InclusionAI
partialShows if the model has enough results for an index.LLaDA2.2-flash
LLaDA2.2-flash is a reasoning model from InclusionAI in the LLaDA2.2 family. 6 benchmarks count toward its score, in 2 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.Free
Output / 1MUS dollars per 1M output tokens.Free
ContextMaximum tokens in one request.128K
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
6 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. |
|---|---|---|---|---|---|---|
| PinchBench | Agentic | 81.7% | — | — | — | Kilo Code |
| τ²-Bench Tool-Agent-User Evaluation | Agentic | 80.3% | 56.5 | — | — | Victor Barres et al. |
| Claw-Eval | Agentic | 64.2% | 59.3 | — | — | Bowen Ye et al. |
| Berkeley Function Calling Leaderboard v4 | Agentic | 60.8% | 45.5 | — | — | Arcee AI |
| Software Engineering Benchmark Verified | Coding | 49.3% | 37.1 | — | — | Carlos E. Jimenez et al. |
| MCP Atlas | Agentic | 46.2% | 43.1 | — | — | OpenAI |
| SWE-bench Pro | Coding | 30.1% | 33.1 | — | — | Xiang Deng et al. |
6 benchmarks count, from 6 of 7 results. A grey row does not count. Too few models took that benchmark.