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Toolradar
Expert GuideEditorially reviewed

Best AI Agent Testing Tools in 2026

TL;DR

Short answer: LangSmith is the PR gate when the agent is LangGraph. Plus is $39/seat/mo and includes 10,000 base traces, and a pytest file can fail the merge on the tool sequence. Maxim is the simulated-user suite: simulation runs start on Professional at $29/seat/mo, not on the free Developer plan. DeepEval is the free pytest library when you will pay the judge model yourself. Promptfoo Community is free, with a 10,000-probe red-team cap, and its paid plans publish no list price.

Fail the pull request when the agent calls the wrong tool, before a customer sees the loop.

·Updated
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43 AI Observability tools tracked

Buy the thing that fails a pull request, because a dashboard you open after the incident is a different product. An AI agent testing tool should mark a run pass or fail when the agent picks the wrong tool, skips a required step, or drops the task in a multi-turn conversation.

Toolradar data: of the 43 AI observability tools in the catalog, 58% offer a free or freemium plan, while 17 (40%) are paid-only.

That mix is why a free trace viewer and a paid simulation suite show up in the same search. A trace that you replay after launch belongs in agent observability. A score on a single answer, including RAG faithfulness, belongs in the AI evaluation guide. A chart of cost and latency belongs in LLM observability. This page is the regression suite you run before the merge.

Start with LangSmith when the agent is LangChain or LangGraph and the check is a trajectory against a reference tool sequence. Move to Maxim AI when a simulated user has to talk to the agent for several turns, and budget the seat that actually includes simulation runs. Use DeepEval when the suite should live in pytest and the only bill you accept is the judge model's API. Use Promptfoo when the same CI job should also red-team the agent, inside the Community probe cap.

How we ranked: these 10 were picked from the 43 tools in AI observability for pre-merge tests of multi-step agents (tool calls, trajectories, and simulated users). Every price was verified on the vendor's own page in September 2026, and nobody paid for a slot.

Top Picks

Picked by editorial review, informed by G2 and Capterra review volume and rating and by media mentions, the signals behind our category rankings. How we rate

Best AI Agent Testing Tools in 2026 compared: starting price, rating and best use, as of September 2026
ToolStarting priceRatingBest for
LangSmithPlus $39/seat/mon/aTeams whose agent is LangChain or LangGraph and who fail a pull request on the tool sequence
Maxim AIFrom $29/seat/mon/aTeams that need multi-turn simulations before the agent talks to a customer
DeepEvalFree, Apache 2.0n/aEngineers who want agent tests in pytest and will pay the judge model themselves
PromptfooFree, 10k probes/mon/aTeams that want one CI config for quality checks and a monthly red-team probe cap
Confident AIStarter $200/mon/aTeams that already run DeepEval and want shared simulations without a per-seat line
BraintrustPro $249/mo4.354 reviewsTeams that want every engineer in the experiment view without buying a seat
LangWatchGrowth $34/core-seat/mon/aTeams that want a simulated user in pytest and a per-seat plan with metered events
OpikPro $19/mon/aTeams that want suite-level assertions and a self-hosted install with no license fee
GalileoPro $100/mo yearlyn/aTeams that want named agent metrics now and can commit to yearly billing
LangfuseCore $29/mon/aTeams that want offline experiments in an open-source stack without a per-seat fee
1
LangSmith logo

LangSmith

Top Pick

Teams whose agent is LangChain or LangGraph and who fail a pull request on the tool sequence

LangSmith screenshot
+The docs ship a trajectory match against a reference message list, including tool calls, plus an LLM judge when you do not want a hard-coded path. Pytest with the LangSmith marker writes a pass or fail back to an experiment.
+Plus is the team plan in the table: unlimited seats, 10,000 base traces a month, then pay as you go. Developer stays free for 1 seat and 5,000 base traces, which is enough for one person and a small suite.
+Base traces are kept 14 days and extended traces 400 days. Tuned evaluators, in public beta for Plus and Cloud Enterprise in the US, are billed only when a run succeeds, so a skipped eval is not a charge.
−A second tester does not fit on Developer. That person is a Plus seat, and Enterprise (SSO, self-host, hybrid) publishes no list price, so a residency requirement leaves the card.
−The page prices a compute unit at $1.50 and a storage unit at $1.00, and it does not print how many traces sit in one storage unit. The upgrade from a 14-day trace to 400 days is an extra fee with no dollar on the page.
Good value

Plus is $39/seat/month with 10,000 traces and one free small serverless deploy.

Watch out

Traces over the included 5k/10k are pay-as-you-go. Seats are only the floor.

See LangSmith alternatives →
2
Maxim AI logo

Maxim AI

  • 4.8 on G2 (3 reviews)

Teams that need multi-turn simulations before the agent talks to a customer

Maxim AI screenshot
+Professional is the first plan whose card lists simulation runs and online evals. It includes unlimited seats, 3 workspaces, 100,000 logs, and 7-day retention, at the monthly seat price in the table, with a 14-day trial.
+The comparison grid caps datasets at 3 on Developer (100 entries), 10 on Professional (1,000 entries), and 30 on Business (10,000 entries). You can see the suite size before you import a transcript dump.
+Business, at $49/seat/mo, raises the log cap to 500,000, retention to 30 days, and adds scheduled runs, RBAC, and PII management. Paid log overage is $1 per 10,000 logs.
−Developer is free for 3 seats, 1 workspace, 10,000 logs, and 3-day retention, and the card does not include simulation runs. The grid also says that plan allows no log overage, so the free workspace stops instead of bursting.
−You pay the seat and the log cap at the same time. Five people on Professional are five seats before the first simulated turn, and a log past the included 100,000 is another line.
Good value

Maxim AI's pricing is fair, offering a generous free Developer tier.

Watch out

Log limits can lead to overage charges

See Maxim AI alternatives →
3
DeepEval logo

DeepEval

Engineers who want agent tests in pytest and will pay the judge model themselves

DeepEval screenshot
+ToolCorrectnessMetric compares tools called with an expected list. The default threshold is 0.5. You can require input parameters, outputs, call order, or an exact list, and a perfect binary score is available in strict mode.
+The getting-started guide for agents runs those checks through pytest and `deepeval test run`, including on a pull request. Component metrics can sit on a single tool-call span rather than only the final answer.
+The framework is Apache 2.0 and runs locally. Confident AI is optional. Their own docs treat the library and the cloud as separate products, so you can keep the suite without a seat.
−There is no platform price because there is no hosted suite in the library. Reports, shared datasets, and a regression baseline marked official require a Confident AI key, which is the next pick and a different bill.
−If you pass available tools, an LLM judges whether the choice was optimal, and that call is your model API. The deterministic name match is free. The optimality check is not.
See DeepEval alternatives →
4
Promptfoo logo

Promptfoo

Teams that want one CI config for quality checks and a monthly red-team probe cap

+Community is free and includes all LLM evaluation features, every model provider, a custom integration with your own app, local or self-hosted runs, and CI. A Python provider can call your own code, which is how an agent enters the suite.
+Red teaming is included up to 10,000 probes a month. The pricing page defines a probe as one request to the target during a red-team test, so a nightly attack suite has a number you can count.
+Vulnerability scanning sits on the same Community plan. You do not buy a second SKU to start looking for jailbreaks, as long as you stay inside that probe allowance.
−Enterprise and On-Premise publish no list price. Team sharing, SSO, continuous monitoring, and a managed cloud are on that quote, not on Community.
−The probe cap is the hard limit on the free attack suite. The page says Enterprise can buy more probes, and it does not print the rate, so a larger red-team program is a sales conversation.
Great value

The pricing for Promptfoo is very generous, especially with a robust free tier offering unlimited local evals and all features.

Watch out

No public overage pricing for Cloud

See Promptfoo alternatives →
5
Confident AI logo

Confident AI

Teams that already run DeepEval and want shared simulations without a per-seat line

+Starter is $200 per organization per month, with unlimited seats, 5 projects, and chat simulations. The metrics table lists 15 or more multi-turn DeepEval metrics for whole conversations, plus 30 or more single-turn metrics.
+The plan includes 5 GB-months of trace spans, then $1 per GB-month ingested or retained. Their calculator treats about 100,000 traces as 1 GB, so you can sketch the span bill before the first month.
+The judge line on Starter and Team is about $0.05 per million input tokens and $0.40 per million output tokens, and the page says it varies by model. Team is $2,000 a month for 75 GB-months, unlimited projects, and SOC 2.
−Free is 2 seats, 1 project, 5 test runs a week, and 1 GB-month. Additional test runs are locked and additional spans are dropped. Chat simulations are on the paid card, so the free week is not the simulation suite.
−AI red teaming is an Enterprise module, and that plan publishes no list price. A quality suite on Starter does not include the attack module. The jump from Starter to Team is the next organization fee, with no tier between them.
Good value

It's best for individual developers or small teams on the Free/Starter plans, scaling to larger enterprises with custom needs.

See Confident AI alternatives →
6
Braintrust logo

Braintrust

  • 4.3 on G2 (54 reviews)

Teams that want every engineer in the experiment view without buying a seat

+Starter is free, with unlimited users, projects, datasets, and experiments, $10 of model credits, 1 GB of processed data, 10,000 scores, and 14-day retention. A second engineer does not add a seat line.
+Pro is the platform fee in the table: $100 of credits, 5 GB included, 50,000 scores, 30-day retention, custom charts, and RBAC. Their scorers doc says agent checks should cover goal completion, and that a tool call can trigger its own scorer.
+Past the included data, Starter adds $4 per GB and Pro adds $3 per GB. Scores past the included block are $2.50 per 1,000 on Starter. Retention past 30 days on Pro is $0.50 per GB per month.
−SAML single sign-on is marked off Starter and Pro. It sits on Enterprise, which is custom pricing, so an identity-provider requirement leaves the self-serve card.
−The Pro score overage is $1.50 per 1,000 after 50,000 scores. A suite that judges every span, not one outcome per task, spends that line faster than a single-answer eval.
Good value

Braintrust's pricing is quite generous, offering a robust Free tier with unlimited evals and 3 users, which is excellent for individual developers or small teams.

Watch out

No clear overage fees mentioned for usage

See Braintrust alternatives →
7
LangWatch logo

LangWatch

Teams that want a simulated user in pytest and a per-seat plan with metered events

LangWatch screenshot
+The pricing table lists simulated users, multi-turn tests, a judge that can pass or fail any turn, and tool-call verification across long dialogues on every package. The same table lists pytest, vitest, and CI.
+Developer is free: 50,000 events a month, 14-day data access, 2 users, 3 scenarios, 3 simulations, and 3 custom evals. No card is required, and the open-source Scenario SDK is called out on the page.
+An event is an LLM call, a tool call, a retrieval, an evaluation, or a simulation step. One user turn can be several events, which is the meter you forecast, not a flat trace.
−Growth, the plan with 200,000 included events and unlimited simulations, is $34 per core seat a month, then $6 per 100,000 events and $4 per GB kept past 30 days.
−Developer stops at 3 simulations and 2 users. A fourth persona, or a third editor, is the paid plan. Self-host is available, and SSO, audit logs, and a support SLA are Enterprise, which is custom.
See LangWatch alternatives →
8
Opik logo

Opik

Teams that want suite-level assertions and a self-hosted install with no license fee

Opik screenshot
+The open-source plan is free and lists the full agent-testing set: tracing, test suites and assertions, and the Agent Playground. Comet says that build is the same codebase as the hosted versions.
+Free Cloud is free and the card lists 25,000 spans a month, 60-day retention, and up to 10 members, and it includes test suites. Pro is the price in the table: the card lists 100,000 spans, the same 60-day clock, and up to 50 members. A FAQ on that page also says every plan includes unlimited members, so confirm the seat cap before you invite the team.
+The test-suite rows cover item-level assertions, suite-level assertions that every case must pass, and an execution policy for how many runs have to succeed. Agent evaluation is listed for both a single step and the whole task.
−Extra spans on Pro are $5 per 100,000. Stretching retention from 60 days to 400 days is a separate fee per 100,000 spans on the same pricing page. A long review window is outside the platform fee.
−AI guardrails are marked for self-hosted deployment, and the cloud columns do not include them. SSO, HIPAA, and a custom region are Enterprise, which publishes no list price. Free Cloud and Pro list the US region.
Great value

Opik by Comet's pricing is extremely generous, offering a fully-featured Free tier that includes advanced capabilities like automated agent optimization and built-in guardrails.

Watch out

Potential overage fees for high usage

See Opik alternatives →
9
Galileo logo

Galileo

  • 3.0 on G2 (1 reviews)

Teams that want named agent metrics now and can commit to yearly billing

Galileo screenshot
+The free plan has no platform fee: 5,000 traces a month, unlimited users, and unlimited custom evals. Pro is the yearly price in the table, for 50,000 traces, standard RBAC, analytics, and Slack support.
+Galileo's April 13, 2026 post lists 9 agentic metrics, including Tool Selection Quality, Action Completion, Reasoning Coherence, and Agent Efficiency. That is a named agent score, not only a generic faithfulness metric.
+The same post describes Luna-2 models in 3B and 8B sizes for running metrics, and it says offline evals can become runtime protection. The pricing page is where you check which of those controls are on Pro.
−The Pro card says pricing scales with traces and shows a 33% saving for yearly billing. It does not print a month-to-month dollar, and it does not print the rate past 50,000 traces.
−Real-time guardrails, SSO, VPC or on-prem, and unlimited traces are Enterprise. That plan publishes no list price. A Pro order is the trace allowance and the RBAC line, not the blocking control.
See Galileo alternatives →
10
Langfuse logo

Langfuse

Teams that want offline experiments in an open-source stack without a per-seat fee

+Experiments via the SDK and the UI, plus LLM-as-a-judge evaluators, are marked on every cloud plan, including free Hobby. You can run a dataset against the agent before you buy a seat anywhere else.
+Core is the price in the table: 100,000 units, 90 days of data access, unlimited users, and 3 annotation queues. Hobby is free for 50,000 units, 30 days, 2 users, and 1 queue.
+A unit is a trace, an observation, or a score. Their own example puts 200,000 units on Core at $37 for the month: the plan fee plus $8 for the second 100,000. Past that, the rate steps from $8 per 100,000 to $7, then $6.50, then $6.
−Pro is $199 a month and still includes 100,000 units. You are paying for 3-year access, 50 alerts, SOC 2 and ISO 27001 reports, and a HIPAA-ready region, not for a larger included test allowance. SSO is the Teams add-on, not part of Pro.
−Because a score is a unit, a heavy judge suite spends the allowance the same way production traffic does. Self-hosting the open-source build avoids that meter and leaves you the upgrades. This is a dataset runner, not a simulated-user studio. For the chart after launch, see Langfuse alternatives.
Good value

Langfuse's pricing is quite generous, especially with a robust free Hobby tier offering 50k observations.

Watch out

Overage fees not explicitly stated for Pro tier

See Langfuse alternatives →

What an AI agent testing tool actually is

An AI agent testing tool runs the agent against a case you defined, then returns pass or fail. The case is a tool sequence, a task outcome, or a conversation with a simulated user. If the product only stores the trace and never fails a build, it is a log.

A trajectory check suits a workflow you can write down. LangSmith documents a trajectory match against a reference message list, including tool calls, and a pytest plugin that records pass or fail. DeepEval scores tool names against an expected list, and can also require input parameters and call order. Opik ships test suites with item-level and suite-level assertions on every plan, including the open-source build.

A simulated user suits a support or sales agent whose next turn depends on what the user says. Maxim AI puts simulation runs on the paid Professional plan. LangWatch lists simulated users, multi-turn tests, and tool-call checks on every package, then caps the free Developer plan at 3 simulations. Confident AI lists chat simulations on the organization plan in the pricing table, not on the free limits.

A red-team pass suits an agent that can call tools with side effects. Promptfoo includes vulnerability scanning on Community and meters red teaming in probes. Blocking a dangerous action in production is a different purchase, covered in LLM security. The framework you build the agent in is covered in agent frameworks.

Why the free plan often omits the test

The expensive mistake is adopting the free tier and discovering the simulation, the second seat, or the longer trace is a paid line. LangSmith Developer is one seat and 5,000 base traces a month. A second person who needs to read the failed pytest is a Plus seat. Base traces are kept 14 days. Extended traces are kept 400 days, and the pricing page describes an extra fee for that upgrade without printing the dollar. Storage and traces are also metered in LangChain Storage Units at $1.00 each, and compute units are $1.50.

Maxim's Developer plan allows 3 seats, 10,000 logs, and 3 days of retention, and the plan card does not include simulation runs. Those runs, plus online evals, are on Professional. Log overage on the paid plans is $1 per 10,000 logs, and Developer does not allow overage at all. A weekend load test that crosses the free log cap stops, rather than billing you.

Confident AI's free organization is 2 seats, 1 project, 5 test runs a week, and 1 GB-month of trace spans. Extra test runs are locked, and extra spans are dropped. Chat simulations are listed on the paid organization plan. LangWatch's free Developer plan includes 50,000 events, 2 users, and 3 simulations. Growth, the plan with unlimited simulations, is $34 per core seat a month, with events past 200,000 at $6 per 100,000.

Langfuse bills a unit for a trace, an observation, or a score, so a test that writes a score spends the same allowance as a production span. Hobby includes 50,000 units and 1 annotation queue. The wider catalog of these products is AI observability. If you are choosing the agent framework at the same time, start from agent frameworks and then attach the suite.

Key Features to Look For

  • A pass or fail on the tool call (Essential)

    LangSmith's trajectory match and DeepEval's ToolCorrectnessMetric both compare the tools the agent called with a list you wrote. A score with no threshold does not block the merge.

  • A CI command your repo already runs (Essential)

    DeepEval's test run, LangSmith's pytest marker, Promptfoo's CI row on Community, and LangWatch's pytest and vitest adapters are the gate. A notebook you remember to open is not.

  • A simulated user with a cap you can see (Essential)

    Maxim sells simulation runs on Professional. LangWatch includes them on every package and then limits Developer to 3 simulations. Confirm the cap before you demo a hundred personas.

  • A judge bill that is separate from the seat (Essential)

    DeepEval is free and the model API is yours. Confident AI prints about $0.05 per million input tokens and $0.40 per million output tokens for its judge, and says the rate varies by model.

  • A retention window that covers the review (Important)

    LangSmith base traces last 14 days. Maxim Developer lasts 3 days, Professional 7, Business 30. Braintrust Starter lasts 14 days and Pro lasts 30. A bug filed next week needs the longer clock.

  • A second seat that is priced on purpose (Important)

    LangSmith Developer is 1 seat. Confident AI's paid plans are unlimited seats on an organization fee. Braintrust Starter and Pro both say unlimited users. A per-seat tool and a flat tool are not the same budget.

  • A place the transcripts are allowed to sit (Important)

    LangSmith cloud is US or EU, and self-host is Enterprise. Langfuse Cloud offers US, EU, or Japan. Opik's free and Pro cloud cards list a US region, and Enterprise is custom. Read that before you paste customer chats into the suite.

  • A red-team probe cap next to the quality suite (Nice to have)

    Promptfoo Community includes 10,000 probes a month and CI. Confident AI lists the red-teaming module on Enterprise, which publishes no list price. Quality tests and attack tests are often different plans.

What to settle before the demo

  1. Write the failure you need to catch. A wrong tool name is a trajectory or ToolCorrectness check. A wandering support chat is a simulated user. A jailbreak is a probe. LangSmith, DeepEval, and Opik start at the first. Maxim and LangWatch start at the second. Promptfoo publishes the third as a probe cap.

  2. Count seats against the free plan before you compare stickers. LangSmith Developer is 1 seat. LangWatch Developer is 2 users. Confident AI Free is 2 seats. Maxim Developer is 3 seats and still omits simulation runs. Braintrust and Galileo both say unlimited users on the free plan.

  3. Ask whether a score spends the same meter as a trace. Langfuse counts scores as units. Braintrust sells scores as their own line, 10,000 included on Starter. Opik counts spans, and a tool call is a span.

  4. Decide how long the failed transcript has to exist. Three days on Maxim Developer, seven on Maxim Professional, and fourteen on a LangSmith base trace are different review habits. If legal wants the text for a quarter, you are on a higher tier or a self-hosted build before the logos matter.

  5. Separate the test suite from the production chart. Replaying a live trace is agent observability. Failing a pull request is this list. Buying one product and expecting both jobs is how teams pay for a log.

Evaluation Checklist

  • On LangSmith, run one pytest with a reference trajectory and confirm the experiment shows a pass or fail, then check whether that trace is a 14-day base trace or you turned on the longer retention.

  • On Maxim, open a Developer workspace and confirm simulation runs are absent, then price one Professional seat against the number of people who must click the run.

  • On DeepEval, assert ToolCorrectnessMetric against a golden tool list, including call order if the sequence matters, and confirm the judge model is an API key you already pay.

  • On Promptfoo, run the Community eval in CI against your agent and count probes before you assume the 10,000 monthly red-team allowance covers a nightly attack suite.

  • On Confident AI, spend the 5 weekly test runs on purpose and confirm chat simulations are on the paid organization plan you were shown.

  • On LangWatch, create a fourth simulation on Developer and confirm it is blocked, then price Growth per core seat plus events past 200,000.

  • On Opik, write one suite-level assertion that every case must pass, and decide whether you are on the open-source install, Free Cloud's 25,000 spans, or Pro's 100,000 spans.

Pricing Overview

Free libraries and CLIs

DeepEval, Promptfoo Community, and the Opik open-source build.

No platform fee

Seat or organization fees

LangSmith Plus, Maxim Professional, and Confident AI Starter.

Monthly seat or a flat organization price

Usage meters and yearly cards

Opik Pro, Braintrust Pro, Galileo Pro, and Langfuse Core.

Spans, scores, traces, or a yearly display price

Pricing Comparison

Best AI Agent Testing Tools in 2026 pricing comparison, as of September 2026
ToolPublished priceWhat that price buysBilling

LangSmith

Plus $39/seat/mo

10,000 base traces, then pay as you go. Developer is free: 1 seat, 5,000 base traces.

Per seat, plus usage

Maxim AI

Professional $29/seat/mo

Simulation runs, 100,000 logs, 7-day retention. Business is $49/seat/mo for 500,000 logs.

Per seat, monthly

DeepEval

Free framework

Apache 2.0. Tool checks and pytest. The judge model is your own API bill.

No platform fee

Promptfoo

Free Community

All eval features and CI. Red teaming is 10,000 probes/mo. Enterprise publishes no list price.

Free, then a quote

Confident AI

Starter $200/mo

Chat simulations, unlimited seats, 5 projects, 5 GB-months, then $1 per extra GB-month.

Per organization

Braintrust

Pro $249/mo

5 GB, 50,000 scores, 30-day retention, unlimited users. Starter is free.

Monthly platform fee

LangWatch

Growth $34/core-seat/mo

Developer is free: 50,000 events, 3 simulations, 2 users. Growth includes 200,000 events, then $6 per 100,000.

Per core seat, plus events

Opik

Pro $19/mo

100,000 spans, up to 50 members, test suites. Then $5 per extra 100,000 spans.

Monthly, plus spans

Galileo

Pro $100/mo yearly

50,000 traces, RBAC, Slack. Free is 5,000 traces. Month-to-month is not printed.

Billed yearly

Langfuse

Core $29/mo

100,000 units, 90-day access, experiments and LLM-as-a-judge. Hobby is free.

Monthly, plus units

Prices were verified on each vendor's pricing page on September 24, 2026. Promptfoo Enterprise, LangSmith Enterprise, and Galileo Enterprise publish no list price. Single-answer scoring sits in the AI evaluation guide.

Mistakes to Avoid

  • ×

    Treating a trace viewer as a test. If the pull request can merge while the agent calls the wrong tool, you bought a log. LangSmith's pytest marker and Opik's suite-level assertion are the checks that can fail the job.

  • ×

    Demo-ing Maxim simulations on a Developer account. The free card is 3 seats and 10,000 logs. Simulation runs are listed on Professional, and that plan is a seat plus a log cap.

  • ×

    Assuming DeepEval's cloud reports are free because the library is free. Official regression baselines on Confident AI need an API key, and the free cloud tier locks runs after 5 a week.

  • ×

    Counting Promptfoo probes as if they were eval rows. A probe is one red-team request. A quality eval and a 10,000-probe attack budget are different lines on the same Community plan.

  • ×

    Budgeting LangWatch Growth as a flat seat price. Events past the 200,000 included are metered on top of each core seat.

  • ×

    Letting every span write a Langfuse score and then forecasting the bill as if only user-facing traces counted. Scores are units, and the included block on Core is the same 100,000 as on the higher platform fees.

Expert Tips

  • →

    Write one golden trajectory for the happy path and one for the refusal before you add a judge. LangSmith's match evaluator and DeepEval's name check are deterministic. Add the model only where the wording can vary.

  • →

    Put the CI command in the same pull request as the agent change. DeepEval's test run, Promptfoo's Community CI row, and LangWatch's pytest adapter are useless if they run on a laptop the night before launch.

  • →

    Cap simulated users on the first week. LangWatch Developer allows 3. Maxim Developer includes simulation in the playground but not simulation runs, which start on Professional. A hundred personas on day one is how the seat plan arrives before the rubric does.

  • →

    Sample production failures into the dataset, then keep the suite small enough to run on every pull request. Langfuse and Confident AI both describe turning traces into datasets. A suite that takes an hour will be skipped.

  • →

    Split the red-team job from the quality job when the probe cap is the constraint. Promptfoo Community is 10,000 probes a month. Confident AI's red-team module is Enterprise. Do not pretend the quality plan includes both.

Red Flags to Watch For

  • !

    A LangSmith workspace with online evaluators left on, because the pricing FAQ says you pay when a tuned evaluator runs successfully, and a quiet schedule becomes a compute bill on top of the seat.

  • !

    A Maxim order that quotes the free Developer plan after a demo of simulation runs. Those runs are on Professional, and Developer does not allow log overage.

  • !

    A Confident AI pilot that treats 5 test runs a week as a team suite. Extra runs are locked, and extra trace spans on that free tier are dropped.

  • !

    A Promptfoo Enterprise quote with no probe number. Community stops at 10,000 probes a month, and the paid plans publish no list price.

  • !

    A LangWatch Growth budget that counts seats only. Events past 200,000 are $6 per 100,000, and storage past 30 days is $4 per GB.

  • !

    A Galileo Pro conversation that assumes real-time guardrails are on the yearly card. The pricing page puts real-time guardrails on Enterprise, which publishes no list price.

The Bottom Line

Choose LangSmith when the agent is LangGraph and the gate is a trajectory in pytest, on the Plus seat in the table if more than one person must see the failure. Choose Maxim when the test is a simulated conversation, and do not budget Developer for that, because simulation runs start on Professional.

Choose DeepEval when the suite should stay in the repo and the platform fee should be zero. Choose Promptfoo when the same CI config should red-team the agent inside 10,000 probes, and treat Enterprise as a quote. Choose Confident AI when the team wants chat simulations on one organization fee. Choose LangWatch when the simulated user matters most, and budget the core seat plus events past 200,000.

Choose Opik when you want assertions on a free self-hosted build. Choose Braintrust when unlimited users matter more than a low platform fee. Choose Galileo when you want the named agent metrics and can pay the yearly card, and buy guardrails only after Enterprise prints a price. Choose Langfuse when the job is a dataset experiment and you can count scores as units. Cite this: Toolradar, "Best AI agent testing tools 2026", September 2026.

Frequently Asked Questions

What is the best AI agent testing tool in 2026?

LangSmith is the best default when the agent is LangChain or LangGraph and you can fail a pull request on a reference tool sequence. The team plan is the Plus row in the pricing table. Maxim is the better default when the test is a simulated multi-turn user, because simulation runs start on Professional, the seat row in that same table, and they are absent from the free Developer card. DeepEval is the best default when you want the check inside pytest and will not pay a platform fee. Promptfoo Community is the best default when the same job includes red teaming, up to 10,000 probes a month.

How much does AI agent testing cost?

Platform fees verified on September 24, 2026 run from a free library to a few hundred dollars a month. LangSmith Plus is $39 per seat. Confident AI Starter is $200 per organization. Braintrust Pro is $249 a month. Opik Pro is $19 a month for 100,000 spans. Galileo Pro is $100 a month when billed yearly. Maxim Professional is the seat that includes simulation runs, and Langfuse Core is the unit plan that includes experiments. Both of those monthly fees are printed in the comparison table. Promptfoo's paid plans publish no list price, and LangWatch Growth is $34 per core seat a month plus metered events. Judge-model tokens are extra on DeepEval, because the library itself has no platform fee.

Is there a free AI agent testing tool?

Yes. DeepEval is an Apache 2.0 library with no platform fee. Promptfoo Community is free, including CI, with red teaming capped at 10,000 probes a month. Opik's open-source build includes test suites and assertions. LangSmith Developer is free for 1 seat and 5,000 base traces. Langfuse Hobby is free for 50,000 units. The catch is the missing feature: Maxim's free Developer plan does not list simulation runs, Confident AI's free tier allows 5 test runs a week, and LangWatch's free plan allows 3 simulations.

How is agent testing different from LLM evaluation?

LLM evaluation scores one answer, often for faithfulness or relevance. Agent testing scores a sequence: which tool was called, whether the arguments matched, and whether a multi-turn task finished. DeepEval's tool metric and LangSmith's trajectory match are the second kind. The AI evaluation guide covers the single-answer and RAG suites. This page is the pull-request gate for the agent loop. Production replay, after the merge, is agent observability.

LangSmith or Maxim for agent tests?

Use LangSmith when you already have a reference trajectory and a LangGraph app. Developer is one free seat and 5,000 base traces, Plus is the per-seat row in the pricing table, and pytest can record the pass. Use Maxim when a simulated user has to carry the conversation. Simulation runs are on Professional, and the free Developer plan stops at 3 seats, 10,000 logs, and 3 days of retention. If you need both a hard tool check and a persona, run the trajectory in LangSmith and the personas in Maxim, because the two products meter different work.

Does Promptfoo test agents or only red-team prompts?

Community includes all LLM evaluation features, a custom integration with your own app, and CI, so an agent can be the target through a Python provider or an HTTP call. Red teaming is a separate meter on that same free plan: 10,000 probes a month, where a probe is one request to the target. Team dashboards, SSO, and continuous monitoring are Enterprise, which publishes no list price. Prompt injection blocking in production is covered in LLM security, not by the CLI alone.

How do I fail a pull request when an agent calls the wrong tool?

Pick a check that returns pass or fail inside CI. LangSmith's pytest integration logs a trajectory, including tool calls, and stores the pass rate. DeepEval's ToolCorrectnessMetric compares the tools called with an expected list, and deepeval test run is the command the workflow doc puts in CI. Opik's suite-level assertions are written so every case must pass. A trace viewer that never exits non-zero will not stop the merge. Prompt versioning around those checks is a separate layer, covered in prompt management.

Cite this page: Toolradar, "Best AI Agent Testing Tools in 2026", updated September 2026, https://toolradar.com/guides/best-ai-agent-testing-tools

Sources

Prices and plan details on this page come from each vendor's own pricing page, re-checked by the Toolradar pricing tracker:

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