Compare·LLM observability and gateway
Continuum
Multi-agent workbench
VS
Helicone
LLM observability and gateway

Continuum vs Helicone

Instrument the app you built, or instrument and control the agents your team runs.

Helicone is open-source LLM observability with a gateway attached. The main repository is Apache 2.0 with 6,085 GitHub stars, and the separate AI Gateway project is GPL-3.0 with 622 stars, advertising 100+ providers behind one OpenAI-compatible interface at a P95 under 5ms, roughly 64MB of memory, around 3,000 requests per second, and a 30MB binary. Its routing strategies are specific: model latency routing, provider latency routing using P2C with PeakEWMA, weighted distribution, and cost optimization, with Redis and S3 caching, rate limiting per user, per team, or globally, and OpenTelemetry tracing. Cloud pricing is Hobby free with 10,000 requests, 1GB of storage, one seat, and 7-day retention; Pro at $79 per month with unlimited seats, alerts, reports, the HQL query language, and 1-month retention; Team at $799 per month adding five organizations, SOC-2 and HIPAA, dedicated Slack support, and 3-month retention; and custom Enterprise with SAML SSO and on-premises deployment. Continuum answers a different question. It is the free workbench where Claude Code, Codex, Cursor, Grok, and OpenCode run under your own subscriptions in isolated git worktrees, with plan gates, diff and PR review, live quota gauges, weekly spend caps, and cost by repo, provider, model, and day across the machines a team actually codes on.

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Workflow Monday path Matrix Decide Money FAQ

Updated 2026-08-03 · Mac stable · Win/Linux desktop beta

Choose Continuum when

Pick Continuum when the thing to observe and control is coding-agent spend across a team's machines: quota gauges, weekly caps, model policy, member approvals, and cost by repo, with worktree isolation and review gates in the same product.

Choose Helicone when

Pick Helicone when you are running an LLM application in production and need request-level observability, sessions, prompt management, evaluation, caching, and a fast self-hostable gateway (GPL-3.0).

Snapshot adjacent job
Dimension Continuum Helicone
Question answered What do our coding agents cost and who approved them How is our LLM app behaving per request
Subject Agents on engineers' machines Requests from your production application
Cost axis Repo · provider · model · day Request, session, user, and model
Control Model policy · weekly caps · member approvals Rate limits, caching, routing at the gateway
Sees subscription work Yes, from local agent logs No, only traffic routed through it
Licensing Free packaged app Apache 2.0, 5.8K stars; gateway Apache, 622 stars
Price Free app · optional hosted tiers Free Hobby · $79 Pro · $799 Team · custom
Mac stable · web · iPhone · Watch · Win/Linux desktop beta · free app
01

Observe an app vs govern agents

In Continuum

Find out what the team's agents actually cost

Week 1

Engineers install Continuum and keep working in worktree sessions under the subscriptions they already had. Nothing is proxied and no keys move.

Week 2

Cost by repo, provider, model, and day shows two repositories carrying most of the spend, including subscription work no gateway could have seen.

Week 3

An admin sets a weekly spend cap and a model policy, and turns on member approvals for new joiners.

Week 4

Live quota gauges become the scheduling signal: batches launch when the window has headroom instead of stalling halfway.

In Helicone

Instrument a production LLM feature

Day 1

Add the integration to the app and start logging on the free Hobby tier: 10,000 requests, 1GB, 7-day retention.

Day 3

Use sessions and user views to trace a bad output back through the exact prompt that produced it.

Day 10

Retention becomes the constraint, so Pro at $79 per month buys unlimited seats, alerts, reports, HQL, and a month of history.

Day 20

Self-host the Apache-licensed AI Gateway for routing and caching, and export traces through OpenTelemetry into the existing stack.

02

Monday path

Monday with two very different telemetry questions

Install, connect, first session - steps you can run the same day.

01

State the question. If it is how our production feature behaves per request, that is Helicone. If it is what our engineers' coding agents cost and whether they are supervised, that is Continuum.

02

For the app: start on Helicone's free Hobby tier, 10,000 requests with 7-day retention, and confirm the one-line integration works against your real client.

03

Check whether 7-day retention is enough for the debugging you actually do; Pro at $79 per month moves it to one month and Team at $799 moves it to three.

04

If routing matters too, self-host the Apache-licensed AI Gateway and test the P2C with PeakEWMA provider routing and Redis or S3 caching under real load.

05

For the agents: install Continuum on the machines where the work happens and start two worktree sessions under existing subscriptions.

06

Set a weekly spend cap and a model policy at the org level, add a member approval, then read cost by repo, provider, model, and day at the end of the week.

07

Compare the live quota gauges against what the team assumed their subscription windows allowed. That gap is usually the finding.

08

Do not force one tool to answer both questions. Request-level app telemetry and per-repo agent spend are different datasets with different owners.

How Continuum measures agents without a proxy

How Continuum measures and controls agent work

  • Cost is reconstructed locally from each agent's own logs and priced by repo, provider, model, and day, so no request has to be proxied to be counted.
  • That is what lets subscription work be visible at all, since Claude Code or Codex running on a seat never sends a metered API call through anything.
  • Live gauges poll each provider's own rate-limit window, showing headroom before a batch stalls halfway through.
  • Org controls apply at the account layer: model policy, weekly spend caps, and member approvals across the team.
  • Each managed session gets its own git worktree and branch, so what an agent did is attributable to a branch and a diff, not only to a token count.
  • Plan mode is read-only until a human approves, and the diff pane supports per-hunk stage, revert, and commit before a pull request opens.
  • Optional hosted inference adds an OpenAI-compatible endpoint and an Anthropic-compatible bare origin with cont_sk_ keys and an auto model router, priced as a flat monthly tier.
03

Observability and workbench matrix

Cells use product nouns on both sides. Continuum is the multi-provider workbench; they win where their loop is the product.

Capability Continuum Helicone
Coding-agent workbench Mac, iPhone, Watch, web, Windows and Linux beta Observability platform and gateway, not a workbench
Per-session git worktree and branch Isolation before the first edit No repository layer
Plan approval, diff review, PR merge Plan gate, per-hunk review, PR in session Out of scope
Request-level LLM tracing Session transcripts and token rollups, not request traces Dashboard, sessions, users, alerts, and OpenTelemetry tracing
Prompt management, datasets, playground Not an application development surface Listed as core platform features
Open source Free packaged app, not an open-source platform Apache 2.0 main repo, 5.8K stars; Apache gateway repo, 622 stars
Self-hostable Agents run on hosts you enroll; the app is not a server you deploy Gateway self-hosts via Docker; Enterprise offers on-premises
Gateway routing and failover Auto model router on optional hosted inference Model latency, provider P2C with PeakEWMA, weighted, and cost routing
Caching and rate limiting Provider-native caching inside sessions; caps are per org and week Redis and S3 caching, limits per user, team, or global
Sees subscription-based agent spend Priced from local agent logs with no proxy Only traffic that passes through the gateway is observed
Cost attributed to a git repository Repo, provider, model, and day Cost by request, session, user, and model
Team spend limits set by an admin Weekly spend caps, model policy, member approvals Rate limits and gateway policy rather than org spend caps
Free tier that covers real use The whole app, running on your own subscriptions Hobby is 10,000 requests, 1GB, one seat, 7-day retention
04

Where the two telemetry stories split

01 · Subject

Your application versus your engineers.

Helicone observes requests your product makes to a model. Continuum observes and governs what coding agents do on the machines your team codes on. Those are different datasets with different owners, and a dashboard built for one reads as noise to the other.

02 · The blind spot

Subscription agent work never reaches a gateway.

Claude Code on a Max seat, Codex under a ChatGPT plan, Cursor under its own subscription: none of that traffic passes through a proxy, so a gateway-based observability tool cannot report on it. Continuum prices local agent logs instead, which is the only way that spend becomes visible without changing how the agents authenticate.

03 · Control

Rate limits versus approval gates.

Helicone's controls are the ones a request boundary allows: caching, rate limiting per user, team, or globally, and routing between providers. Continuum's are the ones a workbench allows: a read-only plan that a human must approve, per-hunk diff review, weekly spend caps, model policy, and member approvals. Both are real governance; they act on different objects.

04 · Ownership

Open source is a genuine advantage, and it is not free to run.

Helicone's main repository is Apache 2.0 and the AI Gateway is GPL-3.0, and the gateway is deliberately small: a 30MB binary, roughly 64MB of memory, around 3,000 requests per second, P95 under 5ms. If self-hosting is the requirement, that is a strong answer. It still means someone owns a deployment, which is the cost Continuum does not ask you to pay because there is no server in the request path.

05 · Retention

Read the retention row before comparing prices.

Hobby keeps 7 days, Pro at $79 per month keeps one month, and Team at $799 per month keeps three. For debugging a live feature that ladder is the real pricing axis, not the request count. Continuum's analytics are local-first and organized by repo and day rather than sold by retention window, which makes the two price lists hard to compare directly and easy to compare wrongly.

05

Coexistence

Stack recipe

How people run both.

These rarely compete for the same budget. Helicone instruments an application your company ships; Continuum instruments and governs the coding agents your engineers run against repositories. A team can reasonably buy both, and Continuum ships no Helicone integration, so treat any pairing as your own wiring rather than a supported path.

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06

Pick by what you are measuring

Continuum

Choose Continuum to see and cap agent spend

  • The spend you cannot explain is coming from coding agents, not from your production application.
  • Most of that spend runs on subscriptions that never cross a gateway.
  • You need cost by repository, provider, model, and day rather than by request and session.
  • An admin has to set weekly spend caps, a model policy, and member approvals across the team.
  • Worktree isolation, plan approval, and diff and PR review belong in the same product as the reporting.
  • You want this working today without deploying or operating anything.
Helicone

Choose Helicone to instrument production LLM calls

  • You are shipping an LLM feature and need per-request tracing, sessions, and user views.
  • Prompt management, datasets, evaluation, and a playground are part of the workflow.
  • An Apache 2.0 license and self-hosting are requirements rather than preferences.
  • You want a fast gateway with latency-aware and cost-aware routing across 100+ providers.
  • Caching in Redis or S3 and rate limits per user, team, or globally are the controls you need.
  • Retention, alerts, SOC-2, HIPAA, SAML SSO, or on-premises deployment drive the purchase.
07

What you pay

Continuum

App + your labs

$0 for the app on Mac, iPhone, Watch, web, and the Windows and Linux desktop beta, running under the provider subscriptions you already pay for. Optional hosted inference is $25 per month for Plus, $100 for Max 100, $200 for Max 200, and $500 for Ultra, with weekly hosted-usage allowances of $25, $100, $200, and $1,000.

Helicone

Their bill

Hobby is free with 10,000 requests, 1GB of storage, one seat, and 7-day retention. Pro is $79 per month, including 10,000 free requests then usage-based charges, unlimited seats, alerts, reports, the HQL query language, and 1-month retention. Team is $799 per month, adding five organizations, SOC-2 and HIPAA, dedicated Slack support, and 3-month retention. Enterprise is custom, with a custom MSA, SAML SSO, on-premises deployment, and bulk cloud discounts. The main platform is Apache 2.0 and the AI Gateway is GPL-3.0; both can be self-hosted.

How to compare

Total cost of work

The two price lists buy different things. Helicone's ladder is driven by retention, seats, and compliance for application telemetry. Continuum charges nothing for the workbench or its local analytics, and its paid tiers buy hosted inference rather than reporting.

Helicone plans checked 3 August 2026 against their pricing page. Vendors reprice often - if you spot a stale figure, tell us and we will fix it. Continuum never marks up a session it runs under your own login.

Continuum ladder: Free app · Plus $25/mo · Max 100 · Max 200 · Ultra - full pricing. Also analytics, multi-account, devices.

08

Questions

Continuum vs Helicone.

Deep dives: docs, providers, sessions.

Only if what you needed was visibility and control over coding-agent spend. Continuum reports cost by repo, provider, model, and day and enforces weekly caps and model policy, including subscription work no gateway sees. It does not replace Helicone's request-level tracing, sessions, prompt management, or evaluation for a production LLM application.

Yes. The main Helicone repository is Apache 2.0 with 6,085 GitHub stars, and the separate AI Gateway repository is GPL-3.0 with 622 stars and can be self-hosted via Docker. Enterprise additionally offers on-premises deployment.

Hobby is free with 10,000 requests, 1GB, one seat, and 7-day retention. Pro is $79 per month with unlimited seats, alerts, reports, HQL, and 1-month retention. Team is $799 per month with five organizations, SOC-2 and HIPAA, dedicated Slack support, and 3-month retention. Enterprise is custom priced.

Not if Claude Code is authenticated with a subscription, because that traffic never passes through a gateway. Helicone observes requests routed through it. Continuum reads the agents' own local logs and prices them, which is how subscription spend becomes visible without changing authentication.

A GPL-3.0 gateway giving one OpenAI-compatible interface to 100+ providers, with model latency routing, provider latency routing using P2C with PeakEWMA, weighted distribution, and cost optimization, plus Redis and S3 caching, rate limits per user, team, or globally, and OpenTelemetry tracing. It advertises a P95 under 5ms, roughly 64MB of memory, around 3,000 requests per second, and a 30MB binary.

Yes, and many teams should. Helicone instruments the LLM application your company ships; Continuum governs the coding agents your engineers run. Continuum ships no Helicone integration, so if you want agent traffic in Helicone you would route it yourself through the gateway, which only works for API-keyed sessions.

Begin

Run your agents
in Continuum.

Free app. Your subscriptions. Optional hosted inference. Mac stable - Windows and Linux desktop are beta.

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vendor-neutral · local-first · multi-device