Grafana Loki vs Elastic Stack
Zero of fourteen models named Grafana Loki first on the direct prompt; zero named Elastic Stack. Both were named by all fourteen models and Grafana Loki carries 46 labels and Elastic Stack 54, so the shares are not directly comparable.
Named in eight categories this edition.
Named in five categories this edition.
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 log management page.
By framing
Grafana LokiFirst choices, of fourteen modelsElastic Stack
Across every category in the October 2026 Edition, Grafana Loki and Elastic Stack were named in the same answer eighty-five times, of the 178 answers naming Grafana Loki and the 167 naming Elastic Stack. In those answers Elastic Stack took the first choice six times and Grafana Loki twelve.
Every model, every framing
| Model | Direct | Paraphrase | Comparative | Budget-constrained | Scale-constrained | Negative |
|---|---|---|---|---|---|---|
| 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 | | |
Grafana Loki Elastic Stack first choice named as an alternative argued againstblank: not namedEach cell is one answer, Grafana Loki on the left and Elastic Stack on the right.The direct prompt
Neither was the first choice, one was named
7 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
7 of 14 modelsThe answer made no first choice from these two in this category.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
Grafana Loki12%#3 of 11Elastic Stack3%#7 of 11Grafana Loki11%#3 of 12Elastic Stack6%#5 of 12Elastic Stack4%#3 of 10Grafana Loki2%#6 of 10What the models said about Grafana Loki
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of four in this category shown.
“Loki is cheap but intentionally less powerful for full-text search.” Kimi K2 · scale prompt · soft negative
“If you want to keep licensing costs low and have strong backend/K8s skills: Deploy Grafana Loki + Fluentd with a Grafana frontend.” GLM 4.7 FlashX · paraphrase prompt · first choice
“Graylog Open and Grafana Loki are the top contenders since they're truly free with no ingestion limits” MiniMax M2.5 · budget prompt · first choice
“best value choice is usually Grafana Loki if you want a low-cost, open-source-friendly platform” GPT-5.4 mini · budget prompt · first choice
What the models said about Elastic Stack
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“The Trap to Avoid: The "Free" ELK Stack (Elasticsearch)... This is often a financial mistake for small companies.” Gemini 3.5 Flash · budget prompt · hard negative
“Avoid spending money on a tool that requires a full-time engineer just to keep the lights on (like raw ELK).” GLM 4.7 FlashX · negative prompt · hard negative
“Verdict: Avoid self-hosting unless you have dedicated DevOps/SRE resources.” Kimi K2 · negative prompt · hard negative
“This is a popular open-source option that is highly customizable and scalable. It's free to use” Mistral Small · budget prompt · first choice
“Datadog or Elastic Cloud are the most common sweet spots for companies of your size” DeepSeek V4 Flash · scale prompt · first choice
“I'd suggest Datadog or ELK Stack as starting points” Claude Haiku 4.5 · paraphrase prompt · first choice
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.