RankingEffort benchmarks

GLM-5.3-Flash effort benchmarks

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

Model

GLM-5.3-Flash

33 measured results · 2 reported effort labels · 33 benchmark/harness combinations. Model evidence and sources →

Capability score evidence

GLM-5.3-Flash · Reasoning: 42.1 overall comparison score. Meets the overall evidence requirements.

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.

How sensitive is this score?

Remove one evaluator or family and refit the graph against the same overall panel. Values use the matching dataset audited 2026-09-12. These are sensitivity checks, not confidence intervals; ranking eligibility may also change.

Removed evidence	Recomputed score	Change
Artificial Analysis	Comparison path lost	—
ARC Prize	46.1	+4.0
Datacurve	38.9	-3.2
LiveCodeBench	41.9	-0.2
Scale	43.6	+1.5
Terminal-Bench	42.4	+0.3
Cognition	43.0	+0.9
LiveBench	42.6	+0.5
SWE-rebench	42.5	+0.4
Epoch AI	42.3	+0.2
Vals AI	41.6	-0.5
Provider reports · Anthropic	42.1	-0.0
Provider reports · Moonshot AI	42.0	-0.0
Provider reports · Meta	42.0	-0.1
Provider reports · Mistral	42.1	+0.0
All provider reports	42.0	-0.1

Every benchmark family

Removed evidence	Recomputed score	Change
omniscience	46.0	+4.0
arc-agi	46.0	+3.9
deepswe	38.9	-3.2
enterprise-ops	45.1	+3.0
automationbench	40.2	-1.9
tau-bench	40.7	-1.4
briefcase	40.7	-1.4
gdpval	40.8	-1.3
hle	43.2	+1.1
aa-lcr	41.1	-1.0
mmmu-pro	43.1	+1.0
frontiercode	43.0	+0.9
epoch-game-puzzles	41.2	-0.9
terminal-bench	41.3	-0.8
simpleqa	42.8	+0.7
gdp-pdf	42.8	+0.7
ifbench	41.4	-0.7
scicode	42.6	+0.5
critpt	42.6	+0.5
swe-rebench	42.5	+0.4
mmlu-pro	42.4	+0.3
multi-swe-bench	41.8	-0.3
apex-agents	42.4	+0.3
livebench-instructions	42.3	+0.2
frontiermath	42.3	+0.2
livebench-language	42.3	+0.2
swe-atlas-qna	41.9	-0.2
arc-agi-3	41.9	-0.2
livecodebench	41.9	-0.2
harvey	41.9	-0.2
vibe-code	42.0	-0.1
livebench-coding	42.0	-0.1
livebench-reasoning	42.0	-0.1
analyst-agent	42.2	+0.1
swe-atlas-test-writing	42.0	-0.1
vals-finance-agent	42.0	-0.1
vals-legal-research	42.0	-0.1
gpqa	42.0	-0.1
aime	42.0	-0.1
vals-code-migration	42.0	-0.1
swe-atlas-refactoring	42.0	-0.1
livebench-data	42.1	+0.0
itbench	42.1	+0.0
livebench-math	42.1	+0.0
math500	42.1	-0.0
enigma-eval	42.1	+0.0
swe-bench-pro	42.1	+0.0
gmmlu	42.1	-0.0
vals-excel-modeling	42.1	-0.0

What evidence is missing from the fit?

Across all collected settings for this model: 37 observations, 32 contributing, 0 matched without graph weight and 5 excluded. Counts do not establish rank eligibility.

1 · Benchmark family or source protocol has not been reviewed
4 · No reviewed effort for this catalog observation; any separately collected effort measurement is counted separately

Inspect every observation and exclusion →

Capability profile

One configuration, seven capabilities

Comparison score · 0–100

AGLM-5.3-Flash · Reasoning3 of 7 capabilities supported

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

Agentic
A55.5Supported
Hard reasoning
A42.6Supported
Coding
A52.3Supported
Human pref
Unknown
Knowledge
A19.9Preliminary
Multimodal
Unknown
Long context
A72.9Preliminary

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	Max	Reasoning
AA-Briefcase EloArtificial Analysis · Artificial Analysis published evaluation; see source for benchmark-specific settings Benchmark details AA-Briefcase 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 2026-09-12.	Not reported	1,449.23 Elo Reported settings GLM-5.3-Flash; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/glm-5-3-flash; 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.	Not reported	80% Reported settings GLM-5.3-Flash; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/glm-5-3-flash; Mode from evaluator isReasoning metadata; effort budget not specified
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 2026-09-12.	Not reported	60.37% Reported settings GLM-5.3-Flash; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/glm-5-3-flash; 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.	Not reported	15.43% Reported settings GLM-5.3-Flash; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/glm-5-3-flash; Mode from evaluator isReasoning metadata; effort budget not specified
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 2026-09-12.	Not reported	33.21% Reported settings GLM-5.3-Flash; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/glm-5-3-flash; Mode from evaluator isReasoning metadata; effort budget not specified
GDP.pdf: All-passArtificial 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 2026-09-12.	Not reported	15.4% Reported settings GLM-5.3-Flash; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/glm-5-3-flash; Mode from evaluator isReasoning metadata; effort budget not specified
GDPval-AA v2 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 a human baseline of 1,000 · Higher is better · Evaluation results measured independently by Artificial Analysis Unit: elo. Source collected 2026-09-12.	Not reported	1,655.63 Elo Reported settings GLM-5.3-Flash; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/glm-5-3-flash; 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.	Not reported	91.21% Reported settings GLM-5.3-Flash; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/glm-5-3-flash; 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.	Not reported	39.85% Reported settings GLM-5.3-Flash; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/glm-5-3-flash; Mode from evaluator isReasoning metadata; effort budget not specified
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 2026-09-12.	Not reported	51.11% Reported settings GLM-5.3-Flash; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/glm-5-3-flash; 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.	Not reported	7.47 Reported settings GLM-5.3-Flash; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/glm-5-3-flash; 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.	Not reported	27.5% Reported settings GLM-5.3-Flash; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/glm-5-3-flash; Mode from evaluator isReasoning metadata; effort budget not specified
SciCodeArtificial 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.	Not reported	51.62% Reported settings GLM-5.3-Flash; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/glm-5-3-flash; Mode from evaluator isReasoning metadata; effort budget not specified
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 2026-09-12.	Not reported	47.22% Reported settings GLM-5.3-Flash; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/glm-5-3-flash; Mode from evaluator isReasoning metadata; effort budget not specified
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 2026-09-12.	Not reported	84.27% Reported settings GLM-5.3-Flash; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/glm-5-3-flash; Mode from evaluator isReasoning metadata; effort budget not specified
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 2026-09-12.	Not reported	32.83% Reported settings GLM-5.3-Flash; Reported effort: reasoning; Model source: https://artificialanalysis.ai/models/glm-5-3-flash; Mode from evaluator isReasoning metadata; effort budget not specified
DeepSWE v1.1Datacurve · mini-swe-agent Benchmark details Original public board. Configuration and task coverage may differ; inspect source. Unit: percent. Source collected 2026-09-12.	63.4% Reported settings glm-5-3-flash; Reported effort: max; 113 unique tasks; 448 attempts; 4 runs	Not reported
FrontierCode 1.1 · extended-chiselCognition · chisel Benchmark details FrontierCode 1.1; chisel. Open each result for its exact effort, task subset, metric and protocol details. Unit: percent. Source collected 2026-09-12.	46.21% Reported settings FrontierCode 1.1; extended; 150 tasks; chisel; source effort max; weighted rubric score, not pass rate; unfair internet runs zeroed by evaluator; flag rate 0	Not reported
FrontierCode 1.1 · main-chiselCognition · chisel Benchmark details FrontierCode 1.1; chisel. Open each result for its exact effort, task subset, metric and protocol details. Unit: percent. Source collected 2026-09-12.	31.83% Reported settings FrontierCode 1.1; main; 100 tasks; chisel; source effort max; weighted rubric score, not pass rate; unfair internet runs zeroed by evaluator; flag rate 0	Not reported
Epoch · Chess Puzzles · 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 2026-09-12.	14% Reported settings Epoch AI Inspect; task 1.1.6; scorer model_extracted_exact_match; model=glm-5.3-flash_max; run=b3cBsiDi4D7NtisdffQqxV; mean accuracy; https://epoch.ai/data/benchmarks.csv	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 2026-09-12.	17.07% Reported settings Epoch AI Inspect; task 2.0.0; scorer verification_code; model=glm-5.3-flash_max; run=iCysWvFJevNyw2dbYosU6J; mean accuracy; https://epoch.ai/data/benchmarks.csv	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 2026-09-12.	55.79% Reported settings Epoch AI Inspect; task 2.0.0; scorer verification_code; model=glm-5.3-flash_max; run=YC2u9wykbYQg4gdkf76j26; mean accuracy; https://epoch.ai/data/benchmarks.csv	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 2026-09-12.	90.15% Reported settings Epoch AI Inspect; task 1.0.11; scorer choice; model=glm-5.3-flash_max; run=Jvt5BNr4ERbE9QGgMcEbmT; mean accuracy; https://epoch.ai/data/benchmarks.csv	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 2026-09-12.	8% Reported settings Epoch AI Inspect; task 1.0.4; scorer agent_submitted_next_move_scorer; model=glm-5.3-flash_max; run=TMM3rPrAHcpBG5Pvw9kr4L; 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 2026-09-12.	93.89% Reported settings Epoch AI Inspect; task 1.1.6; scorer model_extracted_exact_match; model=glm-5.3-flash_max; run=NCikvVWc5SEyMEbCqvVNb2; mean accuracy; https://epoch.ai/data/benchmarks.csv	Not reported
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 2026-09-12.	57.85% Reported settings {"checkpoint":"glm-5.3-flash","evaluatorModel":"zai/glm-5.3-flash","sourceUpdatedOn":"2026-09-10","reasoning_effort":"max","compute_effort":null,"reasoning":null,"temperature":1,"top_p":0.95,"max_output_tokens":131072,"verbosity":null,"provider":"Fireworks AI","harness":null}	Not reported
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 2026-09-12.	20.52% Reported settings {"checkpoint":"glm-5.3-flash","evaluatorModel":"zai/glm-5.3-flash","sourceUpdatedOn":"2026-09-10","reasoning_effort":"max","compute_effort":null,"reasoning":null,"temperature":1,"top_p":0.95,"max_output_tokens":128000,"verbosity":null,"provider":"Zhipu AI","harness":null}	Not reported
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 2026-09-12.	45.19% Reported settings {"checkpoint":"glm-5.3-flash","evaluatorModel":"zai/glm-5.3-flash","sourceUpdatedOn":"2026-09-10","reasoning_effort":"max","compute_effort":null,"reasoning":null,"temperature":1,"top_p":0.95,"max_output_tokens":128000,"verbosity":null,"provider":"Zhipu AI","harness":null}	Not reported
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 2026-09-12.	55.93% Reported settings {"checkpoint":"glm-5.3-flash","evaluatorModel":"zai/glm-5.3-flash","sourceUpdatedOn":"2026-09-10","reasoning_effort":"max","compute_effort":null,"reasoning":null,"temperature":1,"top_p":0.95,"max_output_tokens":128000,"verbosity":null,"provider":"Zhipu AI","harness":null}	Not reported
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 2026-09-12.	86.06% Reported settings {"checkpoint":"glm-5.3-flash","evaluatorModel":"zai/glm-5.3-flash","sourceUpdatedOn":"2026-09-01","reasoning_effort":"max","compute_effort":null,"reasoning":null,"temperature":1,"top_p":0.95,"max_output_tokens":128000,"verbosity":null,"provider":"Zhipu AI","harness":null}	Not reported
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 2026-09-12.	62.92% Reported settings {"checkpoint":"glm-5.3-flash","evaluatorModel":"zai/glm-5.3-flash","sourceUpdatedOn":"2026-09-10","reasoning_effort":"max","compute_effort":null,"reasoning":null,"temperature":1,"top_p":0.95,"max_output_tokens":131072,"verbosity":null,"provider":"Fireworks AI","harness":null}	Not reported
Vals AI · Vibe Code Bench v1.1Vals AI · Vals modified OpenHands harness; five hours or 1,000 turns per app Benchmark details Mean app test pass rate on the canonical v1.1 test set. Browser Use executes workflow tests; each test requires at least 90% of its substeps. Automated judging can introduce error. Alternate agents are excluded. Unit: percent. Source collected 2026-09-12.	30.76% Reported settings {"checkpoint":"glm-5.3-flash","evaluatorModel":"zai/glm-5.3-flash","sourceUpdatedOn":"2026-09-10","reasoning_effort":"max","compute_effort":null,"reasoning":null,"temperature":1,"top_p":0.95,"max_output_tokens":131072,"verbosity":null,"provider":"Fireworks AI","harness":"OpenHands"}	Not reported
Vals AI · Harvey Legal Agent Benchmark v1Vals AI · Vals Harvey held-out legal file-work protocol; internet disabled Benchmark details Mean task resolution across two judges (GPT-5.5 Medium and Sonnet 4.6), requiring every criterion to pass. Criteria pass rates and practice-area splits do not add votes. Shared Harvey family; Fable 5 fallback run excluded. Unit: percent. Source collected 2026-09-12.	6.67% Reported settings {"checkpoint":"glm-5.3-flash","evaluatorModel":"zai/glm-5.3-flash","sourceUpdatedOn":"2026-09-10","reasoning_effort":"max","compute_effort":null,"reasoning":null,"temperature":1,"top_p":0.95,"max_output_tokens":128000,"verbosity":null,"provider":"Zhipu AI","harness":null}	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 · 7,424 results across 240 models · Collected 2026-09-12

GLM-5.3-Flash effort benchmarks

GLM-5.3-Flash

Capability score evidence

One configuration, seven capabilities

Agentic

Hard reasoning

Coding

Human pref

Knowledge

Multimodal

Long context