BlogLLM Benchmark Scores as Published, Side by Side

WildClawBench: Results as Published

Every result the catalog holds for WildClawBench: 6 models from 5 developers, read from 1 page. Each number is as printed by the company named beside it; nothing is ranked or rescored. Models are listed by developer, newest first.

Area Tool Use and WorkflowsMaintainer Shuangrui Ding and co-authorsIntroduced 2026Data version 2026103001, as of 2026-10-30

WildClawBench is a set of 60 human-authored tasks for agents that already run in a command-line harness. The tasks are bilingual and multimodal and fall into six categories. Each task runs in a Docker container with a real harness, such as OpenClaw, Claude Code, Codex, or Hermes Agent, and with real tools rather than mock services. Grading mixes fixed rule checks, an audit of side effects in the environment, and a language or vision-language judge.

WildClawBench

ModelValuePrinted bySetup as printed
GPT-5.6 LunaOpenAI, released 2026-07-0950.4%IFM, IFM K2-Horizon-375B-A23B model cardchecked 2026-10-15Effort: max
GPT-5.6 TerraOpenAI, released 2026-07-0960%IFM, IFM K2-Horizon-375B-A23B model cardchecked 2026-10-15Effort: high
GLM-5.2Z.ai, released 2026-06-1655%IFM, IFM K2-Horizon-375B-A23B model cardchecked 2026-10-15Effort: max
MiniMax M3MiniMax, released 2026-06-0156.4%IFM, IFM K2-Horizon-375B-A23B model cardchecked 2026-10-15-
Nemotron 3 UltraNVIDIA, released 2026-06-0434.2%IFM, IFM K2-Horizon-375B-A23B model cardchecked 2026-10-15-
InklingThinking Machines, released 2026-07-1452.3%IFM, IFM K2-Horizon-375B-A23B model cardchecked 2026-10-15Effort: xhigh

Every number here is read from the same catalog file as the benchmark table, data version 2026103001, and is the number the table shows for that model and test. Where one page printed a model under several setups, each value is listed. The catalog is public in armanobosyan/sugra-llm-benchmarks; a wrong number can be reported from the table, with Report an error under the value, or as an issue in that repository.