Arize AI Pricing: Plans, Costs, and Which One to Choose in 2026

Arize AI pricing starts at $50/month on the AX Pro plan. I've tested several AI observability platforms, and Arize is one of the more expensive options, though it's built for teams that need enterprise-grade features.

This breakdown covers the exact plan costs, what you actually get, and when the price makes sense.

Arize AI Pricing Plans: At a Glance

Arize AI Pricing Plans Breakdown

Each Arize plan charges differently depending on how much your account actually runs.

Phoenix: Free (Self-Hosted, Open Source)

What's included: Open-source, self-hosted platform with no caps on spans (the steps Arize records per AI agent run), ingestion, projects, or retention. Agent tracing, multi-agent graphs, token tracking, custom metrics, dashboards, and monitoring are included.

SDKs for Python and JavaScript ship with the platform, and a paid support add-on is available separately.

Best for: Teams with the DevOps bandwidth to run their own servers and organizations that can't let trace data leave a specific country or region.

Pros:

✅ No caps, period. Your servers decide how much you collect and how long you keep it.

✅ Every eval model runs on open standards, so you can check exactly how your AI is being scored, and nothing is locked away.

Cons:

❌ Alyx, online evaluations, and production monitors don't exist here. Those only run on Arize's cloud.

❌ No uptime guarantee, no SOC2 or HIPAA coverage, no support unless you pay for the add-on.

AX Free: $0/month

What's included: 25,000 spans per month, 1 GB ingestion, and 15-day retention before Arize wipes the history. Adds Alyx (Arize's AI assistant for debugging traces and optimizing prompts), a full evaluation suite with LLM-as-a-judge scoring, production monitors, and human annotation tools.

Prompt management covers version control, side-by-side comparison, and automated optimization. Google and GitHub logins are included, with a data region selector available across the US, EU, or Canada.

Best for: Solo developers and early-stage startups testing an LLM app or AI agent before it sees real traffic.

Pros:

✅ Alyx and the full evaluation suite at $0. Both Langfuse and LangSmith charge for evaluations, but Arize doesn't on this tier.

✅ You can pick your data region (US, EU, Canada) for free, unlike most platforms that only unlock it on paid plans.

Cons:

❌ Run a live agent through a busy afternoon, and that 25K is gone. It goes faster than you'd expect.

❌ No way to pay for extra usage. Once you hit the ceiling, it's either upgrade or stop collecting.

AX Pro: $50/month

What's included: AX Pro takes everything from the free tier and doubles the span limit to 50,000 per month, bumps ingestion to 10 GB, and extends retention to 30 days.

AX Pro has hard limits. Once you hit 50K spans or 10 GB, you'll need to upgrade to Enterprise for additional capacity. Email support and a startup discount program are also included.

Best for: Small production teams who need the data to keep flowing past their monthly limit without someone manually upgrading the account. Qualifying startups can apply for reduced pricing, with $50 as the ceiling rather than the starting point.

Pros:

✅ No per-seat charges. Add your whole team without a procurement conversation.

✅ 10 GB works fine for most teams running basic LLM setups in production, as long as you're not logging full prompt and response text on every call.

Cons:

❌ The hard cap at 50K spans or 10 GB means you lose data collection when you hit it, rather than getting a predictable bill.

❌ No SOC2, HIPAA, enterprise SSO, or audit logs. One compliance requirement from legal sends you straight to Enterprise.

❌ Offline evaluations don't work on data older than 30 days. Retroactive analysis is off the table.

AX Enterprise: Custom Pricing

What's included: Everything in AX Pro, with all fixed limits replaced by negotiated allowances. Adds dedicated support, a contractual uptime SLA, and the full compliance bundle: SOC2 Type II, HIPAA, GDPR, enterprise SSO, role-based access controls, and audit logs.

Also includes ADB Data Fabric, Arize's data store for petabyte-scale telemetry with sub-second queries. It runs on managed cloud or can be self-hosted, with data residency controls available on the self-hosted path.

Best for: Companies in healthcare, finance, or legal that need HIPAA and SOC2 under one roof, and engineering teams running multi-agent systems at a scale where standard observability tools start falling apart.

Pros:

✅ ADB Data Fabric handles petabyte-scale telemetry with sub-second queries. Arize claims teams pay 100x less than traditional platforms.

✅ SOC2 Type II, HIPAA, GDPR, audit logs, and SSO enforcement in one contract. No extra vendors, no patchwork.

Cons:

❌ The jump from $50/month to a custom contract with no middle ground is a real gap for mid-size teams.

❌ Multi-region teams end up managing two systems. Arize recommends a hybrid Phoenix-plus-AX setup for those cases.

Which Arize AI Plan Should You Choose?

Choose Phoenix if you:

• Have a dedicated DevOps team and want zero usage limits
• Need full data sovereignty, meaning trace data can't leave your own servers
• Are comfortable managing your own infrastructure without uptime guarantees or SLAs

Choose AX Free if you:

• Are a solo developer or early-stage startup validating a first LLM app
• Want access to Alyx and the full evaluation suite before committing to a paid plan
• Need data region selection (US, EU, Canada) without paying for it

Choose AX Pro if you:

• Run a small production team and need data to keep flowing past monthly limits
• Don't have compliance requirements like SOC2 or HIPAA yet
• Are a qualifying startup looking to apply for reduced pricing

Choose AX Enterprise if you:

• Operate in healthcare, finance, or legal, and need HIPAA and SOC2 in one platform
• Run multi-agent systems at a scale where 50K spans/month isn't close to enough
• Need a guaranteed uptime SLA and dedicated support backed by a contract

Is Arize AI Worth the Cost?

It depends on the tier and your needs.

AX Free and Phoenix are genuinely good deals. AX Pro at $50/month works if you don't run RAG and have no compliance requirements. AX Enterprise, at a median of $60,000/year, is where the math gets harder to justify.

Arize is worth it if you:

• Run a regulated business that needs HIPAA, SOC2, and production observability in one place. Piecing together separate tools costs more.
• Operate multi-agent systems at petabyte scale where ADB Data Fabric's query performance is the deciding factor.
• Need the full evaluation suite (LLM-as-a-judge, agent path evals, online evals) managed rather than self-hosted.

Skip Arize if you:

• Run a small team with no compliance requirements.
• Have a RAG-heavy architecture. The dual-axis billing compounds fast.
• Need more than 30 days of historical data for retroactive evaluation. That limitation doesn't go away until Enterprise.
• Ship a voice AI product. Arize monitors your LLM backend but doesn't cover pre-production call simulation or live voice monitoring. Cekura handles that layer and integrates with your existing stack.

Arize AI Alternatives and Pricing Comparison

Arize AI isn't the only option. Here's how it stacks up against the main alternatives:

Logfire vs. Arize AI: Which Should You Choose?

Logfire is better for:

• Teams that want full-stack observability beyond LLM calls. Logfire traces HTTP layers, database queries, and background workers in the same view.
• Anyone running RAG applications.
• Small teams watch costs. At 50M spans, Logfire runs $129/month. Arize Pro hits overages well before that.

Arize is better for:

• Regulated industries that need HIPAA, SOC2, and GDPR in one managed platform.
• Teams running multi-agent systems that need ADB Data Fabric's petabyte-scale performance.
• Organizations that need enterprise SSO, role-based access controls, and audit logs from day one.

Use both if:

• You need Arize's compliance stack for enterprise requirements, but want Logfire to handle the rest of your application stack at a lower cost per span.

Arize AI + Cekura: Two Tools, One Stack

Arize monitors your LLM backend across traces, evaluations, prompt optimization, and production monitoring. But it wasn't built for voice, so concurrent call simulation, ASR error detection, and production alerts on the voice layer aren't part of what it does.

Cekura was built for exactly that.

Most teams hit this right before launch, when the LLM backend looks fine but the voice layer hasn't been tested under real load. Running both means you catch that before it reaches users.

Use Arize when you need:

• Agent tracing and LLM evaluation across any framework
• Production monitoring with online evals and custom dashboards
• Compliance coverage (HIPAA, SOC2) for your AI backend

Use Cekura when you need:

• Pre-production testing:
  • Pre-production simulation of your voice and chat agent across hundreds of scenarios
  • A/B testing to compare multiple versions of your agent against the same call scenarios in one place
  • Automated multi-turn red teaming to stress-test against jailbreaks, bias, and adversarial attacks
  • Custom personas and accents, where you can test against Cekura's curated caller library or build your own with specific accents and background noise
• Production monitoring:
  • Production monitoring for latency, instruction-following, tool-call accuracy, and CSAT on live calls
  • Real-time Slack alerts for latency spikes and quality drops, so you find out before your callers do
• Pipeline & compliance:
  • QA runs in your CI/CD pipeline, triggered on prompt changes
  • Cron job scheduling to run tests on a recurring schedule and catch silent regressions between deployments
  • Predefined and custom metrics with built-in latency, instruction-following, and tool-call tracking, plus fully customizable LLM judges
  • Native integrations with Retell, VAPI, ElevenLabs, LiveKit, Pipecat, Bland, and more
  • SOC 2, HIPAA, and GDPR compliant transcript redaction, role-based access, and audit trails

Use both if you're shipping a voice AI product to production. Arize handles what's happening inside your LLM backend. Cekura handles how your voice layer holds up under real conditions. Together, they cover the full stack.

If you're already paying for Arize and need to cover the voice layer too, Cekura connects to your existing stack in under 15 minutes. Request a demo to see how it fits.

My Bottom Line on Arize AI Pricing

AX Free and Phoenix are worth using before you spend anything. AX Pro at $50/month works for small teams without compliance needs, but RAG workloads will hit overages faster than expected.

AX Enterprise at $60,000/year only makes sense if HIPAA, SOC2, and petabyte-scale performance are actual requirements rather than nice-to-haves.

Frequently Asked Questions

Does Arize AI Have a Free Plan?

Yes, Arize AI has two free options. AX Free is a managed cloud plan with 25,000 spans per month and 15-day retention. Phoenix is fully open-source and self-hosted with no usage caps.

How Much Does Arize AI Cost?

Arize AI starts at $50/month on AX Pro. Enterprise pricing is custom, with the median buyer paying $60,000/year, and there's no published tier in between.

What Is the Difference Between Arize Phoenix and Arize AX?

The main difference between Phoenix and AX is where they run. Phoenix is open-source and self-hosted with no usage limits but no managed features. AX is a cloud product with usage-based pricing, a full evaluation suite, and compliance options at the Enterprise tier.

Does Arize AI Charge Per Seat?

No, Arize AI doesn't charge per seat on AX Pro. Costs scale with span volume and data ingestion instead of headcount, making it more predictable than per-seat tools like LangSmith.

Does Arize AI Work With Cekura?

Yes, but they cover different layers of your stack. Arize monitors your LLM backend, covering traces, evaluations, and prompt performance.

Cekura covers what Arize can't, so if your product has a voice agent or chatbot, Cekura runs pre-production simulations and monitors live calls in production. Together, they cover the full stack.