Application performance monitoring
Asked as “APM tool”, and as “application performance monitoring solution”, on behalf of a mid-market B2B company. 54 first choices recorded across the direct, paraphrase, budget and scale prompts, fourteen models each.
Standing · first-choice share
46%
Clear leader
46New Relic20Datadog APM09SigNoz24others
46% of first choices, clear leader.
Since September 2026▼−5Since September 2026: 54% → 49%, −5 points. Inside the 11-point floor: within noise. Read over the models both editions asked.New Relic held the lead, −5 points on 54%, inside the 11-point floor.
By buyer segment
The same question asked on behalf of a different buyer. Each standing is computed within its segment; they sit side by side and are never added together.
Small business
New Relic53%Clear leader▲+1Since September 2026: 51% → 52%, +1 point. Inside the 11-point floor: within noise. Read over the models both editions asked.Standing →Mid-marketNew Relic46%Clear leader▼−5Since September 2026: 54% → 49%, −5 points. Inside the 11-point floor: within noise. Read over the models both editions asked.This pageEnterprise
Dynatrace47%Clear leader▲+1Since September 2026: 46% → 46%, +1 point. Inside the 11-point floor: within noise. Read over the models both editions asked.Standing →
New Relic53%Clear leader▲+1Since September 2026: 51% → 52%, +1 point. Inside the 11-point floor: within noise. Read over the models both editions asked.Standing →Mid-marketNew Relic46%Clear leader▼−5Since September 2026: 54% → 49%, −5 points. Inside the 11-point floor: within noise. Read over the models both editions asked.This pageEnterpriseDynatrace47%Clear leader▲+1Since September 2026: 46% → 46%, +1 point. Inside the 11-point floor: within noise. Read over the models both editions asked.Standing →The standing
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. Ordered by share.
ProductFirst-choice shareNegative rateLabelsQuadrantSince September 2026
01New Relic46%12%65endorsed leader▼−5Since September 2026: 54% → 49%, −5 points. Inside the 11-point floor: within noise. Read over the models both editions asked.54% → 49%
New Relic46%12%65endorsed leader▼−5Since September 2026: 54% → 49%, −5 points. Inside the 11-point floor: within noise. Read over the models both editions asked.54% → 49%02
Datadog APM20%29%68criticized challenger▲+7Since September 2026: 11% → 18%, +7 points. Inside the 11-point floor: within noise. Read over the models both editions asked.11% → 18%
Datadog APM20%29%68criticized challenger▲+7Since September 2026: 11% → 18%, +7 points. Inside the 11-point floor: within noise. Read over the models both editions asked.11% → 18%03
SigNoz9%0%23accepted challenger▼−6Since September 2026: 13% → 7%, −6 points. Inside the 11-point floor: within noise. Read over the models both editions asked.13% → 7%
SigNoz9%0%23accepted challenger▼−6Since September 2026: 13% → 7%, −6 points. Inside the 11-point floor: within noise. Read over the models both editions asked.13% → 7%04
Site24x76%0%16accepted challenger▲+4Since September 2026: 2% → 7%, +4 points. Inside the 11-point floor: within noise. Read over the models both editions asked.2% → 7%
Site24x76%0%16accepted challenger▲+4Since September 2026: 2% → 7%, +4 points. Inside the 11-point floor: within noise. Read over the models both editions asked.2% → 7%05
Elastic APM4%11%28accepted challenger▲+4Since September 2026: 0% → 4%, +4 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 4%
Elastic APM4%11%28accepted challenger▲+4Since September 2026: 0% → 4%, +4 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 4%06
IBM Instana4%17%18accepted challenger=heldSince September 2026: 2% → 2%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.2% → 2%
IBM Instana4%17%18accepted challenger=heldSince September 2026: 2% → 2%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.2% → 2%07
Grafana Cloud2%0%26accepted challenger▼−2Since September 2026: 4% → 2%, −2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.4% → 2%
Grafana Cloud2%0%26accepted challenger▼−2Since September 2026: 4% → 2%, −2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.4% → 2%08
Honeycomb2%0%10accepted challenger=heldSince September 2026: 2% → 2%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.2% → 2%
Honeycomb2%0%10accepted challenger=heldSince September 2026: 2% → 2%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.2% → 2%09Dynatrace2%48%50criticized challenger▲+2Since September 2026: 0% → 2%, +2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 2%
Dynatrace2%48%50criticized challenger▲+2Since September 2026: 0% → 2%, +2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 2%Show the three products at 0%, ordered by negative rate
11
AppDynamics0%27%37criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 0%
AppDynamics0%27%37criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 0%12Jaeger0%18%11accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 0%
10
Sentry0%0%13accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 0%
Sentry0%0%13accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 0%The floor is 11 points of share, measured: how far the models move a leader on their own when the same questions are asked twice with nothing changed. A larger change is movement; a smaller one is noise, and both are shown. Movement is read over the twelve models both editions asked; GPT-6 Luna, Muse Glimmer 30B joined this edition and are in the standing but not yet in the comparison. How the floor is measured
Bars are the share of first choices, 0 to 100Every product with at least 10 labels here. Every product name links to its product page.
All twenty-eight head-to-head pages: the top eight products, each against each
New Relic vs Elastic APMNew Relic vs IBM InstanaNew Relic vs Grafana CloudNew Relic vs HoneycombDatadog APM vs SigNozDatadog APM vs Site24x7Datadog APM vs Elastic APMDatadog APM vs IBM InstanaDatadog APM vs Grafana CloudDatadog APM vs HoneycombSigNoz vs Site24x7SigNoz vs Elastic APMSigNoz vs IBM InstanaSigNoz vs Grafana CloudSigNoz vs HoneycombSite24x7 vs Elastic APMSite24x7 vs IBM InstanaSite24x7 vs Grafana CloudSite24x7 vs HoneycombElastic APM vs IBM InstanaElastic APM vs Grafana CloudElastic APM vs HoneycombIBM Instana vs Grafana CloudIBM Instana vs HoneycombGrafana Cloud vs Honeycomb
Recommended versus criticized
Every product with at least 10 labels here, on both axes. The 30% line names a quadrant, not the verdict above: that one needs more than 40%.
Criticized challengerCriticized default
Negative label rate →
0102030405060708091011J12
Accepted challengerEndorsed leader
0%First-choice share → · lines at 30% share and 25% negative60%
Key
01New Relic46%
New Relic46%02Datadog APM20%
Datadog APM20%03SigNoz9%
SigNoz9%04Site24x76%
Site24x76%05Elastic APM4%
Elastic APM4%06IBM Instana4%
IBM Instana4%07Grafana Cloud2%
Grafana Cloud2%08Honeycomb2%
Honeycomb2%09Dynatrace2%
Dynatrace2%10Sentry0%
Sentry0%11AppDynamics0%
AppDynamics0%12Jaeger0%
What they warned about
Seven of fourteen models held their first choice under the paraphrase. Claude Haiku 4.5, Grok 4.1 Fast, Mistral Small, Qwen 3.7 Flash, Kimi K2, MiniMax M2.5 and Muse Glimmer 30B changed. A high negative share on a product with few labels is a warning. A low share on a product with many labels is salience, not sentiment.
Dynatrace48%
24 of 50 labels negative · 13 of 14 models · 5 hard negative
“Verdict: Avoid unless you are a large enterprise with a dedicated Site Reliability Engineering (SRE) team” Qwen 3.7 Flash, negative prompt
Datadog APM29%
20 of 68 labels negative · 13 of 14 models · 4 hard negative
“tools and vendors you should be **cautious about** or potentially **avoid**... **1. Datadog** - Most Common Complaint ... **Unpredictable pricing**” Kimi K2, negative prompt
AppDynamics27%
10 of 37 labels negative · 9 of 14 models · 3 hard negative
“Teams on perpetual licenses, Rapid Start SKUs and older agents are being actively sunset. If you are evaluating a "new" AppDynamics deployment in 2026 you are effectively buying into Splunk's portfolio roadmap” Muse Glimmer 30B, negative prompt
New Relic12%
8 of 65 labels negative · 8 of 14 models · 1 hard negative
“**New Relic** if your team lacks a dedicated observability engineer.” DeepSeek V4 Flash, negative prompt
What they cite
Citations exist only for the models that return a source list: fourteen of the fourteen in this edition, and all six flagship models on the expanded tier.
Sites the answers cite
76 of 84 answers in this category came back with a source list, from 14 of 14 models: citations where the model returns them, or the search results it consulted. 964 links across 199 sites, every framing counted. Ranked by the number of answers carrying the site or page. 10 of the 252 answers across every segment cited this index's own page for the category; the method page measures whether that reading tilts an answer.
vendor site · Motadata44 answers · 45 citations · 11 models
vendor site · G234 answers · 58 citations · 13 models
vendor site · ManageEngine30 answers · 42 citations · 11 models
vendor site · New Relic28 answers · 44 citations · 12 models
vendor site · Middleware.io28 answers · 30 citations · 11 models
23 answers · 23 citations · 12 models
vendor site · G222 answers · 24 citations · 9 models
vendor site · Coralogix22 answers · 22 citations · 7 models
vendor site · Uptrace21 answers · 23 citations · 9 models
19 answers · 21 citations · 8 models
vendor site · Atatus18 answers · 29 citations · 10 models
vendor site · OpenObserve17 answers · 18 citations · 10 models
Pages the answers cite
The ten pages named in the most answers, by full address. A page here is one the models returned with a recommendation, not one the index endorses.
44 answers · 11 models
27 answers · 10 models
24 answers · 9 models
22 answers · 10 models
19 answers · 8 models
19 answers · 12 models
17 answers · 5 models
17 answers · 7 models
17 answers · 8 models
15 answers · 10 models
Search against answers
Each company's standing in the answers beside its site's footprint in Google search, one row a site: the products the models named on it with their shares, and the share they add up to; monthly searches on Google, and DataForSEO's estimate of AI search demand (modeled from search signals, directional, not a count of queries to any assistant), for the most-searched of the company's and its products' names (the name is in each row's hover text); estimated monthly organic visits to the site; and its best position in Google's top ten for “apm tool”, “apm tools”, “best apm tool”. US estimates from DataForSEO and Google's Ads Transparency Center. A small company's site, or a mid-sized company's site for its flagship, is marked company; a product on a large parent's site (Google, Microsoft) has no site figures. A column with no figures for this category is left out, and an empty cell means none were seen, not none exist. Two measurements side by side: neither is read as the cause of the other.
| Company and products | Share | Own site cited | Name searches, Google | AI search demand, est. | Organic visits | Paid search a month, est. | Google ads, last 30 days | Best Google position |
|---|---|---|---|---|---|---|---|---|
| New Relic newrelic.com | 46% | 629 | 14,800 | 843 | 83,276 | $412 | 89 | 4 |
| Datadog datadoghq.com Datadog APM 20% | 20% | 186 | 74,000 | 3,541 | 159,408 company | $633 | 120 | |
| SigNoz signoz.io | 9% | 208 | 2,400 | 52 | 7,244 | 1 | 5 | |
| Site24x7 site24x7.com | 6% | 214 | 1,300 | 61 | 174,542 | $522 | 120 | |
| Elastic elastic.co Elastic APM 4%, Elastic Observability 0% | 4% | 109 | 74,000 | 34,672 | 208,306 company | 105 | ||
| IBM parent site IBM Instana 4% | 4% | 74 | 201,000 | 34,098 | ||||
| OpenObserve openobserve.ai | 4% | 157 | 1,600 | 9 | 4,825 | 7 | 5 | |
| Grafana Cloud grafana.com Grafana Cloud 2%, Grafana Stack 2%, Prometheus + Grafana 0% | 4% | 174 | 2,400 | 40 | 84,520 | 116 | ||
| Honeycomb honeycomb.io | 2% | 89 | 135,000 | 13,732 | 6,603 | 65 | ||
| Dynatrace dynatrace.com | 2% | 700 | 22,200 | 1,106 | 62,738 | $3,941 | 120 | 2 |
Google's top ten for the three searches hold 15 sites; 4 of them are among the sites the models cited here (manageengine.com, motadata.com, newrelic.com, openobserve.ai). The first result for “apm tool” is blazemeter.com.
How they answered
Six framings of the same buying question, each sent to every model in a fresh session with search on. One row per model, so a row shows whether it held its answer under rewording, what it named when cost was the constraint, and what it argued against. Computed from the raw judge labels.ShowHide
How they answered
Six framings of the same buying question, each sent to every model in a fresh session with search on. One row per model, so a row shows whether it held its answer under rewording, what it named when cost was the constraint, and what it argued against. Computed from the raw judge labels.
ShowHideModelDirect“What is the best APM tool for a mid-market B2B company?”Paraphrase“Which application performance monitoring solution would you recommend to a mid-sized B2B company?”Comparative“What are the top APM tools and how do they differ?”Budget-constrained“What is the best APM tool for a company with a limited budget?”Scale-constrained“We are a 500 person company evaluating a APM tool. What should we look at?”Negative“Which APM tools should I avoid or be cautious about?”
Claude Haiku 4.5Datadog APMNew RelicChangedDatadog APM, DynatraceNew Relicno first choiceagainst: Baselime, Datadog APM, Dynatrace, Elastic APM, New Relic, Odigos, Splunk Observability Cloud
Three alternatives
New Relic, Site24x7, SolarWinds ObservabilityThree alternatives
Datadog APM, Elastic APM, Site24x7Four alternatives
Elastic APM, Grafana Cloud, New Relic, SigNozFive alternatives
Elastic APM, Grafana Cloud, Prometheus, Sentry, SigNozGPT-5.4 miniNew Relicagainst: DynatraceNew RelicHeldno first choiceElastic APMagainst: Datadog APMno first choicenothing named
One alternative
Datadog APMThree alternatives
AppDynamics, Datadog APM, DynatraceFive alternatives
AppDynamics, Datadog APM, Dynatrace, Elastic APM, New RelicTwo alternatives
Grafana Cloud, New RelicGemini 3.5 FlashNew Relicagainst: Datadog APMNew RelicHeldDatadog APMGrafana Cloud, New Relic, SigNozagainst: Datadog APM, DynatraceHoneycombagainst: Datadog APMagainst: AppDynamics, Datadog APM, Dynatrace, Grafana Loki, Jaeger, Prometheus
Two alternatives
Grafana Cloud, SentryThree alternatives
Datadog APM, Honeycomb, SentryFive alternatives
AppDynamics, Dynatrace, Elastic APM, IBM Instana, New RelicFour alternatives
OpenObserve, Sentry, Site24x7, UptraceThree alternatives
Grafana Cloud, New Relic, SigNozPerplexity SonarDatadog APMDatadog APMHeldno first choiceSigNozno first choicenothing named
Three alternatives
AppDynamics, Dynatrace, ManageEngine Applications ManagerThree alternatives
Dynatrace, ManageEngine Applications Manager, Site24x7Three alternatives
Atatus, CubeAPM, New RelicGrok 4.1 FastDatadog APMagainst: DynatraceNew RelicChangedagainst: Dynatraceno first choiceNew Relicno first choiceagainst: AppDynamics, Datadog APM, Dynatrace, New Relic
Two alternatives
IBM Instana, New RelicTwo alternatives
Datadog APM, Site24x7Five alternatives
AppDynamics, Datadog APM, Dynatrace, Elastic APM, New RelicFive alternatives
Grafana Cloud, Prometheus + Grafana, Sentry, SigNoz, UptraceMistral SmallIBM Instanano first choiceChangedDatadog APMOpenObserveno first choiceagainst: AppDynamics, Datadog APM, Dynatrace, Elastic APM, IBM Instana, New Relic, Splunk Observability Cloud
Three alternatives
AppDynamics, Site24x7, Stackify RetraceFour alternatives
AppDynamics, Dynatrace, Elastic APM, New RelicTwo alternatives
Elastic APM, Grafana StackDeepSeek V4 FlashNew Relicagainst: DynatraceNew RelicHeldagainst: AppDynamics, Dynatraceno first choiceNew Relicno first choiceagainst: AppDynamics, Datadog APM, Dynatrace, IBM Instana, New Relic
Three alternatives
Datadog APM, IBM Instana, Site24x7Two alternatives
Datadog APM, Grafana CloudThree alternatives
Honeycomb, Sentry, SigNozLlama 4 Maverickno first choiceno first choiceHeldno first choiceElastic APM, Grafana Stack, OpenObserveno first choiceagainst: AppDynamics, Datadog APM, Dynatrace, New Relic
Two alternatives
OpManager Nexus, Stackify RetraceQwen 3.7 FlashNew Relicagainst: Datadog APMDatadog APMChangedagainst: Dynatrace, IBM AppDynamicsDatadog APMNew Relicno first choiceagainst: AppDynamics, Broadcom DX APM, Datadog APM, Dynatrace, IBM APM, Oracle DBCA, Splunk
One alternative
SolarWinds ObservabilityThree alternatives
Elasticsearch, Grafana Cloud, SigNozSix alternatives
AppDynamics, Dynatrace, Elastic APM, Elastic Observability, Honeycomb, New RelicFive alternatives
Grafana Cloud, Grafana Loki, ManageEngine OpManager Nexus, Prometheus, SigNozKimi K2New Relicagainst: DynatraceNew Relic, Site24x7Changedagainst: Datadog APM, Dynatraceno first choiceSigNozDatadog APM, Dynatrace, New Relicagainst: Datadog APM, Dynatrace, New Relic
Three alternatives
Datadog APM, IBM Instana, Site24x7Three alternatives
Atatus, Jaeger, ZipkinGLM 4.7 FlashXSite24x7Site24x7Heldagainst: Datadog APM, New Relicno first choiceNew Relicno first choiceagainst: AppDynamics, Datadog APM, Dynatrace, Elastic APM, Jaeger, Zipkin
Two alternatives
Datadog APM, IBM InstanaOne alternative
ManageEngine Applications ManagerNine alternatives
Atatus, Elastic APM, Grafana Cloud, Highlight.io, Scout APM, Scouter, Sentry, SigNoz, UptraceMiniMax M2.5New Relicagainst: DynatraceDatadog APM, New RelicChangedagainst: AppDynamics, Dynatraceno first choiceNew RelicDatadog APM, New Relicagainst: Datadog APM, Dynatrace, IBM Instana
One alternative
Datadog APMOne alternative
Site24x7Five alternatives
Azure Application Insights, Elastic APM, Google Cloud Operations, Sentry, SigNozTwo alternatives
Jaeger, PrometheusGPT-6 LunaDatadog APMDatadog APMHeldno first choiceSigNozagainst: Datadog APMno first choiceagainst: Datadog APM, Dynatrace
One alternative
New RelicTwo alternatives
Grafana Cloud, New RelicTwo alternatives
Grafana Cloud, Self-hosted SigNozMuse Glimmer 30BDatadog APM, IBM Instana, New RelicNew RelicChangedagainst: DynatraceDatadog APMNew Relic, SigNozno first choiceagainst: AppDynamics, Datadog APM, Dynatrace, New Relic
Two alternatives
AppDynamics, Site24x7Two alternatives
Datadog APM, IBM InstanaTwo alternatives
Dynatrace, New RelicFive alternatives
Atatus, Elastic APM, Grafana Cloud, Prometheus + Grafana, SolarWinds AppOpticsBold is the first choiceAlternatives are counted; the count opens them.What the answer argued against
The record
One row per call: the version string exactly as returned, whether the model searched, sources cited, and latency. Full answer text is in the free responses file. Download the record
Eighty-four rows: every prompt, every model, every answer.
| Prompt | Model | Version string | Time (UTC) | Searched | Sources | Latency |
|---|---|---|---|---|---|---|
| Direct recommendation | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 10:43 | yes | 15 | 10 s |
| Direct recommendation | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 11:11 | yes | 4 | 6 s |
| Direct recommendation | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 13:46 | yes | 18 | 28 s |
| Direct recommendation | Perplexity Sonar | sonar | 2026-10-01 10:55 | yes | 18 | 3 s |
| Direct recommendation | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 08:54 | yes | 18 | 7 s |
| Direct recommendation | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 12:09 | yes | 11 | 5 s |
| Direct recommendation | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 12:32 | yes | 22 | 31 s |
| Direct recommendation | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 10:52 | yes | 5 | 2 s |
| Direct recommendation | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 12:15 | yes | 9 | 50 s |
| Direct recommendation | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 11:37 | yes | 20 | 19 s |
| Direct recommendation | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 08:09 | yes | 17 | 56 s |
| Direct recommendation | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 09:46 | yes | 9 | 27 s |
| Direct recommendation | GPT-6 Luna | gpt-6-luna | 2026-10-01 12:48 | yes | 2 | 12 s |
| Direct recommendation | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 11:07 | yes | 11 | 16 s |
| Paraphrase | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 09:07 | yes | 18 | 9 s |
| Paraphrase | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 12:51 | yes | 4 | 5 s |
| Paraphrase | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 13:51 | no | 0 | 14 s |
| Paraphrase | Perplexity Sonar | sonar | 2026-10-01 10:10 | yes | 15 | 3 s |
| Paraphrase | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 08:58 | yes | 20 | 6 s |
| Paraphrase | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 13:04 | no | 0 | 2 s |
| Paraphrase | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 08:39 | yes | 24 | 24 s |
| Paraphrase | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 08:01 | yes | 5 | 2 s |
| Paraphrase | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 12:28 | no | 0 | 32 s |
| Paraphrase | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 08:46 | yes | 13 | 29 s |
| Paraphrase | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 10:40 | yes | 20 | 26 s |
| Paraphrase | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 07:56 | yes | 5 | 36 s |
| Paraphrase | GPT-6 Luna | gpt-6-luna | 2026-10-01 12:14 | yes | 3 | 13 s |
| Paraphrase | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 10:48 | yes | 15 | 19 s |
| Comparative | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 13:24 | yes | 10 | 10 s |
| Comparative | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 08:24 | yes | 7 | 6 s |
| Comparative | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 12:42 | yes | 14 | 29 s |
| Comparative | Perplexity Sonar | sonar | 2026-10-01 09:38 | yes | 18 | 6 s |
| Comparative | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 08:11 | yes | 24 | 9 s |
| Comparative | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 07:56 | yes | 8 | 7 s |
| Comparative | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 09:38 | yes | 22 | 29 s |
| Comparative | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 11:58 | yes | 5 | 1 s |
| Comparative | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 11:32 | yes | 9 | 31 s |
| Comparative | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 07:28 | yes | 15 | 27 s |
| Comparative | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 08:29 | yes | 13 | 27 s |
| Comparative | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 10:45 | yes | 5 | 12 s |
| Comparative | GPT-6 Luna | gpt-6-luna | 2026-10-01 09:27 | yes | 8 | 24 s |
| Comparative | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 10:16 | yes | 22 | 45 s |
| Budget constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 12:28 | yes | 9 | 7 s |
| Budget constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 13:50 | yes | 4 | 5 s |
| Budget constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 13:04 | yes | 20 | 26 s |
| Budget constrained | Perplexity Sonar | sonar | 2026-10-01 09:11 | yes | 18 | 2 s |
| Budget constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 11:27 | yes | 11 | 12 s |
| Budget constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 07:49 | yes | 5 | 2 s |
| Budget constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 12:33 | yes | 22 | 33 s |
| Budget constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 13:11 | yes | 5 | 2 s |
| Budget constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 13:16 | yes | 5 | 33 s |
| Budget constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 12:28 | yes | 12 | 18 s |
| Budget constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 08:20 | yes | 13 | 24 s |
| Budget constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 09:26 | yes | 9 | 59 s |
| Budget constrained | GPT-6 Luna | gpt-6-luna | 2026-10-01 11:55 | yes | 3 | 8 s |
| Budget constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 09:57 | yes | 14 | 24 s |
| Scale constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 09:00 | no | 0 | 5 s |
| Scale constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 10:34 | no | 0 | 8 s |
| Scale constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 11:29 | yes | 8 | 28 s |
| Scale constrained | Perplexity Sonar | sonar | 2026-10-01 10:47 | yes | 20 | 5 s |
| Scale constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 11:50 | yes | 14 | 8 s |
| Scale constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 09:00 | no | 0 | 8 s |
| Scale constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 10:52 | yes | 18 | 28 s |
| Scale constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 11:22 | yes | 5 | 2 s |
| Scale constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 08:53 | no | 0 | 31 s |
| Scale constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 07:26 | yes | 13 | 18 s |
| Scale constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 12:59 | no | 0 | 12 s |
| Scale constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 12:14 | yes | 5 | 18 s |
| Scale constrained | GPT-6 Luna | gpt-6-luna | 2026-10-01 07:50 | yes | 2 | 29 s |
| Scale constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 11:51 | yes | 11 | 25 s |
| Negative framing | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 11:21 | yes | 17 | 9 s |
| Negative framing | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 10:49 | yes | 6 | 6 s |
| Negative framing | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 11:39 | yes | 19 | 22 s |
| Negative framing | Perplexity Sonar | sonar | 2026-10-01 12:27 | yes | 20 | 5 s |
| Negative framing | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 11:37 | yes | 24 | 8 s |
| Negative framing | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 09:42 | yes | 5 | 7 s |
| Negative framing | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 11:50 | yes | 24 | 34 s |
| Negative framing | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 09:47 | yes | 5 | 2 s |
| Negative framing | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 10:48 | yes | 18 | 47 s |
| Negative framing | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 09:01 | yes | 15 | 16 s |
| Negative framing | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 09:57 | yes | 20 | 30 s |
| Negative framing | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 11:16 | yes | 17 | 28 s |
| Negative framing | GPT-6 Luna | gpt-6-luna | 2026-10-01 08:30 | yes | 3 | 16 s |
| Negative framing | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 09:49 | yes | 24 | 36 s |
Noise floor in this category
Flips between the edition run and its calibration repeat. Six prompts per model is a small sample; the index-wide floor is the number to trust.
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Claude Haiku 4.5
5 of 5 flipped
GPT-5.4 mini
3 of 4 flipped
Gemini 3.5 Flash
3 of 5 flipped
Perplexity Sonar
3 of 4 flipped
Grok 4.1 Fast
2 of 4 flipped
Mistral Small
1 of 3 flipped
DeepSeek V4 Flash
3 of 5 flipped
Llama 4 Maverick
1 of 1 flipped
Qwen 3.7 Flash
3 of 6 flipped
Kimi K2
3 of 4 flipped
GLM 4.7 FlashX
3 of 3 flipped
MiniMax M2.5
3 of 4 flipped
GPT-6 Luna
3 of 3 flipped
Muse Glimmer 30B
3 of 4 flipped
Normalization in this category
Every judgment call made between the raw labels and the numbers above, listed so it is visible and reversible.
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Category-scoped readings
Cisco AppDynamics read as AppDynamics
Datadog read as Datadog APM
Elastic Cloud read as Elastic APM
Grafana read as Grafana Cloud
Grafana (with Tempo/Prometheus) read as Grafana Cloud
Splunk APM read as Splunk Observability Cloud
Splunk Observability Cloud APM read as Splunk Observability Cloud
Unresolved, counted raw
Baselime
Datadog Community Edition
IBM APM
IBM AppDynamics
Kinsta APM
Logic Monitor
Odigos
Oracle DBCA
Self-hosted SigNoz
Site24x7 or ManageEngine OpManager
Discontinued, still offered
No shut-down product was recommended here.