Benchmark prompts and models on real datasets, score outputs automatically, inspect failures, and ship LLM features with confidence.
Most LLM teams still evaluate changes with manual spot checks and intuition. Without structured datasets, automated metrics, and traceable experiments, hallucinations and quality regressions ship silently to production. At the same time, costs and latency can spiral out of control when switching models without a shared benchmark.
LLM EvalForge brings datasets, experiments, scoring, observability, and human review into one workflow.
Get instant, actionable insights with our interactive observability dashboard. Compare accuracy against latency and cost in real-time as your evaluations run.
Many teams default to massive, expensive frontier models for everything. But for specialized, repetitive tasks, a smaller fine-tuned model often performs just as well—at a fraction of the cost and latency.
EvalForge helps you uncover these inefficiencies. By testing multiple models against the same benchmark, you can confidently switch to a smaller model knowing exactly how it impacts your bottom line and user experience.
1T+ Parameters
Optimal choice
EvalForge powers a self-improving loop where real-world interactions continuously refine your AI models. By automating data curation, model evaluation, and guardrail enforcement, your AI agents get smarter, safer, and cheaper to run over time.
Collect human feedback and edge cases from production to form high-quality evaluation datasets.
Automatically score new data against custom benchmarks to verify answers align to application requirements.
Ensure specific privacy, security, and safety requirements are met when interacting with users.
Use curated ground-truth data to fine-tune smaller, faster models, slashing inference costs while preventing model drift.
EvalForge is designed to integrate seamlessly with the open-source AI ecosystem. Import your favorite datasets and models directly from Hugging Face to instantly access a massive library of resources, increasing your chances of finding the perfect fit for your specific use case.
Need maximum privacy or zero latency? EvalForge fully supports connecting to locally running models using Ollama, vLLM, or LM Studio, ensuring your sensitive data never leaves your environment.
Many teams default to massive, expensive frontier models for everything. But for specialized, repetitive tasks, a smaller fine-tuned model often performs just as well—at a fraction of the cost and latency.
EvalForge helps you uncover these inefficiencies. By testing multiple models against the same benchmark, you can confidently switch to a smaller model knowing exactly how it impacts your bottom line and user experience.
1T+ Parameters
Optimal choice
We're building the missing infrastructure layer for AI engineers who need more than just an API wrapper.
Build reusable evaluation datasets, tag edge cases, and version benchmarks.
Run side-by-side prompt and model variants on the same dataset.
Mix deterministic metrics with LLM-as-a-judge scoring.
Track scores, latency, token usage, cost, and failures in one place.
Send low-scoring outputs into a human review queue.
Launch iterative optimization jobs to improve prompts.
Built For Production
Join the private beta to get early access to the ultimate evaluation stack for AI engineers.