Comparison
Arize Phoenix vs Span
Arize Phoenix and Span are both common AI/LLM terms but cover different ideas. Here is a quick side-by-side.
When you would reach for Arize Phoenix
When you want open-source LLMOps tooling that works in notebooks, the IDE, and production with the same instrumentation.
A team instruments their RAG pipeline with the Phoenix tracer, then runs the built-in faithfulness eval on yesterday's traffic to find sessions where the model contradicted the docs.
When you would reach for Span
Span comes up when the question is fundamentally about infrastructure.
An LLM span: model=gpt-4o, input=system+user msgs, output=response text, tokens_in=820, tokens_out=410, latency=1.8s, cost=$0.0061.
Frequently asked
What is the difference between Arize Phoenix and Span?
Arize Phoenix: Arize Phoenix is an open-source LLM observability and evaluation tool. It ingests OpenTelemetry traces, renders them in a debug UI, and provides built-in LLM-as-judge evaluators for hallucination, relevance, and toxicity. Span: A span is a single unit of work within a trace — one LLM call, one tool call, one retrieval — with a start time, end time, attributes (model, tokens, cost), and a parent span that links it into the trace tree.
When should I use Arize Phoenix vs Span?
When you want open-source LLMOps tooling that works in notebooks, the IDE, and production with the same instrumentation. Span applies when you are focused on infrastructure.
Are Arize Phoenix and Span the same thing?
No. Arize Phoenix is infrastructure; Span is infrastructure. They are related but address different parts of the AI stack.