general benchmark
Include is a general benchmark with a Score reported as a ratio.
Updated Sep 5, 2026
Higher score ranks better on this benchmark.
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelAN | Score87.60% | Percentile100.00% | Participants31 | EvidenceC | Evaluated |
| Rank02 | ModelAC | Score86.20% | Percentile96.67% | Participants31 | EvidenceC | Evaluated |
| Rank03 | ModelAC | Score85.60% | Percentile93.33% | Participants31 | EvidenceC | Evaluated |
| Rank04 | ModelAC | Score85.10% | Percentile90.00% | Participants31 | EvidenceC | Evaluated |
| Rank05 | ModelAC | Score83.00% | Percentile86.67% | Participants31 | EvidenceC | Evaluated |
| Rank06 | ModelAC | Score82.80% | Percentile83.33% | Participants31 | EvidenceC | Evaluated |
| Rank07 | ModelAC | Score81.60% | Percentile80.00% | Participants31 | EvidenceC | Evaluated |
| Rank08 | ModelAC | Score81.00% | Percentile76.67% | Participants31 | EvidenceC | Evaluated |
| Rank09 | ModelAC | Score80.00% | Percentile73.33% | Participants31 | EvidenceC | Evaluated |
| Rank10 | ModelAC | Score80.00% | Percentile70.00% | Participants31 | EvidenceC | Evaluated |
| Rank11 | ModelAC | Score79.70% | Percentile66.67% | Participants31 | EvidenceC | Evaluated |
| Rank12 | ModelAC | Score79.50% | Percentile63.33% | Participants31 | EvidenceC | Evaluated |
| Rank13 | ModelAC | Score78.90% | Percentile60.00% | Participants31 | EvidenceC | Evaluated |
| Rank14 | ModelAC | Score78.90% | Percentile56.67% | Participants31 | EvidenceC | Evaluated |
| Rank15 | ModelAC | Score76.30% | Percentile53.33% | Participants31 | EvidenceC | Evaluated |
| Rank16 | ModelAC | Score75.60% | Percentile50.00% | Participants31 | EvidenceC | Evaluated |
| Rank17 | ModelAC | Score74.50% | Percentile46.67% | Participants31 | EvidenceC | Evaluated |
| Rank18 | ModelAC | Score74.00% | Percentile43.33% | Participants31 | EvidenceC | Evaluated |
| Rank19 | ModelAC | Score73.46% | Percentile40.00% | Participants31 | EvidenceC | Evaluated |
| Rank20 | ModelAC | Score71.60% | Percentile36.67% | Participants31 | EvidenceC | Evaluated |
| Rank21 | ModelAC | Score71.00% | Percentile33.33% | Participants31 | EvidenceC | Evaluated |
| Rank22 | ModelAC | Score69.50% | Percentile30.00% | Participants31 | EvidenceC | Evaluated |
| Rank23 | ModelAC | Score67.00% | Percentile26.67% | Participants31 | EvidenceC | Evaluated |
| Rank24 | ModelAC | Score64.60% | Percentile23.33% | Participants31 | EvidenceC | Evaluated |
| Rank25 | ModelAC | Score61.40% | Percentile20.00% | Participants31 | EvidenceC | Evaluated |
| Rank26 | ModelGO | Score57.20% | Percentile16.67% | Participants31 | EvidenceC | Evaluated |
| Rank27 | ModelGO | Score57.20% | Percentile13.33% | Participants31 | EvidenceC | Evaluated |
| Rank28 | ModelAC | Score55.40% | Percentile10.00% | Participants31 | EvidenceC | Evaluated |
| Rank29 | ModelAC | Score40.60% | Percentile6.67% | Participants31 | EvidenceC | Evaluated |
| Rank30 | ModelGO | Score38.60% | Percentile3.33% | Participants31 | EvidenceC | Evaluated |
The leading models and scores on this benchmark.
A closer view of the leading scores on this benchmark.
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
What Include measures and how its scores work.
Include is a general benchmark.
It reports a Score as a ratio.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
LLM Stats. Benchmark scores retain their original unit. Overall score eligibility is shown separately.
Common questions about Include.
Claude Opus 4.8 is currently ranked first with 87.60%.
The current leaders are Claude Opus 4.8 (87.60%), Qwen3.7 Max (86.20%), and Qwen3.5-397B-A17B (85.60%).
Qwen3.5-35B-A3B has the lowest matched official input price at $0.25 input / $2.0 output per 1M tokens.
The fastest matched records are Claude Opus 4.8 (42.00 tok/s via Vertex AI), Qwen3-235B-A22B-Instruct-2507 (21.74 tok/s via DeepInfra), and Qwen3 235B A22B (21.74 tok/s via DeepInfra).
No. This benchmark measures one defined capability or task. The overall LLMBoard score uses a separate aggregation across eligible benchmark evidence.
It reports a Score as a ratio.
Yes. Higher values rank better for this benchmark.
31 model results are currently shown.
No. This benchmark is shown for reference but does not contribute to the overall score.
Ranking basisThis include AI model leaderboard uses descending score in the benchmark original unit. The leaderboard ranking keeps matched price and speed data separate from benchmark evidence.
Selection summary
Claude Opus 4.8 currently leads Include with 87.60%. 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.