Best LLM observability tools (2026) | Dashpick

Full ranking

1. #1

   LangSmith

   First-party tracing for LangChain apps—deepest when you already build on LangChain/LangGraph and want turnkey eval loops.

   Average score: 8.8/10

   • Tight integration with LangChain ecosystem
   • Pricing scales with traced volume—watch high-traffic services
   • Great for teams that want hosted eval datasets without building UI

   Detailed scores by criterion(expand)

   Criterion	Score
   Tracing depth	9/10
   Evals & datasets	10/10
   Cost tracking	7/10
   PII & redaction	8/10
   SDK coverage	10/10

2. #2

   Langfuse

   Open-source friendly tracing with SaaS hosting—popular when you want transparency, self-host options, and solid cost dashboards.

   Average score: 8.6/10

   • Self-host path appeals to regulated industries
   • Community moves quickly—follow upgrade guides
   • Pair with your own BI for finance-friendly reporting

   Detailed scores by criterion(expand)

   Criterion	Score
   Tracing depth	9/10
   Evals & datasets	8/10
   Cost tracking	9/10
   PII & redaction	8/10
   SDK coverage	9/10

3. #3

   Helicone

   Proxy-style observability with minimal code changes—great when you need fast spend and latency dashboards across providers.

   Average score: 8/10

   • Low friction for teams juggling OpenAI, Anthropic, etc.
   • Eval depth may trail dedicated experimentation platforms
   • Validate proxy latency impact on ultra-low-latency paths

   Detailed scores by criterion(expand)

   Criterion	Score
   Tracing depth	8/10
   Evals & datasets	6/10
   Cost tracking	9/10
   PII & redaction	8/10
   SDK coverage	9/10

4. #4

   Arize Phoenix

   OSS-first observability with strong ML roots—fits teams blending classic ML and LLM workloads who already think in embeddings.

   Average score: 8.2/10

   • Nice bridge from tabular/embedding monitoring to LLM traces
   • May need more glue for non-Python stacks
   • Great for research teams who want notebooks + UI

   See comparisons

   • Threads vs X

   Detailed scores by criterion(expand)

   Criterion	Score
   Tracing depth	8/10
   Evals & datasets	8/10
   Cost tracking	9/10
   PII & redaction	8/10
   SDK coverage	8/10

5. #5

   Weights & Biases

   Experiment heritage extended to LLM workflows—choose when your org already lives in W&B for training jobs.

   Average score: 7.8/10

   • Single pane for model artifacts + traces if you commit fully
   • Pricing familiar to ML teams but can surprise pure app engineers
   • Less opinionated for non-research orgs without existing W&B contracts

   Detailed scores by criterion(expand)

   Criterion	Score
   Tracing depth	8/10
   Evals & datasets	9/10
   Cost tracking	7/10
   PII & redaction	7/10
   SDK coverage	8/10

6. #6

   Braintrust

   Evaluation-centric platform for teams that treat prompts like shipped code—emphasizes regression tests and reviewer workflows.

   Average score: 7.8/10

   • Strong when PMs + engineers collaborate on eval cases
   • Ensure your CI budget supports frequent eval runs
   • Compare breadth of native integrations vs incumbent suites

   See comparisons

   • Rust vs Go

   Detailed scores by criterion(expand)

   Criterion	Score
   Tracing depth	8/10
   Evals & datasets	9/10
   Cost tracking	7/10
   PII & redaction	7/10
   SDK coverage	8/10

7. #7

   Galileo

   Enterprise guardrails and monitoring—shortlist when compliance stakeholders want proactive drift and safety alerts.

   Average score: 7.4/10

   • Useful for regulated chatbots with policy-heavy reviews
   • May be heavy for tiny teams with simple apps
   • Run POCs on your highest-risk intents first

   Detailed scores by criterion(expand)

   Criterion	Score
   Tracing depth	7/10
   Evals & datasets	8/10
   Cost tracking	6/10
   PII & redaction	9/10
   SDK coverage	7/10

8. #8

   Patronus

   Safety and evaluation emphasis for teams that need structured red-teaming and monitoring in one vendor conversation.

   Average score: 7.6/10

   • Interesting for finance/healthcare pilots with strict review gates
   • Pair with general tracing tools if you need full stack visibility
   • Budget time for policy alignment workshops

   Detailed scores by criterion(expand)

   Criterion	Score
   Tracing depth	7/10
   Evals & datasets	9/10
   Cost tracking	6/10
   PII & redaction	9/10
   SDK coverage	7/10