Incident management and on-call for enterprise buyers
Asked as “incident management platform”, and as “on-call scheduling and alerting tool”, on behalf of an enterprise B2B company. 51 first choices recorded across the direct, paraphrase, budget and scale prompts, fourteen models each.
Standing · first-choice share
57%
Clear leader
57PagerDuty18incident.io08Jira Service Management18others
57% of first choices, clear leader.
Since September 2026▲+9Since September 2026: 50% → 59%, +9 points. Inside the 11-point floor: within noise. Read over the models both editions asked.PagerDuty held the lead, +9 points on 50%, 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
incident.io35%Contested▲+4Since September 2026: 30% → 34%, +4 points. Inside the 11-point floor: within noise. Read over the models both editions asked.Standing →Mid-marketincident.io32%Contested▲+5Since September 2026: 25% → 31%, +5 points. Inside the 11-point floor: within noise. Read over the models both editions asked.Standing →Enterprise
PagerDuty57%Clear leader▲+9Since September 2026: 50% → 59%, +9 points. Inside the 11-point floor: within noise. Read over the models both editions asked.This page
incident.io35%Contested▲+4Since September 2026: 30% → 34%, +4 points. Inside the 11-point floor: within noise. Read over the models both editions asked.Standing →Mid-marketincident.io32%Contested▲+5Since September 2026: 25% → 31%, +5 points. Inside the 11-point floor: within noise. Read over the models both editions asked.Standing →EnterprisePagerDuty57%Clear leader▲+9Since September 2026: 50% → 59%, +9 points. Inside the 11-point floor: within noise. Read over the models both editions asked.This pageThe standing
Share is the count of first choices across the direct, paraphrase, budget and scale prompts, over all fourteen models, for an enterprise B2B company. Ordered by share.
ProductFirst-choice shareNegative rateLabelsQuadrantSince September 2026
01PagerDuty57%26%74criticized default▲+9Since September 2026: 50% → 59%, +9 points. Inside the 11-point floor: within noise. Read over the models both editions asked.50% → 59%
PagerDuty57%26%74criticized default▲+9Since September 2026: 50% → 59%, +9 points. Inside the 11-point floor: within noise. Read over the models both editions asked.50% → 59%02incident.io18%13%55accepted challenger▼−1Since September 2026: 17% → 16%, −1 point. Inside the 11-point floor: within noise. Read over the models both editions asked.17% → 16%
incident.io18%13%55accepted challenger▼−1Since September 2026: 17% → 16%, −1 point. Inside the 11-point floor: within noise. Read over the models both editions asked.17% → 16%03
ServiceNow ITSM8%27%45criticized challenger▲+2Since September 2026: 7% → 9%, +2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.7% → 9%
ServiceNow ITSM8%27%45criticized challenger▲+2Since September 2026: 7% → 9%, +2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.7% → 9%04
Jira Service Management8%29%35criticized challenger▲+7Since September 2026: 0% → 7%, +7 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 7%
Jira Service Management8%29%35criticized challenger▲+7Since September 2026: 0% → 7%, +7 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 7%05
Opsgenie4%70%46criticized challenger▲+5Since September 2026: 0% → 5%, +5 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 5%
Opsgenie4%70%46criticized challenger▲+5Since September 2026: 0% → 5%, +5 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 5%06
Splunk On-Call2%23%22accepted challenger▲+2Since September 2026: 0% → 2%, +2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 2%
Splunk On-Call2%23%22accepted 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
07
Rootly0%14%37accepted challenger▼−10Since September 2026: 10% → 0%, −10 points. Inside the 11-point floor: within noise. Read over the models both editions asked.10% → 0%
Rootly0%14%37accepted challenger▼−10Since September 2026: 10% → 0%, −10 points. Inside the 11-point floor: within noise. Read over the models both editions asked.10% → 0%08
xMatters0%11%19accepted challenger▼−2Since September 2026: 2% → 0%, −2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.2% → 0%
xMatters0%11%19accepted challenger▼−2Since September 2026: 2% → 0%, −2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.2% → 0%09
FireHydrant0%7%15accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 0%
FireHydrant0%7%15accepted 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
incident.io vs Grafana IRMincident.io vs Opsgenieincident.io vs Rootlyincident.io vs FireHydrantPagerDuty vs FreshservicePagerDuty vs SquadcastPagerDuty vs Grafana IRMPagerDuty vs OpsgeniePagerDuty vs RootlyPagerDuty vs FireHydrantFreshservice vs SquadcastFreshservice vs Grafana IRMFreshservice vs OpsgenieFreshservice vs RootlyFreshservice vs FireHydrantSquadcast vs Grafana IRMSquadcast vs OpsgenieSquadcast vs RootlySquadcast vs FireHydrantGrafana IRM vs OpsgenieGrafana IRM vs RootlyGrafana IRM vs FireHydrantOpsgenie vs RootlyOpsgenie vs FireHydrantRootly vs FireHydrant
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 →
010203040506070809Accepted challengerEndorsed leader
0%First-choice share → · lines at 30% share and 25% negative70%
Key
01PagerDuty57%
PagerDuty57%02incident.io18%
incident.io18%03ServiceNow ITSM8%
ServiceNow ITSM8%04Jira Service Management8%
Jira Service Management8%05Opsgenie4%
Opsgenie4%06Splunk On-Call2%
Splunk On-Call2%07Rootly0%
Rootly0%08xMatters0%
xMatters0%09FireHydrant0%
FireHydrant0%What they warned about
Seven of fourteen models held their first choice under the paraphrase. Claude Haiku 4.5, Gemini 3.5 Flash, Perplexity Sonar, Mistral Small, Qwen 3.7 Flash, MiniMax M2.5 and GPT-6 Luna 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.
Opsgenie70%
32 of 46 labels negative · 14 of 14 models · 25 hard negative
“**Opsgenie is no longer sold to new customers**; ... evaluate the current JSM offering rather than treating Opsgenie as a new standalone option.” GPT-6 Luna, comparative prompt
PagerDuty26%
19 of 74 labels negative · 13 of 14 models
“The caveat repeatedly noted is the add-on model: base price plus on-call, AIOps/Advance AI, status pages and professional services, which makes the final TCO opaque until you get a quote.” Muse Glimmer 30B, budget prompt
Jira Service Management29%
10 of 35 labels negative · 10 of 14 models · 1 hard negative
“JSM is fundamentally a ticketing system with basic alerting capabilities bolted on. It's not built for the demands of modern incident management.” Claude Haiku 4.5, negative prompt
ServiceNow ITSM27%
12 of 45 labels negative · 9 of 14 models · 1 hard negative
“**Avoid ServiceNow** for predictable pricing” GLM 4.7 FlashX, budget 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. 1125 links across 223 sites, every framing counted. Ranked by the number of answers carrying the site or page. 1 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 · incident.io50 answers · 142 citations · 14 models
vendor site · Rootly48 answers · 76 citations · 12 models
vendor site · Motadata41 answers · 44 citations · 11 models
vendor site · PagerDuty34 answers · 50 citations · 11 models
29 answers · 29 citations · 10 models
vendor site · Guideflow23 answers · 32 citations · 11 models
vendor site · InvGate23 answers · 28 citations · 12 models
23 answers · 23 citations · 9 models
vendor site · Augment Code20 answers · 21 citations · 9 models
vendor site · ComplyJet20 answers · 20 citations · 11 models
vendor site · Hyperping19 answers · 20 citations · 9 models
17 answers · 17 citations · 9 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.
40 answers · 11 models
29 answers · 10 models
23 answers · 9 models
20 answers · 11 models
19 answers · 9 models
19 answers · 11 models
18 answers · 10 models
17 answers · 9 models
15 answers · 7 models
14 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 “best incident management platform”, “incident management platform”, “incident management platforms”. 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 |
|---|---|---|---|---|---|---|---|---|
| PagerDuty pagerduty.com PagerDuty 57%, PagerDuty Operations Cloud 0% | 57% | 249 | 27,100 | 685 | 82,470 | $1,433 | 118 | |
| incident.io incident.io incident.io 18%, Incident IO 0% | 18% | 172 | 1,900 | 70 | 65,369 | $108 | 12 | 1 |
| Jira atlassian.com Jira Service Management 8%, Opsgenie 4% | 12% | 292 | 6,600 | 188 | 4,724,388 company | $5,906 | 61 | 4 |
| ServiceNow parent site ServiceNow ITSM 8%, ServiceNow ITOM 2% | 10% | 231 | 135,000 | 13,451 | ||||
| Splunk parent site Splunk On-Call 2% | 2% | 42 | 40,500 | 6,832 | ||||
| Better Stack betterstack.com | 2% | 285 | 1,600 | 1,017 | 41,811 | 119 | ||
| Rootly rootly.com | 0% | 105 | 1,900 | 30 | 13,774 | 23 | 2 | |
| xMatters xmatters.com | 0% | 34 | 1,900 | 69 | 14,538 | 3 | 9 | |
| FireHydrant firehydrant.com | 0% | 41 | 49,500 | 19 | 20,080 | 6 | ||
| Grafana IRM grafana.com | 0% | 40 | 260 | 4 | 84,520 | 116 |
Google's top ten for the three searches hold 18 sites; 3 of them are among the sites the models cited here (augmentcode.com, incident.io, rootly.com). The first result for “best incident management platform” is incident.io.
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 incident management platform for an enterprise B2B company?”Paraphrase“Which on-call scheduling and alerting tool would you recommend to a large B2B company with thousands of employees?”Comparative“What are the top enterprise-grade incident management platforms and how do they differ?”Budget-constrained“What is the best incident management platform for a large company that needs predictable total cost across thousands of users?”Scale-constrained“We are a 5,000 person company with SSO, SOC 2 and procurement review requirements evaluating an incident management platform. What should we look at?”Negative“Which incident management platforms should a large enterprise avoid or be cautious about?”
Claude Haiku 4.5no first choicePagerDutyChangedServiceNow ITSMagainst: PagerDutySplunk On-Callagainst: Opsgenieno first choiceagainst: Better Stack, Jira Service Management, Opsgenie, PagerDuty
Three alternatives
Splunk On-Call, incident.io, xMattersFive alternatives
Freshservice, Jira Service Management, Rootly, Vibe OnCall, incident.ioOne alternative
PagerDutyGPT-5.4 miniPagerDutyagainst: Jira Service ManagementPagerDutyHeldagainst: OpsgeniePagerDutyJira Service Management, Opsgenieagainst: PagerDuty, Splunk On-Callno first choiceagainst: Opsgenie, Rootly, Splunk On-Call, incident.io, xMatters
Two alternatives
ServiceNow ITSM, xMattersTwo alternatives
Jira Service Management, xMattersFour alternatives
BigPanda, ServiceNow ITSM, Splunk On-Call, xMattersOne alternative
FireHydrantGemini 3.5 FlashPagerDuty, incident.ioagainst: FireHydrantPagerDutyChangedagainst: OpsgenieRootly, incident.ioagainst: Opsgenieincident.ioagainst: Atlassian, PagerDutyPagerDutyagainst: Jira Service Management, Opsgenie, ServiceNow ITSM, Splunk On-Call
Two alternatives
Jira Service Management, RootlyFour alternatives
Freshservice, Jira Service Management, Rootly, incident.ioSix alternatives
Atlassian, FireHydrant, Freshservice, Jira Service Management, PagerDuty, ServiceNow ITSMFour alternatives
FireHydrant, Grafana IRM, OneUptime, SquadcastThree alternatives
FireHydrant, Jira Service Management, incident.ioPerplexity SonarServiceNow ITSMPagerDutyChangedPagerDuty, ServiceNow ITSMServiceNow ITSMagainst: Freshservice, PagerDutyno first choiceagainst: BigPanda, Jira Service Management, Opsgenie, PagerDuty, Rootly, ServiceNow ITSM, incident.io
Three alternatives
PagerDuty, Rootly, incident.ioTwo alternatives
Rootly, incident.ioThree alternatives
BigPanda, Jira Service Management, incident.ioGrok 4.1 FastPagerDutyPagerDutyHeldagainst: OpsgeniePagerDutyagainst: OpsgeniePagerDutyagainst: Opsgenie, Splunk On-Call, incident.ioPagerDutyagainst: BMC Remedy, Jira Service Management, Opsgenie, PagerDuty, ServiceNow ITSM
One alternative
ServiceNow ITSMTwo alternatives
Splunk On-Call, xMattersThree alternatives
ServiceNow ITSM, Splunk On-Call, xMattersOne alternative
ServiceNow ITSMThree alternatives
Opsgenie, Rootly, incident.ioMistral SmallPagerDutyOpsgenie, PagerDutyChangedPagerDutyPagerDutyagainst: Datadog, Opsgenie, incident.iono first choiceagainst: Opsgenie, PagerDuty, ServiceNow ITSM
Two alternatives
ServiceNow ITSM, incident.ioThree alternatives
BigPanda, ServiceNow ITOM, Splunk On-CallFive alternatives
Jira Service Management, Opsgenie, Rootly, ServiceNow ITSM, incident.ioDeepSeek V4 FlashPagerDutyPagerDutyHeldagainst: Opsgenie, Rootly, incident.ioPagerDuty, incident.ioagainst: Opsgenieincident.ioagainst: PagerDuty, Rootly, ServiceNow ITSMincident.ioagainst: Atlassian, Opsgenie, PagerDutynothing named
Three alternatives
FireHydrant, ServiceNow ITSM, incident.ioTwo alternatives
Splunk On-Call, xMattersThree alternatives
Jira Service Management, Rootly, ServiceNow ITSMOne alternative
RootlyLlama 4 MaverickPagerDutyPagerDutyHeldno first choiceagainst: Opsgenieincident.iono first choiceagainst: Opsgenie
Three alternatives
Instatus, Rootly, xMattersTwo alternatives
Jira Service Management, PagerDutyTwo alternatives
InvGate, KayakoQwen 3.7 FlashPagerDuty, ServiceNow ITSMPagerDutyChangedPagerDutyincident.ioagainst: PagerDuty, ServiceNow ITSMno first choiceagainst: Jira Service Management, Opsgenie, PagerDuty, ServiceNow ITSM, Squadcast
Two alternatives
Jira Service Management, OpsgenieThree alternatives
Grafana IRM, Opsgenie, ServiceNow ITSMFive alternatives
Opsgenie, ServiceNow ITSM, Splunk On-Call, incident.io, xMattersOne alternative
Jira Service ManagementKimi K2PagerDutyPagerDutyHeldagainst: Opsgenie, Rootly, incident.ioPagerDutyagainst: Jira Service Management, Splunk On-CallServiceNow ITOMagainst: incident.ioincident.ioagainst: ServiceNow ITSM, xMattersagainst: Opsgenie, PagerDuty, ServiceNow ITSM, Squadcast
Two alternatives
ServiceNow ITSM, incident.ioThree alternatives
ServiceNow ITSM, Splunk On-Call, xMattersTwo alternatives
Datadog Incident Management, ServiceNow ITSMOne alternative
PagerDutyTwo alternatives
FireHydrant, PagerDutyGLM 4.7 FlashXPagerDutyPagerDutyHeldno first choiceagainst: OpsgenieJira Service Managementagainst: PagerDuty, ServiceNow ITSMno first choiceagainst: Grafana IRM, Jira Service Management, Opsgenie, PagerDuty, ServiceNow ITSM
Four alternatives
Jira Service Management, Rootly, ServiceNow ITSM, incident.ioSix alternatives
Better Stack, Grafana IRM, Opsgenie, Rootly, incident.io, xMattersOne alternative
incident.ioMiniMax M2.5PagerDuty, ServiceNow ITSMPagerDutyChangedagainst: OpsgeniePagerDutyJira Service Managementagainst: PagerDutyno first choiceagainst: Jira Service Management, Opsgenie
One alternative
RootlyThree alternatives
Grafana IRM, Splunk On-Call, incident.ioThree alternatives
Jira Service Management, ServiceNow ITSM, incident.ioOne alternative
ServiceNow ITSMGPT-6 Lunaincident.ioPagerDutyChangedagainst: OpsgeniePagerDuty Operations Cloudagainst: OpsgenieJira Service Managementno first choiceagainst: Opsgenie, PagerDuty, Slack- or Teams-centered incident tools
Two alternatives
PagerDuty, RootlyTwo alternatives
Jira Service Management, incident.ioSix alternatives
FireHydrant, Jira Service Management, Rootly, ServiceNow ITSM, incident.io, xMattersTwo alternatives
PagerDuty, incident.ioMuse Glimmer 30BPagerDutyagainst: OpsgeniePagerDutyHeldPagerDutyagainst: OpsgenieBetter Stack, incident.ioagainst: PagerDutyno first choiceagainst: Freshservice, Jira Service Management, Opsgenie, PagerDuty, ServiceNow ITSM
One alternative
Jira Service Management OperationsThree alternatives
Atlassian, Opsgenie, Splunk On-CallFive alternatives
Everbridge, FireHydrant, ServiceNow ITSM, incident.io, xMattersBold 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 11:38 | no | 0 | 4 s |
| Direct recommendation | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 09:07 | yes | 4 | 4 s |
| Direct recommendation | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 08:46 | yes | 24 | 27 s |
| Direct recommendation | Perplexity Sonar | sonar | 2026-10-01 09:35 | yes | 19 | 4 s |
| Direct recommendation | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 07:28 | yes | 23 | 7 s |
| Direct recommendation | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 08:07 | yes | 12 | 6 s |
| Direct recommendation | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 08:09 | yes | 21 | 26 s |
| Direct recommendation | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 10:22 | yes | 5 | 2 s |
| Direct recommendation | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 09:14 | yes | 10 | 24 s |
| Direct recommendation | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 12:28 | yes | 13 | 20 s |
| Direct recommendation | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 13:00 | yes | 24 | 40 s |
| Direct recommendation | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 10:38 | yes | 10 | 15 s |
| Direct recommendation | GPT-6 Luna | gpt-6-luna | 2026-10-01 10:16 | yes | 2 | 15 s |
| Direct recommendation | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 09:11 | yes | 15 | 14 s |
| Paraphrase | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 09:55 | yes | 9 | 7 s |
| Paraphrase | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 09:57 | yes | 4 | 4 s |
| Paraphrase | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 13:46 | yes | 14 | 24 s |
| Paraphrase | Perplexity Sonar | sonar | 2026-10-01 11:59 | yes | 18 | 5 s |
| Paraphrase | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 12:16 | yes | 24 | 12 s |
| Paraphrase | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 11:26 | no | 0 | 3 s |
| Paraphrase | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 09:47 | yes | 24 | 20 s |
| Paraphrase | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 10:16 | yes | 5 | 1 s |
| Paraphrase | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 10:23 | no | 0 | 38 s |
| Paraphrase | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 08:03 | yes | 23 | 19 s |
| Paraphrase | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 10:03 | yes | 24 | 526 s |
| Paraphrase | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 07:51 | yes | 15 | 37 s |
| Paraphrase | GPT-6 Luna | gpt-6-luna | 2026-10-01 12:05 | yes | 4 | 13 s |
| Paraphrase | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 09:27 | yes | 15 | 18 s |
| Comparative | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 12:52 | yes | 9 | 8 s |
| Comparative | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 12:23 | yes | 4 | 9 s |
| Comparative | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 09:07 | yes | 9 | 25 s |
| Comparative | Perplexity Sonar | sonar | 2026-10-01 10:03 | yes | 17 | 4 s |
| Comparative | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 12:29 | yes | 21 | 9 s |
| Comparative | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 12:29 | yes | 8 | 6 s |
| Comparative | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 12:26 | yes | 19 | 51 s |
| Comparative | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 12:10 | yes | 5 | 2 s |
| Comparative | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 07:55 | no | 0 | 36 s |
| Comparative | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 13:38 | yes | 24 | 24 s |
| Comparative | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 07:52 | yes | 23 | 38 s |
| Comparative | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 13:26 | yes | 11 | 18 s |
| Comparative | GPT-6 Luna | gpt-6-luna | 2026-10-01 09:41 | yes | 7 | 28 s |
| Comparative | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 08:46 | yes | 14 | 49 s |
| Budget constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 09:51 | yes | 19 | 10 s |
| Budget constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 12:24 | yes | 3 | 5 s |
| Budget constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 09:43 | yes | 21 | 67 s |
| Budget constrained | Perplexity Sonar | sonar | 2026-10-01 13:10 | yes | 19 | 4 s |
| Budget constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 09:59 | yes | 20 | 8 s |
| Budget constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 11:18 | yes | 5 | 3 s |
| Budget constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 08:35 | yes | 23 | 26 s |
| Budget constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 12:46 | yes | 5 | 2 s |
| Budget constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 13:13 | yes | 9 | 53 s |
| Budget constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 08:04 | yes | 25 | 39 s |
| Budget constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 12:14 | yes | 24 | 46 s |
| Budget constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 12:33 | yes | 24 | 77 s |
| Budget constrained | GPT-6 Luna | gpt-6-luna | 2026-10-01 09:09 | yes | 2 | 20 s |
| Budget constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 13:09 | yes | 20 | 50 s |
| Scale constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 08:19 | yes | 18 | 12 s |
| Scale constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 09:27 | yes | 3 | 6 s |
| Scale constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 10:49 | no | 0 | 15 s |
| Scale constrained | Perplexity Sonar | sonar | 2026-10-01 09:46 | yes | 23 | 7 s |
| Scale constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 08:28 | yes | 15 | 7 s |
| Scale constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 12:13 | no | 0 | 10 s |
| Scale constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 13:02 | yes | 19 | 62 s |
| Scale constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 13:03 | yes | 5 | 3 s |
| Scale constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 09:49 | no | 0 | 31 s |
| Scale constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 07:51 | yes | 24 | 31 s |
| Scale constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 09:18 | yes | 14 | 27 s |
| Scale constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 09:36 | no | 0 | 59 s |
| Scale constrained | GPT-6 Luna | gpt-6-luna | 2026-10-01 09:00 | yes | 2 | 25 s |
| Scale constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 10:10 | yes | 12 | 19 s |
| Negative framing | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 09:45 | yes | 32 | 13 s |
| Negative framing | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 11:40 | yes | 6 | 6 s |
| Negative framing | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 07:36 | yes | 22 | 32 s |
| Negative framing | Perplexity Sonar | sonar | 2026-10-01 07:55 | yes | 20 | 4 s |
| Negative framing | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 08:55 | yes | 23 | 8 s |
| Negative framing | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 10:44 | yes | 5 | 4 s |
| Negative framing | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 12:10 | yes | 25 | 16 s |
| Negative framing | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 10:29 | yes | 5 | 2 s |
| Negative framing | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 08:55 | yes | 19 | 106 s |
| Negative framing | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 13:00 | yes | 23 | 33 s |
| Negative framing | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 11:24 | yes | 22 | 108 s |
| Negative framing | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 12:47 | yes | 15 | 42 s |
| Negative framing | GPT-6 Luna | gpt-6-luna | 2026-10-01 09:45 | yes | 2 | 18 s |
| Negative framing | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 10:14 | yes | 20 | 30 s |
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
ServiceNow read as ServiceNow ITSM
ServiceNow (ITSM Module) read as ServiceNow ITSM
ServiceNow (ITSM) read as ServiceNow ITSM
ServiceNow IT Service Management read as ServiceNow ITSM
ServiceNow IT Service Management (ITSM) read as ServiceNow ITSM
Unresolved, counted raw
Freshservice Incident Management
Incident IO
Jira Service Management Operations
Kayako
Microsoft System Center (SCOM)
New Relic Incident Management
PagerDuty Operations Cloud
Regen (by FluidifyAI)
Slack- or Teams-centered incident tools
Discontinued, still offered
No shut-down product was recommended here.