MKA
Gemini 4 Hydrogen 53.4% Agents complete professional tasks whose work is visual, 200 tasks across 10 fields and 83 occupations, each about three to eight hours of expert work. An agentic grader checks each deliverable against an expert rubric of about 70 yes or no checks, weighted 75% on factual accuracy and 25% on visual design.
Artificial Analysis runs the 200-task set and keeps it private. Ten sample tasks are public on Hugging Face. Every model runs in the same agent harness, Stirrup. The grader is built on a model from outside Google, and experts agreed with it 96% of the time. Labs report Climb WSR, the weighted share of the harder rubric checks a model meets. We don't import Artificial Analysis's leaderboard, so scores here come from lab posts.
- Made by
- Google DeepMind and Artificial Analysis
- Released
- November 2026
- Kind
- Tasks from real jobs
- Level
- Expert
- Scored
- Graded by a model
- Answers
- Open-ended
- Tasks
- Public, plus a private test set
- Last in a launch post
- November 2026
- Last model added
- November 2026
Gemini 4 Hydrogen leads with 53.4%
Best score per model as labs report them in their own cards, drawn striped. Labs pick their own settings, so these compare less cleanly than independent runs.
Source: Labs’ model cards
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | Gemini 4 Hydrogen | 53.4% | Nov 2026 | Lab model card |
Scores over time
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Source: Labs’ model cards
One lab put it in a launch post in the last six months
Launch posts from every lab that has listed it, one tick per post. Tall colored ticks include it, and short gray ones leave it out.
| Date | Launch post | Score | As the post writes it |
|---|---|---|---|
| Nov 12, 2026 | Gemini 4 Hydrogen | 53.4 | MKA (Climb WSR accuracy) |
More in Economic work
- JobBench In use 130 tasks from 35 occupations workers most want delegated. Agent works through messy reference files, graded by fact-anchored binary rubrics. GLM-5.3 61.4%
- GDPval In use Real work tasks from 44 occupations with reference files. Experts blindly compare model deliverables with expert work. Metric is win-or-tie rate.
Seed2.1 Pro 87.9% - GDPval-AA v2.1 In use Agents with shell and web access complete 220 GDPval gold tasks from 44 occupations. Blind pairwise comparisons give Elo ratings. Claude Opus 5.5 1,846
- AA-Briefcase v1.1 In use Version 1.1 of Artificial Analysis's multi-hour office work evaluation, with Elo ratings fitted by Crowd-BT. Claude Opus 5.5 1,822
- CoWorkBench In use Agent completes long-horizon productivity tasks across computer science, finance, law and medicine. Qwen in-house scoring (method unpublished). Claude Fable 5 75.9%
- Vending-Bench 2 In use Agent runs a simulated vending-machine business for one year starting with $500. Score is the final bank balance, averaged over runs. Gemini 4 Carbon $16,484