Prompt
Can you recommend a safety eval suite for comparing model versions with custom rubrics and batch scoring at scale?
Latest observation
Yes — if you want custom rubrics plus batch scoring at scale, I’d recommend looking at Giskard or OpenAI Evals-style frameworks depending on how much infrastructure you want to manage.
Best fit options
1) Giskard
Good for:
- Safety / toxicity / policy style evaluation
- Custom test suites and rubrics
- Batch execution
- Comparing model versions
- Integrates well with CI / regression testing
Why it’s a strong fit:
- You can define custom checks and datasets
- It’s designed for LLM quality and safety regression testing
- Can be used to compare outputs across model versions at scale
2) OpenAI Evals / eval-framework style setup
Good for:
- Building custom scoring rubrics
- Running large-scale evaluation jobs
- Flexible enough for LLM-as-judge or deterministic scoring
Why:
- Very customizable
- Good if your team is comfortable wiring up eval logic
- Better when you want a framework rather than an out-of-the-box safety product
3) LangSmith Evaluations
Good for:
- Batch evals over traces/outputs
- Custom evaluators and rubrics
- Comparing model versions in application workflows
Why:
- Nice if you already use LangChain/LangSmith
- Strong observability + eval loop
- Good for large-scale comparison runs
4) TruLens
Good for:
- LLM app evaluation
- Custom feedback functions
- Safety/groundedness style metrics
- Batch analysis
Why:
- Flexible and developer-friendly
- Works well for iterative comparisons
If your priority is specifically:
- “Safety suite” → Giskard
- “Custom rubrics + scalable batch evals” → LangSmith Evaluations or OpenAI Evals-style framework
- “Production monitoring + evals” → TruLens
My practical recommendation
If you want the best balance of:
- custom rubrics,
- model-version comparisons,
- and batch scoring at scale,
I’d start with:
1. LangSmith Evaluations if your evals are tied to an app/workflow
2. Giskard if you want a more safety-focused suite
3. OpenAI Evals-style custom framework if you want maximum control
If you want, I can also give you:
- a feature-by-feature comparison table, or
- a recommended architecture for running safety evals across model versions at scale.
Observation history
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