InternScience
partialShows if the model has enough results for an index.Agents-A1
Agents-A1 is a reasoning model from InternScience. 5 benchmarks count toward its score, in 3 categories.
IndexOverall score out of 100.Unranked
CoverageShare of the index weight with results.40%
SpeedOutput tokens per second.—
Input / 1MUS dollars per 1M input tokens.N/A
Output / 1MUS dollars per 1M output tokens.N/A
ContextMaximum tokens in one request.262K
EloLMArena rating and rank.N/A
The index is a score out of 100. The ± range shows how much it can change.
CapabilitiesScore per category, out of 100.
Out of 100Results
5 counted| BenchmarkThe test name. | CategoryThe capability that the test measures. | ResultThe score from the publisher. | IndexThis result as a score out of 100. | RunThe settings of the run. | DateDate of the result. | Published byThe source of the result. |
|---|---|---|---|---|---|---|
| Instruction-Following Eval | Instruction | 94.8% | 55.6 | — | — | Jeffrey Zhou et al. |
| BrowseComp | Agentic | 75.5% | 63.2 | — | — | OpenAI |
| LongBench v2 | Reasoning | 60.2% | — | — | — | LongBench v2 authors |
| Humanity's Last Exam with tools | Agentic | 47.6% | 60.7 | — | — | DeepSeek-AI |
| Humanity's Last Exam | Knowledge | 47.6% | 69.1 | — | — | Center for AI Safety et al. |
| VITA-Bench | Agentic | 38.8% | 55.1 | — | — | Meituan LongCat Team |
5 benchmarks count, from 5 of 6 results. A grey row does not count. Too few models took that benchmark.