DeepEval vs Future AGI
A side-by-side comparison of DeepEval and Future AGI, two Eval tools, drawn from Ignaite's continuously-verified listings.
Compared from listings verified as of
Future AGI
EvalEvaluation, observability, and optimization platform for AI agents and LLM apps.
View Future AGIAt a glance
| Attribute | DeepEval | Future AGI |
|---|---|---|
| Category | Eval | Eval |
| Pricing | FREEMIUM | FREEMIUM |
| License | Open core | Open core |
| Deployment | Hybrid | Hybrid |
| Platforms (differs) | CLI, API | Web, API |
| Model support (differs) | BYO key / model | Multi-model |
| Vendor (differs) | Confident AI | Future AGI |
| Capabilities (differs) |
|
|
The honest brief
DeepEval
Write LLM evals as Pytest-style assertions and run them in CI, backed by 50+ metrics across RAG, agents, and safety.
- Assertions run in your CI pipeline
- Metrics for RAG, agents, and safety
- Bring any judge model (BYO key)
- Integrates LangChain/CrewAI/OpenAI
- LLM-as-judge adds cost
- Dashboards need paid Confident AI
- Judge metrics can be noisy
Future AGI
One of the few fully open-source, self-hostable eval stacks that also bundles a model gateway and runtime guardrails, not just offline scoring.
- Open-source, Apache-2.0 licensed
- Self-hostable end-to-end
- Multimodal evaluation support
- Bundles guardrails and a gateway
- Newer, smaller community
- Broad scope can feel complex
- Docs still maturing
When to pick which
Future AGI leans on LLM observability as a headline capability; DeepEval treats it as secondary.
- LLM observability (primary capability)
They also differ on:
- Platforms
- CLI, API · Web, API
- Model support
- BYO key / model · Multi-model
Their capability lists differ in recorded depth — compare the full lists above before deciding.