science benchmark
Protein Design — Sequence Generation evaluates the generation of novel protein sequences conditioned on design constraints.
Updated Oct 23, 2026
Higher score ranks better on this benchmark.
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelAN | Score51.00% | Percentile100.00% | Participants2 | EvidenceC | Evaluated |
| Rank02 | ModelAN | Score33.10% | Percentile0.00% | Participants2 | 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 Protein Design — Sequence Generation measures and how its scores work.
A protein design task focused on generating novel protein sequences conditioned on design constraints.
A Score reported 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 Protein Design — Sequence Generation.
Claude Sonnet 5.5 is currently ranked first with 51.00%.
The current leaders are Claude Sonnet 5.5 (51.00%) and Claude Haiku 5.5 (33.10%).
Claude Haiku 5.5 has the lowest matched official input price at $0.10 input / $0.50 output per 1M tokens.
The fastest matched records are Claude Sonnet 5.5 (42.00 tok/s via Anthropic).
No. This benchmark measures one defined capability or task. The overall LLMBoard score uses a separate aggregation across eligible benchmark evidence.
A Score reported as a ratio.
Yes. Higher values rank better for this benchmark.
2 model results are currently shown.
No. This benchmark is shown for reference but does not contribute to the overall score.
Ranking basisThis protein design — sequence generation 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 Sonnet 5.5 currently leads Protein Design — Sequence Generation with 51.00%. 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.