| Quick answer |
|---|
| The best real-time analytics tools for AI inference are LangSmith at $39 per seat a month for 10,000 base traces, Langfuse for MIT-licensed self-hosting, and Arize Phoenix, free to self-host and OpenTelemetry-native. Helicone covers 10,000 requests a month free through a proxy. |
| How we compare |
|---|
| Judged on what each tool captures per request, on published plan limits, on licence, and on whether self-hosting is genuinely free. Every figure was read off the vendor pricing pages linked below in September 2026, and where a vendor publishes no price that is stated rather than estimated. Every price was re-checked against the vendor’s own pricing page in September 2026, and figures available only from third-party trackers are marked as reported. No vendor paid for placement. We did not run a head-to-head latency or accuracy benchmark. |
Table of Contents
What real-time analytics means for AI inference
For an inference workload, real-time analytics means four signals captured per request: latency, token counts, cost and output quality. The first three are mechanical. The fourth is the reason this category exists as something separate from ordinary application monitoring. For turning numbers into charts, see our guide to AI data visualization tools. Teams that also need alerting and incident response should read our guide to AI ops tools.
A conventional APM tool will tell you a request took 4.2 seconds and returned HTTP 200. It cannot tell you the answer was fluent, confident and wrong. LLM observability tools capture the prompt, the response, the retrieved context and an evaluation score alongside the timing data, so a nested agent call can be reconstructed end to end. Our explainer on AI hallucinations covers why that quality signal cannot be inferred from status codes.
Best real-time analytics tools for AI inference compared
| Tool | Free tier | Paid entry | Licence and hosting |
|---|---|---|---|
| LangSmith | 5,000 base traces/mo, 14-day retention | $39/seat/mo, 10,000 base traces | Managed; enterprise self-host |
| Langfuse | Hobby: 50,000 units/mo | From ~$29/mo cloud | MIT, free self-host |
| Arize Phoenix | Unlimited self-hosted | Arize AX Pro $50/mo, 50,000 spans | Elastic Licence 2.0, OTLP native |
| Braintrust | ~1 GB and 10,000 scores | Pro from $249/mo | Managed |
| Helicone | 10,000 requests/mo, 7-day retention | Pro $79/mo, Team $799 | Proxy; self-host available |
| Weights and Biases Weave | Free tier available | Pro from $60/mo | Managed |
Pick on instrumentation model, not on features
Feature lists in this category converge fast — everything traces, everything scores. The durable difference is how the data gets in, and that decision is expensive to reverse.
- Proxy (Helicone) — change a base URL and you are collecting. Fastest to adopt, but a new hop in the request path and thinner visibility into nested agent steps.
- SDK (LangSmith, Langfuse, Braintrust) — wrap calls in application code. More work, far better structure for multi-step agents.
- OpenTelemetry (Arize Phoenix, and OTLP ingestion elsewhere) — emit standard OTLP spans, defined by the vendor-neutral OpenTelemetry specification. The most portable option, because switching backends later becomes a config change rather than a rewrite.
If you have no strong opinion yet, instrument with OpenTelemetry. It is the only choice on this list that does not lock your traces to one vendor, and for teams running multi-agent systems the nested-span model matches the architecture directly.
The six tools in detail
LangSmith
LangSmith is the default choice for teams already on LangChain. The Developer free tier covers up to 5,000 base traces a month on a single seat; Plus is $39 per seat per month for up to 10,000 base traces, with pay-as-you-go beyond that and custom Enterprise above it. Base traces are kept for 14 days on both plans, and 400-day retention is a paid extra rather than a plan upgrade.
Langfuse
Langfuse is MIT-licensed open source with a genuinely free self-hosted deployment via Docker Compose on Postgres, with optional ClickHouse storage. The Hobby cloud tier covers 50,000 units a month, where a unit is any tracing data point; Core is $29 a month with 90 days of data access, and Pro $199 with three-year retention.
Arize Phoenix
Arize Phoenix is free to self-host under the Elastic License 2.0 and OpenTelemetry-native, accepting traces over standard OTLP. Strongest on drift detection and RAG pipeline quality, with pre-built LLM evaluation templates. Arize AX is the managed tier: free for 25,000 spans with 15-day retention, then Pro at $50 a month for 50,000 spans and 30 days.
Braintrust
Braintrust is evaluation-first rather than tracing-first. A free tier covers roughly 1 GB of data and 10,000 scores; Pro starts at $249 a month. Worth the jump when systematic experiment comparison, not incident debugging, is the main job.
Helicone
Helicone is the lowest-friction option: a proxy that captures requests with a one-line change, free for 10,000 requests a month with seven days of retention; Pro is $79 a month and Team $799. Best for cost and latency analytics when you do not want to instrument application code.
Weights and Biases Weave
Weights and Biases Weave puts tracing and evaluation inside the wider Weights and Biases platform, with a free tier available. Makes most sense for teams already running experiment tracking there; the Pro plan starts at $60 a month for teams under 50 employees.
How long each free tier actually lasts
Free allowances are published as monthly totals, which tells you nothing about whether they survive your traffic. Convert them into time instead. One request a minute is a modest production load: 1,440 a day, or 43,200 across a 30-day month. Here is how long each published free tier lasts at that rate, using September 2026 figures.
| Free tier | Published allowance | Arithmetic at 1,440 a day | Runs out after |
|---|---|---|---|
| LangSmith Developer | 5,000 base traces / month | 5,000 ÷ 1,440 | 3.5 days |
| Helicone free | 10,000 requests / month | 10,000 ÷ 1,440 | 6.9 days |
| Braintrust free | ~10,000 scores / month | 10,000 ÷ 1,440 | 6.9 days |
| Langfuse Hobby | 50,000 units / month | 50,000 ÷ 1,440 | 34.7 days |
| Arize Phoenix, self-hosted | no published ceiling | — | does not |
Only two of the five survive a single request per minute for a whole month, and one of those is the one you host yourself. That reframes the choice: for anything past a prototype, the free tiers on the managed products are trial credits rather than a plan, and the self-hosted options are the only genuinely free path at production volume.
The paid step is worth dividing out too. LangSmith Plus is $39 per seat for 10,000 included base traces, or 39 ÷ 10 = $3.90 per 1,000 traces. Langfuse Core is $29 for 100,000 units, or 29 ÷ 100 = $0.29 per 1,000 units. Do not read that as a 13× gap: one multi-step agent run is a single LangSmith trace but several Langfuse units, so the real difference depends on how many steps your agent takes. Count the steps in one typical run before you choose.
What retention actually costs you
Trace ceilings get the attention in pricing pages; retention windows decide the bill. LangSmith keeps base traces for 14 days on the free Developer tier and on Plus; longer retention is sold as extended traces at 400 days rather than bundled into the higher plan. A 14-day window cannot support a quarterly regression comparison, which is exactly the analysis you need when a model provider silently updates a version behind an endpoint.
Full request and response payloads are also large, so retention drives storage more than request count does. This is the strongest argument for self-hosting Langfuse or Phoenix: you decide what to keep and for how long, and the cost lands on infrastructure you already run. That path pairs naturally with an open-source model you host yourself, and our guide to running AI models offline covers the deployment side. For teams still choosing a model provider, our comparison of AI APIs covers the pricing side of inference itself, and our ranking of the leading AI models compared head to head covers which one to point the traffic at.
Frequently Asked Questions
What are the best real-time analytics tools for AI inference?
LangSmith is the best real-time analytics tool for AI inference on managed infrastructure, at $39 per seat a month for 10,000 base traces, and Langfuse is the best self-hosted option under an MIT licence. Arize Phoenix is free to self-host, and Helicone captures cost and latency with a one-line proxy change.
What does evaluation tooling cost at production volume for AI inference teams?
Published entry pricing gives the shape: LangSmith Plus is $39 per seat a month for 10,000 base traces with pay-as-you-go above that, Braintrust Pro starts at $249 a month, and Langfuse Core is $29 a month for 100,000 units. At high volume the deciding cost is usually retention rather than ingestion, since storing months of full request and response payloads is what makes the bill move. Self-hosting Langfuse or Phoenix converts that into infrastructure spend you control.
Do you need a dedicated eval tool for AI inference teams if you already log traces?
Often not at first. If you already capture prompts, outputs, latency and token counts, you have the observability half. A dedicated evaluation tool such as Braintrust earns its place when you need to compare two prompt or model versions on the same dataset and get a defensible verdict — the workflow generic logging cannot express. Start with tracing, add evaluation when you are shipping changes faster than you can eyeball them.
How do you evaluate LLM output without ground-truth labels for AI inference teams?
Four approaches work without labels. LLM-as-judge scores outputs against a written rubric. Pairwise comparison asks which of two versions is better, which is more reliable than absolute scoring. Reference-free checks validate structure — does the JSON parse, is every claim grounded in the retrieved context. Online signals such as retry rate, thumbs-down rate and conversation abandonment give real user feedback. Combine at least two, and sample a slice for human review to keep the judge honest.
How much do real-time AI inference analytics tools cost?
There is a free path at every level: LangSmith Developer covers 5,000 traces a month, Langfuse Hobby covers 50,000 units, Helicone covers 10,000 requests, and both Langfuse and Arize Phoenix are free to self-host under open licences. Paid entry points published in September 2026 are $29 a month for Langfuse Core with 100,000 units, $39 per seat for LangSmith Plus with 10,000 base traces, and $249 a month for Braintrust Pro.
Conclusion
Start free and instrument early. Helicone gets cost and latency data flowing in an afternoon, Langfuse Hobby covers 50,000 units a month, and Arize Phoenix is free to self-host indefinitely. None of that requires a purchasing decision.
Upgrade on a specific trigger, not on a calendar. Move to LangSmith Plus when retention blocks an investigation you need to run, and add Braintrust when you are shipping prompt and model changes faster than a human can review them. Both are answers to problems you will recognise when they arrive.
