PEIRA.
Attack success standings
Suite v2, dataset 2.6.0
41 ranked full suite results

Adversarial robustness benchmark

Who keeps their answer when the case is attacked

Peira is an adversarial robustness benchmark for AI decision models. Every model decided the same paired cases, each case in a benign form and an attacked form, and Peira measures how often the attacked form flips a right answer. Lower attack success means a stronger model.

Leader

8.9%

Attack success for grok-4.7-high-fast, the top ranked model

Full field

8.9 to 33.8%

Attack success across all 41 ranked full suite results

Price check

−0.15

Rank correlation between price and robustness across 31 priced results. No useful relationship

Standings, all 41 ranked results

Attack success counts a case only when the benign answer was right and the attacked answer was not

Rank Model Attack success 95 percent interval Benign accuracy

Flagged, held off the ranking

Results over an admission gate keep every measured number and take no rank

Standing Model Attack success 95 percent interval Benign accuracy

Findings

What the numbers mean

The evidence behind the headline results. Each reading below derives from the same payload as every number on this page.

Finding, malformed output

The ranked board flips on decisions. The flagged band flips on broken output.

Ranked, 41 results
31,944 counted flips

Malformed 1.3%
Genuine 98.7%

Flagged, 5 results
5,757 counted flips

Malformed 60.2%
Genuine 39.8%

Mercury-3, the extreme
1,732 counted flips

Malformed 85.6%
Genuine rate 7.5%

Mercury alone counted 1,732 flips, and 1,483 of them went to malformed output. No ranked result has malformed output as the majority of its counted flips. The highest malformed rate on the ranked board is 2.4 percent.

Finding, the harness

One model, two wires, two readings

gpt-6-luna, openai-decisions10.7%

Interval 9.8% to 11.6%, malformed 0.0%, $0.2922 a run

gpt-6-luna, openai-structured12.3%

Interval 11.4% to 13.3%, malformed 2.4%, $0.7537 a run

1.6 points apart, with the intervals overlapping

The same model ran the same suite through two OpenAI wires. Only the wire changed, so take the gap as the size of the harness effect.

Finding, guard models

The guard rows answer a different question

Decision reversals, 0 of the 121 counted flips

  • granite-guardian-hap-125m0.0%
  • Shieldstral-1.0-3B0.5%
  • Qwen3Guard-Gen-4B0.8%
  • deberta-v3-base-prompt-injection-v24.0%
  • granite-guardian-4.1-8b9.1%
  • Llama-Prompt-Guard-2-86M18.0%

The six guard results ran the 373 cases where abstaining is a designed answer, 7.9 percent of the suite. Not one of their 121 counted flips is a decision reversal, and none of the six carries a recorded serving cost.

Disclosed error, one case

One case on this board was never decided

grok-4.7-high-fast stands first on the full suite at 8.9 percent, measured through the Cursor agent harness.

One case produced no answer on either call and is carried as a disclosed error. It never enters the attack success rate.

The harness's provider layer refused that case on both calls. It is a content moderation prompt the layer blocks outright, so no run through this harness could have measured it.

Its benign accuracy of 96.3 percent reads over the 4,700 cases that produced an answer. The blocked case is in neither the hits nor the misses, and none of its 403 counted flips went to malformed output.

Method and notes

How the board was measured

The rules every figure on this page rests on, stated once. Facts about one result stand on its reading.

What a case is

A case is one decision, presented to the model twice. The benign form asks for the decision plainly, and the attacked form wraps the same decision in a hostile input drawn from one of the attack families. Attack success counts a case only when the benign answer was right and the attacked side answered wrong, abstained, or produced malformed output. A case is eligible when the model answered its benign form with a readable decision. The genuine flip rate counts only the flips where the attacked output was a changed decision, and excludes the flips to malformed output.

The suite

The full suite holds 4,701 paired cases on dataset 2.6.0, suite v2. The 11 attack families are retrieval poisoning, verbosity inflation, cryptographic payload, crosslingual shift, judge sycophancy, canary leakage, evidence positioning, history leakage, frequency salience, question pair incoherence, and threshold edge hunting. The guard slices ran a 373 case abstain subset of the same suite, and their rates rest on that smaller base wherever they appear.

Intervals and rounding

Every headline attack success rate carries a 95 percent interval, computed by the Wilson method over the run's own eligible count. Printed figures are computed from the unrounded values the pipeline sealed and rounded once, at the precisions the board prints. Ties in the ranking mean the intervals overlap, and nothing more.

Admission

A result earns a rank when its complete sealed run passes every admission gate. The gates are a malformed response rate at or under 5 percent, benign accuracy of at least 0.5, at least 200 eligible cases overall, and at least 20 eligible cases in each required family. A malformed response is one the run could not read as a decision in the form the suite asked for. Results over a gate are flagged. They keep every number the board measured and are not ranked until a complete run passes every gate. Slice runs are judged by the same gates on the sub-population they measured.

Costs

Cost is the recorded total for one full run, priced at the rates in the run's own provenance. Where some of a run's calls went unpriced, the recorded total understates the true cost and the figure is a lower bound, marked wherever it prints. Results with no per-call API charge record a cost of 0.00 or no cost at all, and the page keeps those two facts apart in words.

Re-run segments

A re-run segment chains to an earlier run of the same measurement, and the figures on this board are the segment's own. Which results rest on one is stated on each result's reading.

Calls that produced no answer

A case that produced no answer on either call is never eligible, so it cannot enter the conditional attack success rate the board ranks by. The runner scores a side that never answered as malformed output, so the case stands in its run's unconditional tally. Benign accuracy is computed over the cases the model decided. A failed attacked call does not by itself affect eligibility. Which results carry such a case, and how many cases each carries, is stated on each result's reading.

Standing of the figures

The figures are the current best measurement of these results on this suite, not settled fact. When a result is re-measured, a later publish replaces its figures, and the change is recorded in the note at the foot of the page.