llmboard.aiAI model intelligence
Home

Model Rankings

OverallOpen ModelsAgentCodingReasoningMathKnowledgeInstruction FollowingTextVision
Image GenerationImage Editing
Video GenerationImage to VideoVideo Editing
Text to SpeechSpeech to Text
Embeddings

Efficiency

Chat Token PricingImage PricingVideo PricingAudio Pricing
Chat Speed & LatencyProvider Reliability

Benchmarks

GPQAMMLU-ProAIME 2025SWE-Bench VerifiedMMLUHumanity's Last ExamLiveCodeBenchMATHHumanEvalMMMU-Pro
All Benchmarks

Tools

Model Directory

Scoring & Data

Scoring & Data
1224 models729 benchmarks

Leaderboard Center

Overall RankingCodingCore BenchmarksPrice & ValueRuntime Performance

Modalities

All ModelsImage GenerationImage EditingVideo GenerationImage-to-VideoVideo EditingText-to-SpeechSpeech-to-TextEmbeddings

Data & Methods

Scoring MethodAll Benchmarks
llmboard.aiCopyright 2026 llmboard.ai

multimodal benchmark

TempCompass Leaderboard

TempCompass is a multimodal benchmark for evaluating the temporal perception capabilities of Video Large Language Models (Video LLMs).

Updated Sep 5, 2026

Models2
Model coverage2
MetricScore
EvidenceB

On this page

  • Ranking
  • Highlights
  • Distribution
  • Top models
  • About
  • FAQ

TempCompass Ranking

Higher score ranks better on this benchmark.

2 rows
Columns

Show columns

Sort by
Rank
Model
Score
Percentile
Participants
Evidence
Evaluated
Rank01ModelACQwen2.5 VL 72B InstructAlibaba Cloud / Qwen TeamScore74.80%Percentile100.00%Participants2EvidenceCEvaluatedSep 8, 2026
Rank02ModelACQwen2.5 VL 7B InstructAlibaba Cloud / Qwen TeamScore71.70%Percentile0.00%Participants2EvidenceCEvaluatedSep 8, 2026

TempCompass Highlights

The leading models and scores on this benchmark.

Rank #1Qwen2.5 VL 72B Instruct74.80%Rank #2Qwen2.5 VL 7B Instruct71.70%

TempCompass Score Distribution

A closer view of the leading scores on this benchmark.

TempCompass

The Top AI Models for TempCompass

The first five results on this benchmark, with official price and output speed added where the model identity can be matched.

What is TempCompass?

What TempCompass measures and how its scores work.

TempCompass is a benchmark that uses conflicting videos with identical static content but differing temporal aspects to evaluate Video Large Language Models (Video LLMs).

It measures temporal perception of action, motion, speed, temporal order, and attribute changes through multi-choice QA, yes/no QA, caption matching, and caption generation, using the Score metric as a ratio.

Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.

Family
TempCompass
Modality
multimodal
Primary category
multimodal
Score direction
higher
LLMBoard eligible
No
Evaluation key
overall

LLM Stats. Benchmark scores retain their original unit. Overall score eligibility is shown separately.

FAQ

Common questions about TempCompass.

Which model scores highest on TempCompass?

Qwen2.5 VL 72B Instruct is currently ranked first with 74.80%.

What are the top three models on TempCompass?

The current leaders are Qwen2.5 VL 72B Instruct (74.80%) and Qwen2.5 VL 7B Instruct (71.70%).

Which TempCompass model has the lowest official input price?

Qwen2.5 VL 7B Instruct has the lowest matched official input price at $0.35 input / $1.1 output per 1M tokens.

Which models are fastest among TempCompass results?

No matched runtime record is currently available.

Does the highest score result prove overall model quality?

No. This benchmark measures one defined capability or task. The overall LLMBoard score uses a separate aggregation across eligible benchmark evidence.

What does TempCompass measure?

It measures temporal perception of action, motion, speed, temporal order, and attribute changes through multi-choice QA, yes/no QA, caption matching, and caption generation, using the Score metric as a ratio.

Is a higher score better?

Yes. Higher values rank better for this benchmark.

How many models are compared?

2 model results are currently shown.

Does this benchmark affect the overall score?

No. This benchmark is shown for reference but does not contribute to the overall score.

Ranking basisThis tempcompass AI model leaderboard uses descending score in the benchmark original unit. The leaderboard ranking keeps matched price and speed data separate from benchmark evidence.

  1. 01
    AC
    Qwen2.5 VL 72B InstructAlibaba Cloud / Qwen Team
    Score
    74.80%

    Strengths

    • Ranks #1 of 2 compared models
    • 100th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures TempCompass, not total model capability
  2. 02
    AC
    Qwen2.5 VL 7B InstructAlibaba Cloud / Qwen Team
    Score
    71.70%
    Price
    $0.35 input / $1.1 output per 1M tokens

    Strengths

    • Ranks #2 of 2 compared models
    • 0th percentile on this benchmark
    • C evidence result

    Considerations

    • This result measures TempCompass, not total model capability

Selection summary

Best AI Models for TempCompass

Qwen2.5 VL 72B Instruct currently leads TempCompass with 74.80%. It is the top model on this specific benchmark, while the best LLM for the broader task should also be checked against other benchmarks, price, and runtime.

Use this leaderboard with the supporting benchmark results and coverage details above. A leaderboard position summarizes the selected ranking signal; it does not replace workload-specific testing.

Benchmark rank #1Qwen2.5 VL 72B Instruct74.80%
Benchmark rank #2Qwen2.5 VL 7B Instruct71.70% · $0.35 input / $1.1 output per 1M tokens