Ornith AI
partialShows if the model has enough results for an index.Ornith-1.5-397B
Ornith-1.5-397B is a reasoning model from Ornith AI in the Ornith 1.5 family. 14 benchmarks count toward its score, in 3 categories.
IndexOverall score out of 100.Unranked
CoverageShare of the index weight with results.55%
SpeedOutput tokens per second.—
Input / 1MUS dollars per 1M input tokens.Free
Output / 1MUS dollars per 1M output tokens.Free
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
14 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. |
|---|---|---|---|---|---|---|
| Graduate-Level Google-Proof Q&A | Knowledge | 92.8% | 63.9 | — | — | David Rein et al. |
| GPQA Diamond | Knowledge | 92.8% | 63.9 | — | — | David Rein et al. |
| BrowseComp | Agentic | 86.6% | 72.5 | — | — | OpenAI |
| Terminal-Bench 2.1 (provider run) | Agentic | 86.1% | 74.9 | — | — | DeepSeek-AI |
| Terminal-Bench 2.1 (provider run) | Agentic | 86.1% | 74.9 | — | — | DeepSeek-AI |
| Software Engineering Benchmark Verified | Coding | 86.0% | 66.5 | — | — | Carlos E. Jimenez et al. |
| Claw-Eval | Agentic | 81.4% | 86.3 | — | — | Bowen Ye et al. |
| WideResearch | Agentic | 80.8% | 66.7 | — | — | Qwen |
| MCP Atlas | Agentic | 80.0% | 68.4 | — | — | OpenAI |
| Toolathlon-Verified | Agentic | 71.2% | 69.9 | — | — | Moonshot AI |
| SWE-bench Pro | Coding | 65.1% | 67.0 | — | — | Xiang Deng et al. |
| NL2Repo | Coding | 59.5% | 71.8 | — | — | MiniMax |
| Humanity's Last Exam with tools | Agentic | 56.1% | 68.9 | — | — | DeepSeek-AI |
| DeepSWE | Agentic | 56.0% | 64.5 | — | — | Datacurve AI |
| Humanity's Last Exam | Knowledge | 44.6% | 66.6 | — | — | Center for AI Safety et al. |
| Humanity's Last Exam without tools | Knowledge | 44.6% | 66.6 | — | — | OpenAI |
| Terminal-Bench 3.0 | Agentic | 13.5% | 65.2 | — | — | Ryan Marten et al. |
14 benchmarks count, from 17 of 17 results. A grey row does not count. Too few models took that benchmark.