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Braintrust vs Fireworks AI vs Arize Phoenix

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

Braintrust vs Fireworks AI vs Arize Phoenix, side by side
Braintrustby Braintrust DataRemove Braintrust from this comparisonFireworks AIby Fireworks AIRemove Fireworks AI from this comparisonArize Phoenixby Arize AIRemove Arize Phoenix from this comparison
Sets it apart
  • Only one with an MCP server
  • Most skills (5)
  • Official Fireworks AI listing
  • Streams responses
  • Newest listing (added Aug 11, 2026)
  • No auth required
  • Official Arize AI listing
What it isEvaluates and observes LLM applications end to end: capture traces, score them with evals, iterate in a prompt playground, and gate deploys on eval results run from CI.Production inference platform for open models with fast function calling, structured output, and fine-tuning behind an OpenAI-compatible API.Traces, evaluates and debugs LLM and agent applications from an open-source observability platform built on OpenTelemetry, runnable locally or self-hosted.
ProviderBraintrust DataFireworks AIArize AI
Official vendorNot an official listingFireworks AIArize AI
VerifiedYesSame for all
AccessAPI, MCP, CLIAPIAPI, CLI
AuthBearer TokenAPI KeyNone
MCP serverIn its setup guideNo MCP serverNo MCP server
CLI installIn its docsNo CLIpippip install arize-phoenix
API base URLIn its docshttps://api.fireworks.ai/inference/v1In its docs
SkillsExperiment Based Evals, Production Trace Logging, Prompt Playground, Human Review And Datasets, Braintrust CLINone listedOpenTelemetry Tracing, Evaluation Runs, Prompt Experiments
StreamingNoYesNo
Push notificationsNoSame for all
CategoriesInfrastructure & Ops, Code & DevToolsLanguage & Translation, Infrastructure & OpsData & Analytics, Infrastructure & Ops
Tagseval-driven-development, prompt-playground, trace-logging, human-review, llm-proxy, scorers, dataset-management, ci-eval-gatesinference, function-calling, structured-output, open-modelsllm-tracing, opentelemetry, span-inspection, prompt-experiments, self-hosted, eval-runner
Listed sinceAug 1, 2026Aug 11, 2026Jul 25, 2026
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/compare?a=braintrust&b=fireworks-ai&c=arize-phoenix
3 listings side by side · "same" marks a row every column shares
listings
braintrustapi+cli+mcpOnly one with an MCP server; Most skills (5)fireworks-aiapiOfficial Fireworks AI listing; Streams responses; Newest listing (added Aug 11, 2026)arize-phoenixapi+cliNo auth required; Official Arize AI listing
rows
descriptionEvaluates and observes LLM applications end to end: capture traces, score them with evals, iterate in a prompt playground, and gate deploys on eval results run from CI. | Production inference platform for open models with fast function calling, structured output, and fine-tuning behind an OpenAI-compatible API. | Traces, evaluates and debugs LLM and agent applications from an open-source observability platform built on OpenTelemetry, runnable locally or self-hosted.
providerBraintrust Data | Fireworks AI | Arize AI
officialNot an official listing | Fireworks AI | Arize AI
verified (same)Yes
accessAPI, MCP, CLI | API | API, CLI
authBearer Token | API Key | None
mcpIn its setup guide | No MCP server | No MCP server
cliIn its docs | No CLI | pip: pip install arize-phoenix
apiIn its docs | https://api.fireworks.ai/inference/v1 | In its docs
skillsExperiment Based Evals, Production Trace Logging, Prompt Playground, Human Review And Datasets, Braintrust CLI | — | OpenTelemetry Tracing, Evaluation Runs, Prompt Experiments
streamingNo | Yes | No
push (same)No
categoriesInfrastructure & Ops, Code & DevTools | Language & Translation, Infrastructure & Ops | Data & Analytics, Infrastructure & Ops
tagseval-driven-development, prompt-playground, trace-logging, human-review, llm-proxy, scorers, dataset-management, ci-eval-gates | inference, function-calling, structured-output, open-models | llm-tracing, opentelemetry, span-inspection, prompt-experiments, self-hosted, eval-runner
addedAug 1, 2026 | Aug 11, 2026 | Jul 25, 2026
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