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OpenLLMetry vs Cerebras Inference vs Arize Phoenix

Side by side, from each listing’s own data. A row where every column says the same is shown once, dimmed.

OpenLLMetry vs Cerebras Inference vs Arize Phoenix, side by side
OpenLLMetryby TraceloopRemove OpenLLMetry from this comparisonCerebras Inferenceby CerebrasRemove Cerebras Inference from this comparisonArize Phoenixby Arize AIRemove Arize Phoenix from this comparison
Sets it apart—
  • Most skills (4)
  • Streams responses
  • Newest listing (added Oct 31, 2026)
  • Only one with a CLI
  • No auth required
What it isInstruments LLM and agent applications with OpenTelemetry-native tracing, exporting spans for prompts, tool calls, and chains to any OTel-compatible backend.Serves open-weight LLMs such as Qwen and GPT OSS through an OpenAI-compatible API on wafer-scale hardware, for developers who need very fast inference.Traces, evaluates and debugs LLM and agent applications from an open-source observability platform built on OpenTelemetry, runnable locally or self-hosted.
ProviderTraceloopCerebrasArize AI
Official vendorTraceloopCerebrasArize AI
VerifiedYesSame for all
AccessAPIAPIAPI, CLI
AuthAPI KeyAPI KeyNone
CLI installNo CLINo CLIpippip install arize-phoenix
API base URLIn its docshttps://api.cerebras.ai/v1In its docs
SkillsAuto Instrumentation, Span Export, Workflow TracingTool Calling, Structured Outputs, Batch Inference, Prompt CachingOpenTelemetry Tracing, Evaluation Runs, Prompt Experiments
StreamingNoYesNo
Push notificationsNoSame for all
CategoriesInfrastructure & Ops, Research & KnowledgeLanguage & Translation, Infrastructure & OpsData & Analytics, Infrastructure & Ops
Tagsopentelemetry, llm-tracing, observability, span-export, prompt-monitoring, vendor-neutral, sdk-instrumentationfast-inference, openai-compatible, wafer-scale, llm-api, open-weight-models, structured-outputs, batch-inferencellm-tracing, opentelemetry, span-inspection, prompt-experiments, self-hosted, eval-runner
Listed sinceSep 18, 2026Oct 31, 2026Jul 25, 2026
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/compare?a=openllmetry&b=cerebras-inference&c=arize-phoenix
3 listings side by side · "same" marks a row every column shares
listings
openllmetryapi—cerebras-inferenceapiMost skills (4); Streams responses; Newest listing (added Oct 31, 2026)arize-phoenixapi+cliOnly one with a CLI; No auth required
rows
descriptionInstruments LLM and agent applications with OpenTelemetry-native tracing, exporting spans for prompts, tool calls, and chains to any OTel-compatible backend. | Serves open-weight LLMs such as Qwen and GPT OSS through an OpenAI-compatible API on wafer-scale hardware, for developers who need very fast inference. | Traces, evaluates and debugs LLM and agent applications from an open-source observability platform built on OpenTelemetry, runnable locally or self-hosted.
providerTraceloop | Cerebras | Arize AI
officialTraceloop | Cerebras | Arize AI
verified (same)Yes
accessAPI | API | API, CLI
authAPI Key | API Key | None
cliNo CLI | No CLI | pip: pip install arize-phoenix
apiIn its docs | https://api.cerebras.ai/v1 | In its docs
skillsAuto Instrumentation, Span Export, Workflow Tracing | Tool Calling, Structured Outputs, Batch Inference, Prompt Caching | OpenTelemetry Tracing, Evaluation Runs, Prompt Experiments
streamingNo | Yes | No
push (same)No
categoriesInfrastructure & Ops, Research & Knowledge | Language & Translation, Infrastructure & Ops | Data & Analytics, Infrastructure & Ops
tagsopentelemetry, llm-tracing, observability, span-export, prompt-monitoring, vendor-neutral, sdk-instrumentation | fast-inference, openai-compatible, wafer-scale, llm-api, open-weight-models, structured-outputs, batch-inference | llm-tracing, opentelemetry, span-inspection, prompt-experiments, self-hosted, eval-runner
addedSep 18, 2026 | Oct 31, 2026 | Jul 25, 2026
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