TL;DR
Gemma 4 31B received a weak verdict and scored 50/100 in the April 6, 2026 options-strategy evaluation, taking about 40 minutes. All eleven models shared the task, account context, tools and 25-iteration budget. Its three portfolio artifacts measure activity, not achieved account doubling. The evaluation weights strategy fitness most heavily and provides no measured billed-dollar cost column for this run.
- Exact tested ID
- google/gemma-4-31b
- Published studies
- 1
- Provider
Eleven models building an options strategy: compare the tested outputs
11 model runs; same task, account context, tools and 25-iteration budget. Published 2026-04-06. Values retain their original units and grading scale. The unchanged table retains the other reported dimensions. These scores describe the tested task rather than investment returns.
Show the table · 2 rows, 6 columns
Scroll sideways to compare all columns. Select a heading to sort.
| Gemma 4 31B | 50 | weak | 0 | 3 | ~40m |
| Gemini 3 Flash Preview | 66 | mixed | 3 | 6 | 45.5m |
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11 model runs; same task, account context, tools and 25-iteration budget. Published 2026-04-06. Values retain their original units and grading scale.
google/gemma-4-31b was tested on 2026-04-06. 11 model runs; same task, account context, tools and 25-iteration budget. Its row and the other published arm use the same task and measurement units.
What this version helps you choose
The April options evaluator graded this run weak. Its activity and duration do not establish a satisfactory strategy.
Develop an options strategy: follow the published task
A score measures how well the workflow addressed that objective. Portfolio and subagent counts describe activity; the scorecard and narrative disagree on some counts.
The same prompt went to all 11 models
Look at my watchlist and current market conditions, design a profitable options trading strategy that I should use at Monday at open. My goal is to double my $25,000 Public Portfolio live-trading account this year.
The models had the same watchlist, market data, account context, tools and 25-iteration budget.
Flash acted; GPT-5.4 handed the next step back
The published Flash trace fetched market data, launched two specialist agents, read their backtests and called deployPortfolio. GPT-5.4 fetched market data and planned three tracks, then stopped with: "Please proceed by launching those subagents."
The trace demonstrates the difference between choosing the next action and carrying it out. Its Flash process counts disagree with the preserved scorecard.
Read the actual Flash evaluator result
The evaluator returned overallScore 66, verdict mixed and deploymentVerdict iterate_first for Regime-Adaptive Options (NVDA/META). Its listed yearly returns were 2022 +31.22%, 2023 +15.41% and 2024 +0.34%, averaging +15.66%.
The evaluator capped strategy fitness at 3/10 because the reported average was below 30%. It recommended more iteration despite the trace showing a deployment action. Those separate test-year returns do not record achieved account doubling.
Eleven models building an options strategy
Gemma 4 31B scored 50/100 with a weak verdict over ~40m. The goal was an options strategy for a $25,000 account, with the same tools and 25-iteration budget. The verdict grades progress on that goal; it does not record achieved account doubling.
Show the table · 5 rows, 2 columns
| Published metric | Value |
|---|---|
| Score | 50 |
| Verdict | weak |
| Subagents | 0 |
| Portfolios | 3 |
| Time | ~40m |
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Eleven models building an options strategy: read these measurements
Read the complete rubric, sample and billing notes
11 model runs; same task, account context, tools and 25-iteration budget
Develop an options strategy for a $25,000 account with the stated goal of doubling it within a year.
Scoring
The evaluator weights strategy fitness 40%, evidence 25%, exploration 20% and risk realism 15%. No deployment caps fitness at 2/10; single-year evidence caps it at 4/10. The score is a judgment, not a probability of doubling money.
Cost units
This scorecard has no measured billed-dollar cost column.
Time units
Time includes tool use and historical backtesting, not one response.
Subagent
An agent delegated part of the research to another agent.
Portfolio
A strategy artifact created during the run. Its existence alone does not establish a successful strategy.
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