Track and Compare Every LLM Evaluation in One Dashboard
Valohai LLM is the one place for your team to track, compare, and understand LLM evaluations across models, prompts, and datasets.
Ship with confidence instead of gut feeling.
No credit card required.
Valohai is trusted by teams at
Evaluation Without a System Is Just Guesswork
You changed the prompt. You swapped the model. You tuned the temperature. Each time you got a number — but where did it go?
- Results end up in notebooks, spreadsheets, or Slack threads... hard to find, harder to compare
- Comparing last week's run to today's means re-running everything from scratch
- Stakeholders ask "which model is best?" You struggle to answer confidently
- A 2% accuracy improvement could be real progress or just noise, how do you tell?
You don't have an evaluation problem. You have a tracking and comparison problem.
One Place for Every Evaluation Result Your Team Produces
Valohai LLM is a lightweight SaaS platform purpose-built for LLM evaluation tracking. Run evaluations in your own environment using a simple Python library. Results stream into a shared dashboard where you can filter, aggregate, and compare them side by side.
No infrastructure to manage. No YAML files to write. No MLflow server to babysit.
Track Everything
Every evaluation run is captured, labeled, and queryable. Stop losing results to terminal output and expired notebook sessions.
Compare Anything
GPT-4o vs. Claude vs. your fine-tuned model. Temperature 0.7 vs. 1.0. Dataset A vs. Dataset B. Up to 6 configurations side by side with radar charts, bar charts, and scorecards.
Decide Faster
Group results by any dimension — model, category, difficulty. See exactly where each configuration excels and where it falls apart. Make decisions backed by data, not demos.
From First Install to First Result in Minutes
Upload your evaluation dataset
Bring your test cases as JSONL or CSV. Questions, expected answers, labels, whatever matters to your use case.
Define what to test
Create a task with your parameter grid: which models, which prompts, which settings. Valohai LLM automatically runs every combination against every test case. No loops to write, no scripts to maintain.
Run and compare
Execute evaluations from your terminal with three lines of Python. Results stream into your dashboard in real time. Filter, group, and compare as they arrive.
It's as simple as...
pip install valohai-llmimport valohai_llm
valohai_llm.post_result(
task="support-bot-eval",
labels={"model": "gpt-4o", "category": "billing"},
metrics={"relevance": 0.92, "latency_ms": 340}
)No credit card required.
Built for How Evaluation Actually Works
Real-time streaming
Watch results arrive live as your evaluations run. Spot problems early instead of waiting for the full batch to finish.
Multi-dimensional grouping
Group by model, then by category, then by difficulty. Slice your results however you need to find the signal.
Visual comparison
Radar charts, bar charts, and scorecards make it obvious which configuration wins — and where. Share screenshots, not spreadsheets.
Automatic parameter sweeps
Define a grid of models and settings. The platform runs every combination against every test case. No loop-writing required.
Team workspaces
Everyone sees the same results, the same comparisons, the same source of truth. No more "check my notebook."
Fits your workflow
Post results from CI pipelines, Jupyter notebooks, or standalone scripts. Wherever your evaluations already run. Nothing to migrate.
"Which LLM Should Power Our Support Bot?"
Three models. Four ticket categories. 60 evaluations. One task definition — results stream in automatically.
- Grouped by model — quality and cost tradeoffs at a glance.
- Grouped by model + category — Llama 3 matches GPT-4o on simple tickets but drops on complex ones.
- The decision: Route simple tickets to Llama 3, complex ones to Claude 3 Opus. API costs drop 60%.
From data upload to business decision — minutes, not days.
Watch the full example walkthrough in the video.
Try It With Your Own DataYou've Tried the Alternatives
Beyond Spreadsheets
For one person, one run, one model — spreadsheets work great. But when multiple engineers are comparing multiple models across multiple runs, things get fragile fast. Columns drift, versions multiply, and context disappears.
Not Another Observability Platform
No tracing, no prompt management. Just evaluation tracking, done right. If you only need to track and compare eval results, you shouldn't have to adopt an entire observability stack.
Start Small, Scale Later
Begin with eval tracking. When you're ready for compute orchestration, automated pipelines, and deployment — Valohai LLM connects to the broader Valohai platform.
Valohai LLM does one thing well: evaluation tracking and comparison. Start here, scale when you need to.
Ready to Bring Order to Your Evals?
Sign up, upload a dataset, and run your first evaluation in minutes. No credit card, no sales call, no infrastructure setup.
Start Tracking FreeNo credit card required.