RankingEffort benchmarks

Claude Sonnet 4.6

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106 measured results · 7 effort settings · 68 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

AClaude Sonnet 4.6 · Max4 of 7 capabilities supported

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

Agentic
A40.8Supported
Hard reasoning
A28.2Supported
Coding
A30.6Supported
Human pref
Unknown
Knowledge
A17.6Supported
Multimodal
A18.6Preliminary
Long context
A63.3Preliminary

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

Claude Sonnet 4.6 · Max: 19.0 overall comparison score. Meets the overall evidence requirements.

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

Shared-result disagreement. This aggregate order conflicts with matched benchmark results against 1 other configurations. Different test coverage and opponents affect the fit. Inspect published results before treating the rank as conclusive.

Which sources carry the weight?

Cognition · 21.9% direct comparison weight · independent of the model provider
Artificial Analysis · 21.8% direct comparison weight · independent of the model provider
ARC Prize · 21.6% direct comparison weight · independent of the model provider
Vals AI · 19.3% direct comparison weight · independent of the model provider
Epoch AI · 15.4% direct comparison weight · independent of the model provider

Which benchmark families carry the weight?

FrontierCode · 21.9% direct comparison weight
ARC-AGI · 21.6% direct comparison weight
GPQA · 6.3% direct comparison weight
simpleqa · 5.4% direct comparison weight
Aime · 5.0% direct comparison weight
Other families (24) · 39.8% 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	122 → 121	Up 1	203 remaining / 241 lost	17.3 (-1.6 points)
ARC Prize	143 → 165	Down 22	444 remaining / 0 lost	17.3 (-1.7 points)
Datacurve	143 → 142	Up 1	444 remaining / 0 lost	15.7 (-3.3 points)
LiveCodeBench	143 → 141	Up 2	444 remaining / 0 lost	19.0 (+0.0 points)
Scale	143 → 143	No movement	444 remaining / 0 lost	20.9 (+1.9 points)
Terminal-Bench	143 → 142	Up 1	444 remaining / 0 lost	18.9 (-0.0 points)
Cognition	143 → 129	Up 14	444 remaining / 0 lost	22.8 (+3.8 points)
LiveBench	142 → 141	Up 1	443 remaining / 1 lost	19.6 (+0.6 points)
SWE-rebench	143 → 145	Down 2	444 remaining / 0 lost	18.8 (-0.2 points)
Epoch AI	141 → 127	Up 14	431 remaining / 13 lost	24.6 (+5.6 points)
Vals AI	143 → 160	Down 17	443 remaining / 1 lost	14.9 (-4.1 points)
Provider reports · Anthropic	143 → 143	No movement	444 remaining / 0 lost	19.0 (-0.0 points)
Provider reports · Moonshot AI	143 → 142	Up 1	444 remaining / 0 lost	18.6 (-0.4 points)
Provider reports · Meta	143 → 143	No movement	444 remaining / 0 lost	19.0 (+0.0 points)
Provider reports · Mistral	143 → 143	No movement	444 remaining / 0 lost	19.0 (+0.0 points)
Provider reports · OpenAI	143 → 143	No movement	444 remaining / 0 lost	19.1 (+0.1 points)
All provider reports	143 → 142	Up 1	444 remaining / 0 lost	18.7 (-0.3 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
frontiercode	22.8	+3.8
deepswe	15.7	-3.3
arc-agi	16.7	-2.2
mmmu-pro	20.2	+1.2
hle	19.9	+1.0
simpleqa	19.9	+0.9
gpqa	19.5	+0.6
vals-tax-agent	18.4	-0.5
epoch-game-puzzles	18.5	-0.5
mmlu-pro	19.5	+0.5
terminal-bench	19.5	+0.5
livebench-instructions	19.3	+0.3
aa-lcr	18.7	-0.3
multi-swe-bench	18.7	-0.3
vals-code-migration	18.7	-0.3
harvey	18.7	-0.3
vibe-code	19.2	+0.3
aime	18.7	-0.3
frontiermath	18.7	-0.2
livebench-language	19.2	+0.2
vals-legal-research	18.8	-0.2
livebench-coding	18.8	-0.2
swe-atlas-qna	18.8	-0.2
itbench	18.8	-0.2
arc-agi-3	18.8	-0.2
swe-rebench	18.8	-0.2
ifbench	19.1	+0.2
briefcase	18.8	-0.2
enigma-eval	18.8	-0.1
critpt	19.1	+0.1
omniscience	18.8	-0.1
livebench-reasoning	18.9	-0.1
gdpval	18.9	-0.1
swe-atlas-test-writing	18.9	-0.1
analyst-agent	19.0	+0.1
vals-finance-agent	19.0	+0.0
apex-agents	19.0	+0.0
terminal-bench-science	19.0	+0.0
automationbench	19.0	+0.0
livebench-data	19.0	+0.0
gdp-pdf	18.9	-0.0
vals-excel-modeling	18.9	-0.0
tau-bench	18.9	-0.0
livebench-math	19.0	+0.0
gmmlu	19.0	+0.0
swe-atlas-refactoring	19.0	-0.0
math500	19.0	+0.0
livecodebench	19.0	+0.0
swe-bench-pro	19.0	+0.0
enterprise-ops	19.0	-0.0

What evidence is missing from the fit?

Across all collected settings for this model: 151 observations, 75 contributing, 0 matched without graph weight and 76 excluded. Counts do not establish rank eligibility.

20 · Conflicting values for this configuration in the same evaluation
6 · 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
2 · Fewer than two distinct model identities remain in this evaluation
2 · Effort is not identified
17 · No reviewed effort for this catalog observation; any separately collected effort measurement is counted separately
1 · Microsoft report Table 11 and section 4.1: MAI Terminal-Bench removes timeouts and uses a minimal ReAct harness; comparator values are cited from other model releases. A common evaluation protocol is not established.
4 · No matched, identified effort unit; duplicates and unnamed comparators do not add evidence
21 · Supporting evidence outside the reviewed capability core
2 · 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	Low	Medium	High	Max	Thinking 32K	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	Not reported	Not reported	20% Reported settings Claude Sonnet 4.6 (Max); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6-adaptive	Not reported	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	Not reported	Not reported	1,062.96 Elo Reported settings Claude Sonnet 4.6 (Max); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6-adaptive	Not reported	Not reported	Not reported
APEX-Agents-AAArtificial 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	Not reported	Not reported	28.02% Reported settings Claude Sonnet 4.6 (Max); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6-adaptive	Not reported	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	Not reported	Not reported	80% Reported settings Claude Sonnet 4.6 (Max); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6-adaptive	Not reported	69.33% Reported settings Claude Sonnet 4.6 (Non-reasoning, Low); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6-non-reasoning-low-effort 68.33% Reported settings Claude Sonnet 4.6 (Non-reasoning, High); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6	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	Not reported	Not reported	20.1% Reported settings Claude Sonnet 4.6 (Max); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6-adaptive	Not reported	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	Not reported	Not reported	3.14% Reported settings Claude Sonnet 4.6 (Max); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6-adaptive	Not reported	0.86% Reported settings Claude Sonnet 4.6 (Non-reasoning, High); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6 0.86% Reported settings Claude Sonnet 4.6 (Non-reasoning, Low); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6-non-reasoning-low-effort	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	Not reported	Not reported	15.8% Reported settings Claude Sonnet 4.6 (Max); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6-adaptive	Not reported	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	Not reported	Not reported	1,232 Elo Reported settings Claude Sonnet 4.6 (Max); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6-adaptive	Not reported	Not reported	Not reported
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 2026-10-18.	Not reported	Not reported	Not reported	90.48% Reported settings Claude Sonnet 4.6 (Max); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6-adaptive	Not reported	88.24% Reported settings Claude Sonnet 4.6 (Non-reasoning, Low); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6-non-reasoning-low-effort 89.24% Reported settings Claude Sonnet 4.6 (Non-reasoning, High); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6	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	Not reported	Not reported	87.47% Reported settings Claude Sonnet 4.6 (Max); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6-adaptive	Not reported	79.9% Reported settings Claude Sonnet 4.6 (Non-reasoning, High); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6 79.7% Reported settings Claude Sonnet 4.6 (Non-reasoning, Low); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6-non-reasoning-low-effort	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	Not reported	Not reported	33.6% Reported settings Claude Sonnet 4.6 (Max); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6-adaptive	Not reported	13.35% Reported settings Claude Sonnet 4.6 (Non-reasoning, High); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6 11.21% Reported settings Claude Sonnet 4.6 (Non-reasoning, Low); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6-non-reasoning-low-effort	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	Not reported	Not reported	56.6% Reported settings Claude Sonnet 4.6 (Max); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6-adaptive	Not reported	41.16% Reported settings Claude Sonnet 4.6 (Non-reasoning, High); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6 42.38% Reported settings Claude Sonnet 4.6 (Non-reasoning, Low); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6-non-reasoning-low-effort	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	Not reported	Not reported	39.8% Reported settings Claude Sonnet 4.6 (Max); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6-adaptive	Not reported	Not reported	Not reported
MLCR-AAArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details Share 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 2026-10-18.	Not reported	Not reported	Not reported	24.44% Reported settings Claude Sonnet 4.6 (Max); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6-adaptive	Not reported	20% Reported settings Claude Sonnet 4.6 (Non-reasoning, High); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6 20.56% Reported settings Claude Sonnet 4.6 (Non-reasoning, Low); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6-non-reasoning-low-effort	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	Not reported	Not reported	73.29% Reported settings Claude Sonnet 4.6 (Max); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6-adaptive	Not reported	70.58% Reported settings Claude Sonnet 4.6 (Non-reasoning, High); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6 69.19% Reported settings Claude Sonnet 4.6 (Non-reasoning, Low); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6-non-reasoning-low-effort	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	Not reported	Not reported	12.22 Reported settings Claude Sonnet 4.6 (Max); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6-adaptive	Not reported	-3.55 Reported settings Claude Sonnet 4.6 (Non-reasoning, High); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6 -2.1 Reported settings Claude Sonnet 4.6 (Non-reasoning, Low); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6-non-reasoning-low-effort	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	Not reported	Not reported	40.87% Reported settings Claude Sonnet 4.6 (Max); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6-adaptive	Not reported	36.52% Reported settings Claude Sonnet 4.6 (Non-reasoning, Low); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6-non-reasoning-low-effort 38.55% Reported settings Claude Sonnet 4.6 (Non-reasoning, High); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6	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	Not reported	Not reported	50.12% Reported settings Claude Sonnet 4.6 (Max); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6-adaptive	Not reported	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	Not reported	Not reported	75.73% Reported settings Claude Sonnet 4.6 (Max); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6-adaptive	Not reported	78.95% Reported settings Claude Sonnet 4.6 (Non-reasoning, Low); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6-non-reasoning-low-effort 79.53% Reported settings Claude Sonnet 4.6 (Non-reasoning, High); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6	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	Not reported	Not reported	34.43% Reported settings Claude Sonnet 4.6 (Max); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6-adaptive	Not reported	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	Not reported	Not reported	53.03% Reported settings Claude Sonnet 4.6 (Max); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6-adaptive	Not reported	46.21% Reported settings Claude Sonnet 4.6 (Non-reasoning, High); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6 42.42% Reported settings Claude Sonnet 4.6 (Non-reasoning, Low); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6-non-reasoning-low-effort	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	Not reported	Not reported	71.16% Reported settings Claude Sonnet 4.6 (Max); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6-adaptive	Not reported	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	Not reported	Not reported	3.03% Reported settings Claude Sonnet 4.6 (Max); Model source: https://artificialanalysis.ai/models/claude-sonnet-4-6-adaptive	Not reported	Not reported	Not reported
ARC-AGI-2ARC Prize · v2 Semi-Private Benchmark details Original public board. Configuration and task coverage may differ; inspect source. Unit: percent. Source collected 2026-10-18.	Not reported	Not reported	60.42% Reported settings Claude Sonnet 4.6 (High); Source model ID: claude_sonnet_4_6_high; 120 tasks	58.33% Reported settings Claude Sonnet 4.6 (Max); Source model ID: claude_sonnet_4_6_max; 120 tasks	Not reported	Not reported	Not reported
DeepSWE v1.1Datacurve · mini-swe-agent Benchmark details Original public board. Configuration and task coverage may differ; inspect source. Unit: percent. Source collected 2026-10-18.	Not reported	Not reported	29.9% Reported settings claude-sonnet-4-6; Reported effort: high; 113 unique tasks; 451 attempts; 4 runs	Not reported	Not reported	Not reported	Not 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 · 8,916 results across 259 models · Collected 2026-10-18

Claude Sonnet 4.6

Compare with

One configuration, seven capabilities

Agentic

Hard reasoning

Coding

Human pref

Knowledge

Multimodal

Long context

Capability score evidence

Benchmark results