Arize Phoenix vs Anyscale
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Arize Phoenix
Open source LLM tracing and evaluation that captures spans scores prompts and outputs, clusters failures and offers a hosted AX service with free and enterprise tiers.
Pricing Free, SaaS tiers by quote
Category data
Difficulty Beginner
Type Web App
Status Active
Anyscale
Fully managed Ray platform for building and running AI workloads with pay as you go compute, autoscaling clusters, GPU utilization tools and $100 get started credit.
Pricing Pay as you go
Category data
Difficulty Beginner
Type Web App
Status Active
Feature Tags Comparison
Only in Arize Phoenix
llmobservabilitytracingevaluationopensourceotel
Shared
None
Only in Anyscale
raydistributedtraininginferencegpuautoscaling
Key Features
Arize Phoenix
- • Open source tracing and evaluation built on OpenTelemetry
- • Span capture for prompts tools model outputs and latencies
- • Clustering to reveal failure patterns across sessions
- • Built in evals for relevance hallucination and safety
- • Compare models prompts and guardrails with custom metrics
- • Self host or use hosted AX with expanded limits and support
Anyscale
- • Managed Ray clusters with autoscaling and placement policies
- • High GPU utilization via pooling and queue aware scheduling
- • Model serving endpoints with rolling updates and canaries
- • Ray compatible APIs so existing code ports quickly
- • Observability and cost tracking across jobs and users
- • Environment images with Python CUDA and dependency control
Use Cases
Arize Phoenix
- → Trace and debug RAG pipelines across tools and models
- → Cluster bad answers to identify data or prompt gaps
- → Score outputs for relevance faithfulness and safety
- → Run A B tests on prompts with offline or online traffic
- → Add governance with retention access control and SLAs
- → Share findings with engineering and product via notebooks
Anyscale
- → Scale fine tuning and batch inference on pooled GPUs
- → Port Ray pipelines from on prem to cloud with minimal edits
- → Serve real time models with canary and rollback controls
- → Run retrieval augmented generation jobs cost efficiently
- → Consolidate ad hoc notebooks into governed projects
- → Share clusters across teams with quotas and budgets
Perfect For
Arize Phoenix
ml engineers data scientists and platform teams building LLM apps who need open source tracing evals and an optional hosted path as usage grows
Anyscale
ml engineers data scientists and platform teams that want Ray without managing clusters and need efficient GPU utilization with observability and controls
Capabilities
Arize Phoenix
Spans and Context Professional
Built in and Custom Intermediate
Clustering and Search Intermediate
Hosted AX Basic
Anyscale
Managed Clusters Professional
Model Endpoints Intermediate
Utilization and Cost Intermediate
Enterprise Controls Intermediate
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