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Index › IT › IT operations and endpoint › Telemetry pipelines › Grafana vs Grafana Loki
Telemetry pipelines · November 2026 Edition

Grafana vs Grafana Loki

Zero of fourteen models named Grafana first on the direct prompt; zero named Grafana Loki. Grafana was named by eleven of the fourteen models and Grafana Loki by eleven and both carry 18 labels, so the shares below are directly comparable.

Grafana

accepted challenger

Named in nine categories this edition.

Grafana Loki

accepted challenger

Named in seven categories this edition.

First-choice share2%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate6%6%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#6#7A position in a field of 18; printed, not drawn.
Labels1818Equal, which is what makes the shares comparable.
The two percentage rows are drawn on one 0 to 100 track, Grafana reading right to left. Rank and label count are printed, not drawn.OpenTelemetry Collector was named alongside these two in thirteen of the fourteen direct answers. OpenTelemetry Collector vs Grafana · OpenTelemetry Collector vs Grafana Loki · Cribl Stream vs Grafana

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.
GrafanaFirst choices, of fourteen modelsGrafana Loki
Direct00
Paraphrase00
Comparative001 against Grafana Loki
Budget-constrained11
Scale-constrained00
Negative001 against Grafana
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 Grafana and Grafana Loki stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
Claude Haiku 4.5
GPT-5.4 mini
Gemini 3.5 Flash
Perplexity Sonar
Grok 4.20
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
Grafana Grafana Loki first choice named as an alternative argued againstblank: not namedEach cell is one answer, Grafana on the left and Grafana Loki on the right.

The direct prompt

The plain question, one answer per model, grouped by where Grafana and Grafana Loki stood in it.

Neither was the first choice, one was named

2 of 14 modelsThe answer put something else first and named one of the two as an alternative.
GLM 4.7 FlashXOpenTelemetry Collector alternatives: Grafana, Grafana Loki, OTel Collector, Prometheus, Tempo
Muse Glimmer 30BOpenTelemetry Collector alternatives: Cribl Stream, Grafana, Grafana Cloud, Grafana Loki, Jaeger, New Relic, Prometheus, Tempo, Vector

Neither was named

12 of 14 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5Cribl Stream alternatives: Bindplane, Datadog
GPT-5.4 miniOpenTelemetry Collector
Gemini 3.5 FlashCribl Stream, OpenTelemetry Collector, Vector alternatives: Amberflo, Census, Grafana Cloud, Hightouch, Lago, Metronome, Mixpanel, PostHog, RudderStack
Perplexity SonarOpenTelemetry Collector alternatives: Cribl Stream, Edge Delta
Grok 4.20OpenTelemetry Collector alternatives: Cribl Stream, Fluent Bit, Mezmo Telemetry Pipeline, Vector
Mistral SmallOpenTelemetry Collector alternatives: Cribl Stream, Vector
DeepSeek V4 FlashOpenTelemetry Collector alternatives: Cribl Stream, Grafana LGTM Stack
Llama 4 MaverickVector alternatives: Cribl Stream, OpenTelemetry Collector
Qwen 3.7 FlashGrafana Cloud alternatives: Datadog, Honeycomb, Lightstep, OpenTelemetry Collector
Kimi K2OpenTelemetry Collector alternatives: Cribl Stream, Vector
MiniMax M2.5OpenTelemetry Collector alternatives: Cribl Stream, Vector
GPT-6 LunaOpenTelemetry Collector alternatives: Alloy, Datadog, Grafana Cloud, Honeycomb, RudderStack

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
Grafana Loki leads by one point.
Grafana Loki3%#5 of 15
Grafana1%#11 of 15
The full small business standing →
Mid-marketThe figures above
Level: the same share of first choices.
Grafana2%#6 of 18
Grafana Loki2%#7 of 18
The full mid-market standing →
Enterprise
Level: the same share of first choices.
Grafana0%#– of 15
Grafana Loki0%#– of 15
The full enterprise standing →

What the models said about Grafana

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

“The Grafana Stack—Grafana for visualization, Prometheus for metrics, Loki for logs, and Tempo for traces—is a fully open-source, modular observability solution with maximum control and minimal licensing cost” Claude Haiku 4.5 · budget prompt · first choice

What the models said about Grafana Loki

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

“Common for cost-conscious teams but lacks a unified "pipeline" layer.” Grok 4.20 · comparative prompt · soft negative
Also compared
OpenTelemetry Collector vs GrafanaOpenTelemetry Collector vs Grafana LokiCribl Stream vs GrafanaCribl Stream vs Grafana LokiVector vs GrafanaVector vs Grafana LokiGrafana Cloud vs GrafanaGrafana Cloud vs Grafana LokiFluent Bit vs GrafanaFluent Bit vs Grafana LokiGrafana vs New RelicGrafana Loki vs New RelicAll twenty-eight head-to-head pages and the full telemetry pipelines standing

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.