RankingEffort benchmarks

Qwen 3.8-Max · XHigh

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36 measured results · 6 effort settings · 34 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

AQwen 3.8-Max · XHigh1 of 7 capabilities supported

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

Agentic
Unknown
Hard reasoning
A64.3Supported
Coding
A56.8Preliminary
Human pref
Unknown
Knowledge
A26.3Preliminary
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.

Capability score evidence

Qwen 3.8-Max · XHigh: 52.0 overall comparison score. Meets the overall evidence requirements.

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

Which sources carry the weight?

Epoch AI · 50.6% direct comparison weight · independent of the model provider
Datacurve · 49.4% direct comparison weight · independent of the model provider

Which benchmark families carry the weight?

DeepSWE · 49.4% direct comparison weight
GPQA · 11.8% direct comparison weight
Aime · 11.7% direct comparison weight
epoch-game-puzzles · 10.3% direct comparison weight
simpleqa · 8.5% direct comparison weight
Other families (1) · 8.1% 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.

DeepSWE v1.1 review: Epoch AI reported grading errors in at least 23 of 113 tasks. These published results remain included. Review their limitations in Epoch's review when interpreting this evidence.

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 2026-10-20.

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	64 → 63	Up 1	203 remaining / 241 lost	52.5 (+0.5 points)
ARC Prize	67 → 66	Up 1	444 remaining / 0 lost	55.2 (+3.3 points)
Datacurve	67 → 60	Up 7	444 remaining / 0 lost	51.0 (-0.9 points)
LiveCodeBench	67 → 67	No movement	444 remaining / 0 lost	52.0 (-0.0 points)
Scale	67 → 68	Down 1	444 remaining / 0 lost	53.8 (+1.8 points)
Terminal-Bench	67 → 67	No movement	444 remaining / 0 lost	52.3 (+0.3 points)
Cognition	67 → 62	Up 5	444 remaining / 0 lost	51.1 (-0.9 points)
LiveBench	67 → 66	Up 1	443 remaining / 1 lost	53.0 (+1.0 points)
SWE-rebench	67 → 67	No movement	444 remaining / 0 lost	51.0 (-0.9 points)
Epoch AI	66 → 66	No movement	431 remaining / 13 lost	51.6 (-0.4 points)
Vals AI	67 → 66	Up 1	443 remaining / 1 lost	51.2 (-0.7 points)
Provider reports · Anthropic	67 → 67	No movement	444 remaining / 0 lost	52.0 (+0.0 points)
Provider reports · Moonshot AI	67 → 66	Up 1	444 remaining / 0 lost	51.5 (-0.5 points)
Provider reports · Meta	67 → 67	No movement	444 remaining / 0 lost	52.1 (+0.2 points)
Provider reports · Mistral	67 → 67	No movement	444 remaining / 0 lost	52.0 (+0.0 points)
Provider reports · OpenAI	67 → 67	No movement	444 remaining / 0 lost	51.9 (-0.1 points)
All provider reports	67 → 66	Up 1	444 remaining / 0 lost	51.6 (-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
simpleqa	56.5	+4.6
arc-agi	54.4	+2.4
epoch-game-puzzles	50.1	-1.8
aime	50.6	-1.4
mmmu-pro	52.9	+1.0
swe-rebench	51.0	-0.9
deepswe	51.1	-0.9
frontiercode	51.1	-0.9
hle	52.7	+0.7
frontiermath	51.3	-0.7
terminal-bench	52.5	+0.5
gpqa	51.5	-0.5
mmlu-pro	52.4	+0.5
arc-agi-3	51.6	-0.4
swe-atlas-qna	51.6	-0.3
multi-swe-bench	51.6	-0.3
livebench-instructions	52.2	+0.3
harvey	51.7	-0.2
tau-bench	51.7	-0.2
gdp-pdf	52.2	+0.2
livebench-language	52.2	+0.2
livebench-coding	51.8	-0.2
livebench-data	52.1	+0.1
vals-finance-agent	51.8	-0.1
livebench-reasoning	51.8	-0.1
automationbench	51.8	-0.1
vals-legal-research	51.8	-0.1
briefcase	51.9	-0.1
ifbench	51.9	-0.1
gdpval	51.9	-0.1
itbench	51.9	-0.1
vibe-code	51.9	-0.1
swe-atlas-test-writing	51.9	-0.1
apex-agents	52.0	+0.1
enigma-eval	52.0	+0.1
livebench-math	52.0	+0.1
vals-tax-agent	51.9	-0.0
omniscience	52.0	+0.0
critpt	52.0	+0.0
terminal-bench-science	52.0	+0.0
vals-code-migration	52.0	+0.0
aa-lcr	52.0	+0.0
analyst-agent	52.0	+0.0
swe-atlas-refactoring	52.0	+0.0
gmmlu	52.0	+0.0
swe-bench-pro	52.0	+0.0
math500	52.0	+0.0
livecodebench	52.0	+0.0
vals-excel-modeling	52.0	+0.0
enterprise-ops	52.0	-0.0

What evidence is missing from the fit?

Across all collected settings for this model: 103 observations, 21 contributing, 0 matched without graph weight and 82 excluded. Counts do not establish rank eligibility.

3 · 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
7 · Evaluator has not been reviewed for independent admission
1 · Source reports 55.1% and 38/64 completed runs; incomplete trials. Published percentage retained.
3 · Effort is not identified
2 · No matched opponent in this evaluation unit
17 · No reviewed effort for this catalog observation; any separately collected effort measurement is counted separately
36 · Supporting evidence outside the reviewed capability core
1 · 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.
5 · Narrow specialist biological, medical or security evaluation; preserved as raw evidence outside general capability scoring.
1 · The GLM card attributes this evaluation to Artificial Analysis; it is not a new Z.ai comparison.
1 · Composite index or publisher-specific internal evaluation lacks a stable general-capability comparison unit. Composite index excluded to avoid double counting its ingredients.
4 · Legacy self-report lacks a reviewed comparison configuration

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	XHigh	Max	Reasoning	Unspecified
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	Not reported	1,384.6 Elo Reported settings Qwen3.8 Max; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-8-max-0803; Mode from evaluator isReasoning metadata; effort budget not specified	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	Not reported	78.33% Reported settings Qwen3.8 Max; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-8-max-0803; Mode from evaluator isReasoning metadata; effort budget not specified	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	Not reported	49.23% Reported settings Qwen3.8 Max; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-8-max-0803; Mode from evaluator isReasoning metadata; effort budget not specified	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	Not reported	20% Reported settings Qwen3.8 Max; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-8-max-0803; Mode from evaluator isReasoning metadata; effort budget not specified	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	Not reported	20.2% Reported settings Qwen3.8 Max; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-8-max-0803; Mode from evaluator isReasoning metadata; effort budget not specified	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	Not reported	1,604.43 Elo Reported settings Qwen3.8 Max; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-8-max-0803; Mode from evaluator isReasoning metadata; effort budget not specified	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	Not reported	92.73% Reported settings Qwen3.8 Max; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-8-max-0803; Mode from evaluator isReasoning metadata; effort budget not specified	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	Not reported	43.05% Reported settings Qwen3.8 Max; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-8-max-0803; Mode from evaluator isReasoning metadata; effort budget not specified	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	Not reported	19.44% Reported settings Qwen3.8 Max; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-8-max-0803; Mode from evaluator isReasoning metadata; effort budget not specified	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	Not reported	82.31% Reported settings Qwen3.8 Max; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-8-max-0803; Mode from evaluator isReasoning metadata; effort budget not specified	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	Not reported	3.4 Reported settings Qwen3.8 Max; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-8-max-0803; Mode from evaluator isReasoning metadata; effort budget not specified	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	Not reported	31.85% Reported settings Qwen3.8 Max; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-8-max-0803; Mode from evaluator isReasoning metadata; effort budget not specified	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	Not reported	53.24% Reported settings Qwen3.8 Max; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-8-max-0803; Mode from evaluator isReasoning metadata; effort budget not specified	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	Not reported	51.34% Reported settings Qwen3.8 Max; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-8-max-0803; Mode from evaluator isReasoning metadata; effort budget not specified	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	Not reported	81.27% Reported settings Qwen3.8 Max; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-8-max-0803; Mode from evaluator isReasoning metadata; effort budget not specified	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	Not reported	18.69% Reported settings Qwen3.8 Max; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/qwen3-8-max-0803; Mode from evaluator isReasoning metadata; effort budget not specified	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	57.5% Reported settings qwen3-8-max; Reported effort: xhigh; 113 unique tasks; 449 attempts; 4 runs	Not reported	Not reported	Not reported
VulcanBench v3 · Report 12VulcanBench · VulcanBench bare-bones API loop, deterministic hidden tests in Docker Benchmark details Frozen v3, 23 post-cutoff repository tasks. Published pass@1; repeat counts and time budgets vary by report. Display only pending comparability review. Unit: percent. Source collected 2026-10-18.	81.2% Reported settings Qwen3.8-Max; source label: low; low effort; 23 tasks; evaluation 2026-08-04. See source for repeat counts and wall-clock budget.	71% Reported settings Qwen3.8-Max; source label: medium; medium effort; 23 tasks; evaluation 2026-08-04. See source for repeat counts and wall-clock budget.	55.1% Reported settings Qwen3.8-Max; source label: xhigh (default); xhigh effort; 23 tasks; evaluation 2026-08-04. Source reports 55.1% and 38/64 completed runs; incomplete trials. Published percentage retained. Source reports 55.1% and 38/64 completed runs; incomplete trials. Published percentage retained. Source label needs review	Not reported	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	46% Reported settings Epoch AI Inspect; task 2.0.0; scorer exact; model=qwen3.8-max_xhigh; run=bq5y6Tp83KLtxC58UDfpyN; mean accuracy; https://epoch.ai/data/benchmarks.csv	Not reported	Not reported	Not reported
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	46.34% Reported settings Epoch AI Inspect; task 2.0.0; scorer verification_code; model=qwen3.8-max_xhigh; run=PBRdMZyz4L4CqPpXyLD2Lk; mean accuracy; https://epoch.ai/data/benchmarks.csv	Not reported	Not reported	Not reported
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	74.74% Reported settings Epoch AI Inspect; task 2.0.0; scorer verification_code; model=qwen3.8-max_xhigh; run=ABT89ieSWGnGj4RYMduHiG; mean accuracy; https://epoch.ai/data/benchmarks.csv	Not reported	Not reported	Not reported
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	92.68% Reported settings Epoch AI Inspect; task 1.0.11; scorer choice; model=qwen3.8-max_xhigh; run=TEVNDC9QXBh7PQvX9kHZip; mean accuracy; https://epoch.ai/data/benchmarks.csv	Not reported	Not reported	Not reported
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	38% Reported settings Epoch AI Inspect; task 1.0.4; scorer agent_submitted_next_move_scorer; model=qwen3.8-max_xhigh; run=c2YLifDU4zYCX5Jbi9HLL7; mean accuracy; https://epoch.ai/data/benchmarks.csv	Not reported	Not reported	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	99.44% Reported settings Epoch AI Inspect; task 1.1.6; scorer model_extracted_exact_match; model=qwen3.8-max_xhigh; run=aGRKHaq9uSawfYVpC565zU; mean accuracy; https://epoch.ai/data/benchmarks.csv	Not reported	Not reported	Not reported
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	45.8% Reported settings Epoch AI Inspect; task 1.2.0; scorer simpleqa_scorer; model=qwen3.8-max_xhigh; run=bfftd5EzUK9yAekafEofvK; mean accuracy; https://epoch.ai/data/benchmarks.csv	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 · 8,915 results across 259 models · Collected 2026-10-18

Qwen 3.8-Max · XHigh

Compare with

One configuration, seven capabilities

Agentic

Hard reasoning

Coding

Human pref

Knowledge

Multimodal

Long context

Capability score evidence

Benchmark results