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Telemetry pipelines · October 2026 Edition

Vector vs New Relic

Two of fourteen models named Vector first on the direct prompt; one named New Relic. Vector was named by thirteen of the fourteen models and New Relic by eleven and Vector carries 35 labels and New Relic 18, so the shares are not directly comparable.

Vector

accepted challenger

Named in two categories this edition.

New Relic

accepted challenger

Named in eight categories this edition.

First-choice share12%3%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate3%11%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#3#6A position in a field of 14; printed, not drawn.
Labels3518A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Vector reading right to left. Rank and label count are printed, not drawn.OpenTelemetry Collector was named alongside these two in ten of the fourteen direct answers. OpenTelemetry Collector vs Vector · OpenTelemetry Collector vs New Relic · Cribl Stream vs Vector

Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all fourteen models, for a mid-market B2B company; rank is within the category; every quote names the model and the prompt it came from. Both figures come from the telemetry pipelines page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
VectorFirst choices, of fourteen modelsNew Relic
Direct211 against New Relic
Paraphrase41
Comparative201 against Vector
Budget-constrained001 against New Relic
Scale-constrained10
Negative10
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where Vector and New Relic stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
Claude Haiku 4.5
GPT-5.4 mini
Gemini 3.5 Flash
Perplexity Sonar
Grok 4.1 Fast
Mistral Small
DeepSeek V4 Flash
Llama 4 Maverick
Qwen 3.7 Flash
Kimi K2
GLM 4.7 FlashX
MiniMax M2.5
GPT-6 Luna
Muse Glimmer 30B
Vector New Relic first choice named as an alternative argued againstblank: not namedEach cell is one answer, Vector on the left and New Relic on the right.

The direct prompt

The plain question, one answer per model, grouped by where Vector and New Relic stood in it.

Vector first, New Relic not the choice

2 of 14 modelsNew Relic was named in the answer but not as the choice, or not at all.
Qwen 3.7 FlashVector alternatives: Cribl Stream, OpenTelemetry Collector
MiniMax M2.5Vector alternatives: Datadog

New Relic first, Vector not the choice

1 of 14 modelsVector was named in the answer but not as the choice, or not at all.
Muse Glimmer 30BCribl Stream, New Relic alternatives: Datadog, Edge Delta, Grafana Cloud, Middleware.io, OpenTelemetry Collector, SigNoz, Uptrace

Neither was the first choice, one was named

5 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Grok 4.1 FastOpenTelemetry Collector alternatives: ClickHouse Cloud, Grafana, Grafana Cloud, Grafana Loki, Honeycomb, Jaeger, Palo Alto Networks Cortex Cloud, Prometheus, SigNoz, Tempo, Thanos, Uptrace, Vector
Mistral SmallOpenTelemetry Collector alternatives: Chronosphere Telemetry Pipeline, Grafana LGTM, OpenObserve, Vector
DeepSeek V4 FlashGrafana Cloud, OpenTelemetry Collector alternatives: Cribl Stream, New Relic
Kimi K2Cribl Stream, OpenTelemetry Collector alternatives: Fluent Bit, Vector
GLM 4.7 FlashXGrafana Observability Stack alternatives: Datadog, Honeycomb, New Relic

Neither was named

6 of 14 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5no first choice alternatives: OpenTelemetry Collector
GPT-5.4 miniOpenTelemetry Collector alternatives: Census, Google BigQuery, Hightouch, Looker, Metabase, RudderStack, Snowflake, Twilio Segment, dbt
Gemini 3.5 FlashOpenTelemetry Collector, PostHog, RudderStack alternatives: BindPlane OP, Cribl Stream, Grafana Cloud, Honeycomb
Perplexity SonarGrafana Alloy alternatives: AWS Distro for OpenTelemetry, Datadog Observability Pipelines, Edge Delta
Llama 4 Maverickno first choice
GPT-6 LunaGrafana Cloud, OpenTelemetry Collector alternatives: Datadog, Honeycomb

Bold names in an answer are the products the judge labeled a first choice; a model naming several gives each of them that label. The full answer text for every row is in the record.

By buyer segment

The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
Vector leads by fourteen points.
Vector14%#3 of 12
New Relic0%#11 of 12
The full small business standing →
Mid-marketThe figures above
Vector leads by eight points.
Vector12%#3 of 14
New Relic3%#6 of 14
The full mid-market standing →
Enterprise
Vector leads by four points.
Vector4%#4 of 12
New Relic0%#12 of 12
The full enterprise standing →

What the models said about Vector

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.

“its documentation describes trace support as limited and in alpha, so verify your trace use case before choosing it” GPT-6 Luna · comparative prompt · soft negative
“Vector is often cited as a top choice for mid-market companies because it offers enterprise-level capabilities without the enterprise price tag” MiniMax M2.5 · direct prompt · first choice
“Ship logs/metrics to a local agent (like Vector, FluentBit, or an OpenTelemetry Collector) running next to the app.” Qwen 3.7 Flash · negative prompt · first choice
“Best like-for-like swap for an existing pipeline: Vector. It keeps the transformation depth and drops the JVM” Muse Glimmer 30B · comparative prompt · first choice

What the models said about New Relic

No label in this category carried a quote.

Also compared

Comparisons are drawn for the top eight products in each category, each against each. The output is the models' output; nothing here is a recommendation by the index.