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Model succession engine

Move the model.Keep the capability.

Companies replace models and can silently lose behavior their application depends on. InheritBench finds what broke, helps recover it, and proves whether the replacement is ready to ship.

What InheritBench does

1

Find what broke

Measure which required behaviors disappeared after the model change.

2

Recover the behavior

Target the gaps and select a recovered successor under control.

3

Decide whether to ship

Run final evaluation and safety checks against explicit readiness rules.

The browser evaluates precomputed predictions. Model training and inference happen outside the browser.

The replacement risk

A replacement can sound right and still break your application.

Teams switch models for cost, latency, licensing, infrastructure, or vendor reasons. General benchmarks do not prove that application-specific rules survived the move.

Plausible text can still use the wrong policy code, bypass an approval, violate a contract, or choose an unsafe action. InheritBench tests the behavior the application actually requires.

The reference replacement produced valid-looking output while preserving only 0 of 32 required behaviors.

How it works

Diagnose → Recover → Assure

Turn a model replacement into three clear questions: what was lost, can it be recovered, and is the successor ready to ship?

01

Diagnose

Compare the replacement with the behavior your application already depends on.

02

Recover

Target the missing behavior and compare recovery candidates without using final-test results.

03

Assure

Apply the same evaluation and safety rules to decide whether the recovered successor is ready to ship.

Try it yourself

Choose → Run → Review

Choose a built-in candidate, run the evaluation in your browser, and review the readiness decision. Then introduce a controlled failure and see the decision change.

Open the Assurance Lab

Reference result

Qwen capability recovered on an OLMo successor.

Four recovery candidates were compared without looking at final-test results. Candidate 0 was selected, then evaluated once on clean and adversarial records.

CONDITIONAL PASS
Source
Qwen2.5-0.5B
Successor
OLMo-2-0425-1B
Selected candidate
Candidate 0

64 / 64

Operational correctness

63 / 64

Exact-contract fidelity

64 / 64

Strict validity

2 on 1 adversarial record

Safety findings

CONDITIONAL_PASS

Readiness

Clean behavior recovered fully. Adversarial evidence retained 2 safety findings on 1 record, producing a conditional deployment decision.