Capability score evidence

Qwen3-max · Non-reasoning: 8.5 overall comparison score. Needs 3 benchmark families

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.

This configuration did not qualify for the dated stability audit.

What evidence is missing from the fit?

Across all collected settings for this model: 25 observations, 3 contributing, 0 matched without graph weight and 22 excluded. Counts do not establish rank eligibility.

20 · Conflicting values for this configuration in the same evaluation
2 · Benchmark family or source protocol has not been reviewed

Inspect every observation and exclusion →

Capability profile

One configuration, seven capabilities

Comparison score · 0–100

AQwen3-max · Non-reasoning0 of 7 capabilities supported

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

Agentic
Unknown
Hard reasoning
A9.6Preliminary
Coding
Unknown
Human pref
Unknown
Knowledge
A10.3Preliminary
Multimodal
Unknown
Long context
Unknown

Each profile belongs to the named configuration. Capability scores use a shared panel for all axes, distinct from the overall ranking panel; they are not accuracy percentages or direct head-to-head wins.

Compare this configuration →Explore the model evidence profile →

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	Non-reasoning
AIME 2025Artificial 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.	80.67% Reported settings Qwen3 Max; Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/qwen3-max; Mode from evaluator isReasoning metadata; effort budget not specified 75% Reported settings Qwen3 Max (Preview); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/qwen3-max-preview; Mode from evaluator isReasoning metadata; effort budget not specified
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.	50% Reported settings Qwen3 Max; Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/qwen3-max; Mode from evaluator isReasoning metadata; effort budget not specified 43% Reported settings Qwen3 Max (Preview); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/qwen3-max-preview; Mode from evaluator isReasoning metadata; effort budget not specified
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.	0.86% Reported settings Qwen3 Max (Preview); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/qwen3-max-preview; Mode from evaluator isReasoning metadata; effort budget not specified 0% Reported settings Qwen3 Max; Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/qwen3-max; Mode from evaluator isReasoning metadata; effort budget not specified
Global-MMLU-LiteArtificial 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.	83.29% Reported settings Qwen3 Max; Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/qwen3-max; Mode from evaluator isReasoning metadata; effort budget not specified
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.	76.36% Reported settings Qwen3 Max (Preview); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/qwen3-max-preview; Mode from evaluator isReasoning metadata; effort budget not specified 76.36% Reported settings Qwen3 Max; Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/qwen3-max; Mode from evaluator isReasoning metadata; effort budget not specified
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.	10.15% Reported settings Qwen3 Max (Preview); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/qwen3-max-preview; Mode from evaluator isReasoning metadata; effort budget not specified 11.91% Reported settings Qwen3 Max; Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/qwen3-max; Mode from evaluator isReasoning metadata; effort budget not specified
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.	48.03% Reported settings Qwen3 Max (Preview); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/qwen3-max-preview; Mode from evaluator isReasoning metadata; effort budget not specified 44.15% Reported settings Qwen3 Max; Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/qwen3-max; Mode from evaluator isReasoning metadata; effort budget not specified
LiveCodeBenchArtificial 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.	76.72% Reported settings Qwen3 Max; Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/qwen3-max; Mode from evaluator isReasoning metadata; effort budget not specified 65.08% Reported settings Qwen3 Max (Preview); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/qwen3-max-preview; Mode from evaluator isReasoning metadata; effort budget not specified
MMLU-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 2026-09-12.	83.83% Reported settings Qwen3 Max (Preview); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/qwen3-max-preview; Mode from evaluator isReasoning metadata; effort budget not specified 84.12% Reported settings Qwen3 Max; Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/qwen3-max; Mode from evaluator isReasoning metadata; effort budget not specified
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.	-42.78 Reported settings Qwen3 Max (Preview); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/qwen3-max-preview; Mode from evaluator isReasoning metadata; effort budget not specified -43.55 Reported settings Qwen3 Max; Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/qwen3-max; Mode from evaluator isReasoning metadata; effort budget not specified
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.	24.2% Reported settings Qwen3 Max (Preview); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/qwen3-max-preview; Mode from evaluator isReasoning metadata; effort budget not specified 24.42% Reported settings Qwen3 Max; Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/qwen3-max; Mode from evaluator isReasoning metadata; effort budget not specified
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.	32.75% Reported settings Qwen3 Max (Preview); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/qwen3-max-preview; Mode from evaluator isReasoning metadata; effort budget not specified 74.27% Reported settings Qwen3 Max; Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/qwen3-max; Mode from evaluator isReasoning metadata; effort budget not specified
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.	20.45% Reported settings Qwen3 Max; Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/qwen3-max; Mode from evaluator isReasoning metadata; effort budget not specified 19.7% Reported settings Qwen3 Max (Preview); Reported effort: non-reasoning; Model source: https://artificialanalysis.ai/models/qwen3-max-preview; Mode from evaluator isReasoning metadata; effort budget not specified

What these comparisons mean

Each source reports its own effort labels. Matching labels do not establish equal compute budgets or identical fallback behavior. Open Reported settings to inspect the exact model name, agent and task coverage. Multiple results at one level remain visible rather than selecting the best. Source-reported None or Non-reasoning labels are not treated as evidence that an API supports those settings.

These measurements use their own dated source collection. The leaderboard fits identified configurations jointly; it contains no pooled model ratings. Explicit thinking budgets are separate configurations. Read the methodology.

Download all effort benchmark results · 7,424 results across 240 models · Collected 2026-09-12

Qwen3-max effort benchmarks

Qwen3-max

Capability score evidence

One configuration, seven capabilities

Agentic

Hard reasoning

Coding

Human pref

Knowledge

Multimodal

Long context