Comparison

Logfire vs Honeycomb

Both products are OpenTelemetry-native. Logfire adds the rest of the production AI loop: full-stack traces, datasets, evaluators, human review, quality SLOs, and improvement workflows, with PostgreSQL-compatible SQL that developers and coding agents can use directly.

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Feature comparison

Quick comparison

Logfire and Honeycomb compared feature by feature
Feature	Logfire	Honeycomb
OpenTelemetry	Native, no proprietary agent	Native, no proprietary agent
Query interface	SQL (PostgreSQL syntax) as text	Visual Query Builder with SQL-shaped clauses, plus a natural-language assistant
Evals & datasets	Datasets, code and LLM-judge scorers, experiments, human annotation, live evals	Not offered
Free tier	10M records/month	20M events/month
Usage pricing	Personal: 10M records free; Team: $49/month + $2/M over 10M	$150 Pro entry; $3/M events of monthly capacity, with a separate metric-point allowance
Seats	1 on Free; 5 on Team ($49/mo), $25 each beyond; unlimited on Growth ($249/mo)	Unlimited on every plan
SLOs	SLIs from any SQL predicate, including AI quality	Mature SLO product; not on Free, 2 on Pro

Key differences

Where the two actually diverge

Evals: the decisive gap for an AI product

Honeycomb markets LLM observability, an agent timeline and token tracking. What it does not have is any part of the evaluation workflow: no datasets, no scorers, no experiments, no human annotation. That is fine if you are monitoring an AI feature. It is a problem if you are trying to answer whether last week's prompt change made your answers better, because tracing shows you what happened and says nothing about whether it was any good. Logfire ships datasets built from production traces, code and LLM-judge scorers, annotation queues, experiment comparison against a baseline, and live evals over real traffic.

A query you can paste, commit, and hand to an agent

Honeycomb's Query Builder is a well-made visual tool: filters, breakdowns and calculations across SQL-shaped clauses, with a natural-language assistant on top. Logfire's queries are SQL text. The difference is not really ergonomics, it is what a query is: an interface you operate, or an artifact you can put in a script, review in a pull request, paste into an alert, and hand to a coding agent that already writes PostgreSQL. Point Claude Code or Cursor at our MCP server and it writes the query itself.

Objectives that can be about quality

Logfire defines an SLI as a SQL predicate over spans, and evaluation results are spans too. That means an objective can be “the judge scored this run at or above 0.8” or “availability, but only for calls to this provider”. For a team running AI in production, quality can be operated with the same discipline as latency and availability.

Two different pricing shapes

Honeycomb's free plan includes 20 million events and 100 million metric points a month. Pro sells monthly capacity at a published $3 per million events, starting at $150 for 50 million events and 250 million metric points, with 60-day event retention. Logfire Personal includes 10 million records; Team is $49 plus $2 per million beyond that with 30-day retention, while Growth supports up to 90 days. The worked trace-only examples show both Logfire plans and preserve Honeycomb's separate metric allowance instead of pretending every entitlement is interchangeable.

Decision guide

Which should you choose?

Choose Logfire if

You are building an AI product and need evals, datasets and annotation alongside traces
You want to write queries as text, put them in version control, and hand them to a coding agent
You want SLOs whose definition of 'good' can be an evaluation score, not just latency or errors
Your usage is record-heavy rather than byte-heavy and per-record pricing suits you better
You want to start and scale without talking to anyone

Choose Honeycomb if

Your team is already standardized on Honeycomb and wants to keep that investigation workflow
BubbleUp's automatic outlier attribution is the workflow you want
You need unlimited seats from day one

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Pricing

Monthly capacity versus record usage

Honeycomb and Logfire trace-only pricing with retention and separate metric allowances disclosed
Illustrative monthly workload	Logfire	Honeycomb
Free cloud allowance	10M records/month	20M events + 100M metric points/month
50M trace spans/month	$129 Team (30 days) · $329 Growth (up to 90 days)	$150 Pro (60 days) + 250M metric points
750M trace spans/month	$1,529 Team (30 days) · $1,729 Growth (up to 90 days)	$2,250 Pro (60 days) + 3.75B metric points
Billing shape	$2/M records above 10M	$3/M events of chosen monthly capacity; sustained overage can throttle

See the exact pricing math and sources 13 published inputs · 4 official sources · checked August 20, 2026

Calculation scope

Honeycomb's 2026 monthly event-capacity pricing for trace-only workloads at the published 50-million-event entry tier and 750-million-event upper Pro boundary. Metric data points remain a separate included allowance.

Basis: USD; public monthly list price. Prices checked August 20, 2026.

Published inputs

Logfire Personal base: $0/month Pydantic Logfire source
Logfire Team base: $49/month Pydantic Logfire source
Logfire Growth base: $249/month Pydantic Logfire source
Logfire included telemetry: 10,000,000 records/month Pydantic Logfire source
Logfire additional telemetry: $2 per 1,000,000 records Pydantic Logfire source
Honeycomb Free event allowance: 20,000,000 events/month Honeycomb source
Honeycomb Free metrics allowance: 100,000,000 data points/month Honeycomb source
Honeycomb Pro entry package: $150/month Honeycomb source
Honeycomb Pro starting event allowance: 50,000,000 events/month Honeycomb source
Honeycomb Pro starting metrics allowance: 250,000,000 data points/month Honeycomb source
Honeycomb 2026 Pro event rate: $3 per 1,000,000 events of monthly capacity Honeycomb source
Honeycomb published Pro event range: Up to 750,000,000 events/month Honeycomb source
Honeycomb published Pro metrics range: Up to 3,750,000,000 data points/month Honeycomb source

Assumptions

Plan pricing: $3 per million events of monthly capacity Honeycomb publishes the 2026 Pro rate and says its four capacity tiers top out at 750 million events per month. Honeycomb source
Event equivalence: One trace span = one Honeycomb event = one Logfire record Honeycomb explicitly counts each span in a trace as one event. The direct totals are limited to trace spans and do not convert metric data points into records. Honeycomb source
Meters: Events and metric data points remain separate The public Honeycomb packages include both allowances, so neither is silently converted into the other. Honeycomb source
Retention: Honeycomb 60 days; Logfire Team 30 days; Growth up to 90 days Both Logfire plan totals are shown so the price and retention trade-off stays visible instead of being presented as an equivalent package. Pydantic Logfire source Honeycomb source

Calculations

25 million trace spans per month

The first volume past Honeycomb's free allowance, and the row where the two pricing shapes separate. Logfire meters the 15 million records beyond its included 10 million. Honeycomb Free stops at 20 million events, and Pro's entry capacity is 50 million, so this workload buys twice the capacity it uses. Below 20 million events Honeycomb Free is genuinely free and the comparison is not worth drawing.

Logfire

$79

Team base $49 $49
Additional records (25M − 10M included) ÷ 1M × $2 $30

Honeycomb Pro

$150

Entry Pro capacity 25M events exceed the 20M Free allowance; Pro starts at 50M × $3/M $150

50 million trace spans per month

Honeycomb's entry Pro tier is compared with both Logfire plans because the included retention periods differ.

Logfire

$129

Team base $49 $49
Additional records (50M − 10M included) ÷ 1M × $2 $80

Logfire

$329

Growth base $249 $249
Additional records (50M − 10M included) ÷ 1M × $2 $80

Honeycomb Pro

$150

Monthly event capacity 50M events × $3/M events $150

750 million trace spans per month

The upper published Pro boundary is calculated from Honeycomb's $3-per-million event rate; included metric capacity is not converted into trace value.

Logfire

$1,529

Team base $49 $49
Additional records (750M − 10M included) ÷ 1M × $2 $1,480

Logfire

$1,729

Growth base $249 $249
Additional records (750M − 10M included) ÷ 1M × $2 $1,480

Honeycomb Pro

$2,250

Monthly event capacity 750M events × $3/M events $2,250

Source ledger

Pydantic Logfire — Pricing and plans for Pydantic Logfire Official vendor source · checked August 20, 2026 https://pydantic.dev/pricing

“Covers 10 million logs, spans, and metrics every month.”

The official calculator shows 20 million records and no extra seats totaling $69/month on Team.
Honeycomb — Honeycomb pricing Official vendor source · checked August 20, 2026 https://www.honeycomb.io/pricing

“Up to 750M events + 3.75B metric data points per month”

Honeycomb publishes a 20-million-event Free allowance and Pro capacity from 50 million through 750 million events per month.
Honeycomb — 2026 Pro Plan Changes Official vendor source · checked August 20, 2026 https://docs.honeycomb.io/get-started/honeycomb/2026-pro-plan-changes

“The new per-event rate is $3.00 per million events.”

Honeycomb says the 2026 Pro structure has four capacity tiers and tops out at 750 million events per month.
Honeycomb — How Honeycomb Calculates Usage Official vendor source · checked August 20, 2026 https://docs.honeycomb.io/get-started/manage-costs/how-honeycomb-calculates-usage

“Honeycomb measures two types of usage: events and metrics data points.”

Each trace span counts as one event; event and metric limits are independent; events and logs have 60-day fixed retention and metrics have 13-month fixed retention by default.

What this calculation does not include

The direct totals model trace spans only. Honeycomb's separately included metric points can be valuable, but they are not converted into a synthetic Logfire-record equivalent.
Honeycomb Pro includes 60-day fixed retention for events and logs; Logfire Team includes 30 days and Growth supports up to 90 days.
Honeycomb sells monthly event and metric capacity rather than automatic pay-as-you-go usage. A second consecutive month over either limit can lead to throttling after a 10-day warning unless capacity increases or usage falls.
Honeycomb separately protects up to three event bursts and three metric bursts per calendar month; qualifying excess is stored without counting against the monthly limit.
Enterprise quotes, volume discounts, add-ons, taxes, and data-shipping costs are excluded.

FAQ

Common questions

Does Honeycomb have evals?

No. Honeycomb's platform and AI observability pages market LLM observability, an agent timeline and token tracking, but no datasets, scorers, experiments or human annotation. If you are buying observability for an AI product and you need to know whether a prompt change made your answers better, that is the gap. Logfire ships datasets, code and LLM-judge scorers, human annotation queues, experiment comparison and live evals over production traffic.

Are both Logfire and Honeycomb OpenTelemetry-native?

Yes, genuinely. Neither requires a proprietary agent, both accept standard OTLP, and both let you export the same telemetry elsewhere. Honeycomb's OpenTelemetry contribution record is real and deep. Anyone telling you one of these two is OTel-native and the other is not is selling you something.

How do the query interfaces actually differ?

Honeycomb's Query Builder is a visual tool: you add filters, breakdowns and calculations across SELECT, WHERE, GROUP BY, ORDER BY, LIMIT and HAVING clauses, with a natural-language assistant that generates queries for you. It is fast and well designed. Logfire's queries are SQL text, which means they paste into a script, live in a pull request, and can be written by a coding agent that already knows PostgreSQL syntax. Which you prefer depends on whether you want queries to be an interface or an artifact.

How do the free tiers differ?

Honeycomb publishes 20 million events plus 100 million metric points per month, while Logfire includes 10 million records across logs, spans, and metrics. Those are different units and product entitlements, not a like-for-like capacity claim. Beyond the free tier, Honeycomb's 2026 Pro rate is $3 per million events of chosen monthly capacity, starting at 50 million events, while Logfire Team is $49 plus $2 per million records over 10 million. The worked trace-only examples keep retention and Honeycomb's separate metric allowance visible.

Can I run both during an evaluation?

Yes, and it is the sensible way to decide. Both speak OTLP, so you can fan the same telemetry out to both backends with an OpenTelemetry Collector, run the same debugging task in each, and keep whichever answered faster. No instrumentation rewrite is required, which is the practical benefit of both being OTel-native.

When might Honeycomb be the better fit?

Honeycomb can be the practical choice for a team already standardized on its investigation workflow, especially when BubbleUp or unlimited seats are requirements. Logfire is the stronger fit when the same product must connect full-stack telemetry to datasets, evaluators, human review, and production improvement.

Try Logfire alongside Honeycomb

Both speak OTLP, so a collector can send the same telemetry to each and you can decide on your own traces. 10 million records a month, free.

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