Incident management and on-call for small business buyers
Asked as “incident management platform”, and as “on-call scheduling and alerting tool”, on behalf of a small B2B company. 55 first choices recorded across the direct, paraphrase, budget and scale prompts, fourteen models each.
Standing · first-choice share
35%
Contested · Better Stack 16%
35incident.io16Better Stack11PagerDuty38others
35% of first choices, contested.
Since September 2026▲+4Since September 2026: 30% → 34%, +4 points. Inside the 11-point floor: within noise. Read over the models both editions asked.incident.io held the lead, +4 points on 30%, 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.This pageMid-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.Standing →
incident.io35%Contested▲+4Since September 2026: 30% → 34%, +4 points. Inside the 11-point floor: within noise. Read over the models both editions asked.This pageMid-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.Standing →The standing
Share is the count of first choices across the direct, paraphrase, budget and scale prompts, over all fourteen models, for a small B2B company. Ordered by share.
ProductFirst-choice shareNegative rateLabelsQuadrantSince September 2026
01incident.io35%5%61endorsed leader▲+4Since September 2026: 30% → 34%, +4 points. Inside the 11-point floor: within noise. Read over the models both editions asked.30% → 34%
incident.io35%5%61endorsed leader▲+4Since September 2026: 30% → 34%, +4 points. Inside the 11-point floor: within noise. Read over the models both editions asked.30% → 34%02
Better Stack16%0%34accepted challenger▼−6Since September 2026: 21% → 15%, −6 points. Inside the 11-point floor: within noise. Read over the models both editions asked.21% → 15%
Better Stack16%0%34accepted challenger▼−6Since September 2026: 21% → 15%, −6 points. Inside the 11-point floor: within noise. Read over the models both editions asked.21% → 15%03PagerDuty11%51%68criticized challenger▲+6Since September 2026: 6% → 13%, +6 points. Inside the 11-point floor: within noise. Read over the models both editions asked.6% → 13%
PagerDuty11%51%68criticized challenger▲+6Since September 2026: 6% → 13%, +6 points. Inside the 11-point floor: within noise. Read over the models both editions asked.6% → 13%04
Squadcast7%7%29accepted challenger▼−6Since September 2026: 13% → 6%, −6 points. Inside the 11-point floor: within noise. Read over the models both editions asked.13% → 6%
Squadcast7%7%29accepted challenger▼−6Since September 2026: 13% → 6%, −6 points. Inside the 11-point floor: within noise. Read over the models both editions asked.13% → 6%05
Rootly7%12%32accepted challenger▲+9Since September 2026: 0% → 9%, +9 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 9%
Rootly7%12%32accepted challenger▲+9Since September 2026: 0% → 9%, +9 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 9%06
Opsgenie7%63%46criticized challenger▲+9Since September 2026: 0% → 9%, +9 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 9%
Opsgenie7%63%46criticized challenger▲+9Since September 2026: 0% → 9%, +9 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 9%07
Spike.sh2%0%10accepted challenger▼−2Since September 2026: 4% → 2%, −2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.4% → 2%
Spike.sh2%0%10accepted 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
Freshservice2%14%14accepted challenger▲+2Since September 2026: 0% → 2%, +2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 2%
Freshservice2%14%14accepted challenger▲+2Since September 2026: 0% → 2%, +2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 2%09
FireHydrant2%15%13accepted challenger▲+2Since September 2026: 0% → 2%, +2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 2%
FireHydrant2%15%13accepted 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 four products at 0%, ordered by negative rate
13
ServiceNow ITSM0%100%14criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 0%
ServiceNow ITSM0%100%14criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 0%12
Splunk On-Call0%45%11criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 0%
Splunk On-Call0%45%11criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 0%11
Jira Service Management0%32%28criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 0%
Jira Service Management0%32%28criticized 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
Grafana IRM0%15%13accepted challenger▼−2Since September 2026: 2% → 0%, −2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.2% → 0%
Grafana IRM0%15%13accepted challenger▼−2Since September 2026: 2% → 0%, −2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.2% → 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 →
01020304050607080910111213Accepted challengerEndorsed leader
0%First-choice share → · lines at 30% share and 25% negative50%
Key
01incident.io35%
incident.io35%02Better Stack16%
Better Stack16%03PagerDuty11%
PagerDuty11%04Squadcast7%
Squadcast7%05Rootly7%
Rootly7%06Opsgenie7%
Opsgenie7%07Spike.sh2%
Spike.sh2%08Freshservice2%
Freshservice2%09FireHydrant2%
FireHydrant2%10Grafana IRM0%
Grafana IRM0%11Jira Service Management0%
Jira Service Management0%12Splunk On-Call0%
Splunk On-Call0%13ServiceNow ITSM0%
ServiceNow ITSM0%What they warned about
Four of fourteen models held their first choice under the paraphrase. Gemini 3.5 Flash, Perplexity Sonar, Grok 4.1 Fast, Mistral Small, DeepSeek V4 Flash, Qwen 3.7 Flash, Kimi K2, GLM 4.7 FlashX, 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.
ServiceNow ITSM100%
14 of 14 labels negative · 12 of 14 models · 8 hard negative
“Why Small Businesses Should Avoid It: ServiceNow is the industry standard for large corporations, but it represents a massive bottleneck for a small team.” Gemini 3.5 Flash, negative prompt
PagerDuty51%
35 of 68 labels negative · 12 of 14 models · 5 hard negative
“Avoid These Traps as a Small Company... it is often overly complex and carries high platform fees and contract lock-ins” Gemini 3.5 Flash, direct prompt
Opsgenie63%
29 of 46 labels negative · 11 of 14 models · 22 hard negative
“Why Small Businesses Should Avoid It: Building an incident management process on a platform that will be shut down is a waste of time and resources.” Gemini 3.5 Flash, negative prompt
Jira Service Management32%
9 of 28 labels negative · 7 of 14 models · 3 hard negative
“Full-featured ITSM suites like **ServiceNow** and **Jira Service Management** are often overkill for small businesses” MiniMax M2.5, 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
77 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. 1009 links across 160 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 · Rootly50 answers · 73 citations · 14 models
vendor site · incident.io47 answers · 133 citations · 13 models
vendor site · ComplyJet29 answers · 29 citations · 12 models
29 answers · 29 citations · 12 models
vendor site · Motadata28 answers · 29 citations · 11 models
vendor site · G226 answers · 50 citations · 13 models
vendor site · Hyperping26 answers · 29 citations · 11 models
26 answers · 26 citations · 11 models
vendor site · Guideflow21 answers · 31 citations · 9 models
vendor site · Instatus19 answers · 21 citations · 12 models
vendor site · LiveAgent18 answers · 18 citations · 10 models
vendor site · PagerDuty17 answers · 21 citations · 8 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.
29 answers · 12 models
29 answers · 12 models
27 answers · 11 models
26 answers · 11 models
22 answers · 10 models
21 answers · 10 models
18 answers · 10 models
18 answers · 10 models
16 answers · 8 models
14 answers · 8 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 |
|---|---|---|---|---|---|---|---|---|
| incident.io incident.io | 35% | 172 | 1,900 | 70 | 65,369 | $108 | 12 | 1 |
| Better Stack betterstack.com | 16% | 285 | 1,600 | 1,017 | 41,811 | 119 | ||
| PagerDuty pagerduty.com | 11% | 249 | 27,100 | 685 | 82,470 | $1,433 | 118 | |
| Squadcast squadcast.com | 7% | 57 | 2,900 | 41 | 47 | |||
| Rootly rootly.com | 7% | 105 | 1,900 | 30 | 13,774 | 23 | 2 | |
| Opsgenie atlassian.com Opsgenie 7%, Jira Service Management 0% | 7% | 292 | 6,600 | 188 | 4,724,388 | $5,906 | 61 | 4 |
| Zenduty zenduty.com | 4% | 13 | 320 | 4 | 199 | 0 | ||
| Hyperping hyperping.com | 4% | 58 | 140 | 0 | 67,358 | |||
| Spike.sh spike.sh | 2% | 11 | 20 | 0 | 6,691 | |||
| Freshservice freshworks.com | 2% | 381 | 8,100 | 221 | 111,586 | $14,486 | 113 |
Google's top ten for the three searches hold 18 sites; 2 of them are among the sites the models cited here (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 a small B2B company?”Paraphrase“Which on-call scheduling and alerting tool would you recommend to a small business that sells to other businesses?”Comparative“What are the top incident management platforms for a small team and how do they differ?”Budget-constrained“What is the best incident management platform for a small company with a tight budget?”Scale-constrained“We are a 30 person company evaluating an incident management platform. What should we look at?”Negative“Which incident management platforms should a small business avoid or be cautious about?”
Claude Haiku 4.5no first choiceno first choiceHeldincident.ioSquadcastno first choiceagainst: Opsgenie, Rootly, ServiceNow ITSM, Zendesk, incident.io
Five alternatives
Better Stack, Freshservice, PagerDuty, Squadcast, incident.ioThree alternatives
Better Stack, PagerDuty, SquadcastTwo alternatives
Better Stack, incident.ioGPT-5.4 miniPagerDutyagainst: OpsgeniePagerDutyHeldagainst: Opsgenie, Splunk On-CallPagerDutyagainst: Jira Service Management, Opsgenieincident.ioagainst: Opsgenie, PagerDutyno first choiceagainst: Freshservice, PagerDuty, ServiceNow ITSM, Splunk On-Call, xMatters
Three alternatives
FireHydrant, Jira Service Management, RootlyTwo alternatives
Squadcast, incident.ioFour alternatives
FireHydrant, Rootly, incident.io, xMattersTwo alternatives
Jira Service Management, RootlyGemini 3.5 FlashBetter Stack, incident.ioagainst: Jira Service Management, Opsgenie, PagerDutyBetter StackChangedagainst: Opsgenie, PagerDutyBetter Stackagainst: Opsgenie, PagerDutyBetter Stack, Zendutyagainst: Opsgenie, PagerDuty, incident.ioincident.ioagainst: Jira Service Management, Opsgenie, PagerDutyagainst: BigPanda, Jira Service Management, Moogsoft, Opsgenie, PagerDuty, ServiceNow ITSM, SolarWinds Incident Response, Splunk On-Call
Two alternatives
Grafana IRM, RootlyThree alternatives
Hyperping, Squadcast, incident.ioFour alternatives
Rootly, Spike.sh, Squadcast, incident.ioThree alternatives
Grafana IRM, OneUptime, SquadcastTwo alternatives
Better Stack, RootlyPerplexity Sonarincident.ioTaskCallChangedincident.ioagainst: SpiceworksSpiceworks, incident.iono first choiceagainst: Jira Service Management, Opsgenie, PagerDuty, ServiceNow ITSM, SolarWinds Service Desk, xMatters
Three alternatives
Freshservice, Spiceworks, Zoho DeskTwo alternatives
Hyperping, incident.ioFour alternatives
Better Stack, Jira Service Management, PagerDuty, RootlyTwo alternatives
Better Stack, Zoho DeskGrok 4.1 Fastincident.ioagainst: ServiceNow ITSMOpsgenieChangedagainst: PagerDutyOpsgenie, incident.ioagainst: PagerDutyPagerDuty, incident.iono first choiceagainst: Freshservice, Jira Service Management, PagerDuty, ServiceNow ITSM, SolarWinds Service Desk
Four alternatives
Freshservice, Hyperping, Jira Service Management, PagerDutyTwo alternatives
Squadcast, incident.ioOne alternative
Splunk On-CallTwo alternatives
Better Stack, Jira Service ManagementFive alternatives
HappyFox, Opsgenie, PagerDuty, Zoho Desk, incident.ioMistral SmallFreshservice, Rootlyagainst: PagerDutyOpsgenie, PagerDutyChangedincident.ioagainst: Jira Service Management, ZabbixPagerDuty, incident.iono first choiceagainst: NinjaOne, Opsgenie, PagerDuty, ServiceNow ITSM
Three alternatives
AlertOps, Splunk On-Call, ZendutyTwo alternatives
PagerDuty, RootlyTwo alternatives
Grafana IRM, RootlyDeepSeek V4 Flashincident.ioagainst: PagerDutyOpsgenieChangedagainst: PagerDutySquadcast, incident.ioagainst: OpsgeniePagerDutyagainst: Opsgenieincident.ioagainst: Opsgenie, PagerDutyagainst: BMC Helix ITSM, Cherwell, HP Service Manager, Jira Service Management, Opsgenie, PagerDuty, Rootly, ServiceNow ITSM, Splunk On-Call, Squadcast, xMatters
Three alternatives
AlertOps, Better Stack, ZendutyOne alternative
incident.ioFive alternatives
FireHydrant, PagerDuty, Rootly, Spike.sh, ZendutyFour alternatives
Jira Service Management, Splunk On-Call, Squadcast, incident.ioThree alternatives
Better Stack, SplunkOn-Call, SquadcastLlama 4 Maverickno first choiceno first choiceHeldXurrent IMRno first choiceno first choicenothing named
Two alternatives
PagerDuty, incident.ioQwen 3.7 FlashBetter Stack, Rootlyagainst: FireHydrant, PagerDutyBetter StackChangedBetter Stackagainst: PagerDutySquadcastno first choiceagainst: ServiceNow ITSMagainst: BMC Helix ITSM, FireHydrant, Micro Focus, Opsgenie, PagerDuty, Rootly, SAP Incident Manager, ServiceNow ITSM, Squadcast
Two alternatives
Hyperping, incident.ioTwo alternatives
Opsgenie, PagerDutyThree alternatives
Jira Service Management, Squadcast, incident.ioThree alternatives
Better Stack, Opsgenie, PagerDutyKimi K2incident.ioagainst: Opsgenie, PagerDutyOpsgenieChangedagainst: PagerDuty, Splunk On-Callincident.ioagainst: Grafana IRM, Opsgenie, PagerDutyincident.ioagainst: Opsgenie, PagerDutyno first choiceagainst: Opsgenie, PagerDuty, ServiceNow ITSM
Three alternatives
Better Stack, Spike.sh, ZendutyTwo alternatives
Grafana IRM, Spike.shTwo alternatives
FireHydrant, SquadcastTwo alternatives
Grafana IRM, SquadcastGLM 4.7 FlashXSquadcast, incident.ioagainst: PagerDutySpike.shChangedagainst: PagerDutyno first choiceincident.ioagainst: GoAlert, Grafana IRM, OneUptimeno first choicenothing named
Two alternatives
Jira Service Management, RootlyThree alternatives
OnPage, Pagerly, incident.ioOne alternative
PagerDutyMiniMax M2.5Rootly, incident.ioBetter Stack, HyperpingChangedagainst: Opsgenie, PagerDutyBetter Stack, incident.ioagainst: PagerDutyBetter Stack, FireHydrantRootly, incident.ioagainst: PagerDutyagainst: Jira Service Management, PagerDuty, ServiceNow ITSM
One alternative
incident.ioOne alternative
SquadcastTwo alternatives
PagerDuty, incident.ioOne alternative
OpsgenieGPT-6 LunaBetter StackBetter StackHeldagainst: OpsgenieBetter Stackagainst: Opsgenie, Rootlyincident.iono first choiceagainst: Opsgenieagainst: Datadog Incident Response, Opsgenie, PagerDuty, ServiceNow ITSM, xMatters
Two alternatives
PagerDuty, incident.ioOne alternative
PagerDutyTwo alternatives
PagerDuty, incident.ioTwo alternatives
Jira Service Management, PagerDutyMuse Glimmer 30Bincident.ioagainst: Opsgenie, PagerDutyHyperping, incident.ioChangedincident.ioagainst: OpsgenieSquadcast, Zendutyno first choiceagainst: PagerDuty, ServiceNow ITSM, SolarWinds Service Desk, incident.io
Three alternatives
Better Stack, FireHydrant, SquadcastTwo alternatives
Opsgenie, Spike.shFive alternatives
Better Stack, Jira Service Management, PagerDuty, Squadcast, ZendutyThree alternatives
Grafana IRM, ONES Project, OpsgenieBold 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 11:02 | yes | 9 | 8 s |
| Direct recommendation | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 08:45 | yes | 4 | 4 s |
| Direct recommendation | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 07:37 | yes | 14 | 30 s |
| Direct recommendation | Perplexity Sonar | sonar | 2026-10-01 11:39 | yes | 17 | 4 s |
| Direct recommendation | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 12:00 | yes | 25 | 6 s |
| Direct recommendation | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 07:40 | yes | 5 | 4 s |
| Direct recommendation | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 13:13 | yes | 19 | 22 s |
| Direct recommendation | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 11:45 | yes | 5 | 1 s |
| Direct recommendation | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 09:24 | yes | 10 | 24 s |
| Direct recommendation | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 07:57 | yes | 13 | 25 s |
| Direct recommendation | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 11:59 | yes | 17 | 64 s |
| Direct recommendation | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 10:45 | yes | 5 | 18 s |
| Direct recommendation | GPT-6 Luna | gpt-6-luna | 2026-10-01 11:51 | yes | 3 | 14 s |
| Direct recommendation | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 11:41 | yes | 24 | 27 s |
| Paraphrase | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 07:58 | no | 0 | 4 s |
| Paraphrase | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 07:36 | yes | 5 | 5 s |
| Paraphrase | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 09:19 | yes | 8 | 20 s |
| Paraphrase | Perplexity Sonar | sonar | 2026-10-01 11:38 | yes | 15 | 3 s |
| Paraphrase | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 13:21 | yes | 23 | 9 s |
| Paraphrase | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 08:10 | no | 0 | 3 s |
| Paraphrase | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 08:12 | yes | 22 | 21 s |
| Paraphrase | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 13:07 | yes | 5 | 2 s |
| Paraphrase | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 10:26 | no | 0 | 30 s |
| Paraphrase | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 08:36 | yes | 20 | 14 s |
| Paraphrase | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 07:56 | yes | 22 | 119 s |
| Paraphrase | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 08:53 | yes | 5 | 23 s |
| Paraphrase | GPT-6 Luna | gpt-6-luna | 2026-10-01 08:00 | yes | 3 | 18 s |
| Paraphrase | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 11:33 | yes | 13 | 25 s |
| Comparative | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 12:19 | yes | 9 | 9 s |
| Comparative | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 08:43 | yes | 5 | 7 s |
| Comparative | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 13:23 | yes | 27 | 26 s |
| Comparative | Perplexity Sonar | sonar | 2026-10-01 12:09 | yes | 17 | 8 s |
| Comparative | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 10:09 | yes | 25 | 16 s |
| Comparative | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 10:08 | yes | 15 | 11 s |
| Comparative | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 11:34 | yes | 22 | 36 s |
| Comparative | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 08:36 | yes | 5 | 2 s |
| Comparative | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 08:43 | yes | 5 | 32 s |
| Comparative | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 12:50 | yes | 20 | 26 s |
| Comparative | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 10:46 | yes | 15 | 143 s |
| Comparative | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 13:38 | yes | 13 | 27 s |
| Comparative | GPT-6 Luna | gpt-6-luna | 2026-10-01 13:20 | yes | 6 | 20 s |
| Comparative | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 12:31 | yes | 23 | 35 s |
| Budget constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 08:04 | yes | 9 | 8 s |
| Budget constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 10:18 | yes | 4 | 5 s |
| Budget constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 12:45 | yes | 13 | 27 s |
| Budget constrained | Perplexity Sonar | sonar | 2026-10-01 10:28 | yes | 20 | 3 s |
| Budget constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 11:07 | yes | 21 | 7 s |
| Budget constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 11:10 | yes | 5 | 5 s |
| Budget constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 13:21 | yes | 17 | 22 s |
| Budget constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 11:21 | yes | 5 | 2 s |
| Budget constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 08:37 | yes | 12 | 25 s |
| Budget constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 08:26 | yes | 20 | 21 s |
| Budget constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 13:36 | yes | 24 | 225 s |
| Budget constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 11:08 | yes | 5 | 25 s |
| Budget constrained | GPT-6 Luna | gpt-6-luna | 2026-10-01 10:13 | yes | 3 | 12 s |
| Budget constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 10:57 | yes | 22 | 40 s |
| Scale constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 12:09 | no | 0 | 5 s |
| Scale constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 07:39 | no | 0 | 7 s |
| Scale constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 13:38 | yes | 10 | 26 s |
| Scale constrained | Perplexity Sonar | sonar | 2026-10-01 07:50 | yes | 19 | 4 s |
| Scale constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 12:24 | yes | 13 | 8 s |
| Scale constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 10:44 | no | 0 | 7 s |
| Scale constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 12:48 | yes | 17 | 32 s |
| Scale constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 07:46 | yes | 5 | 2 s |
| Scale constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 13:42 | yes | 5 | 22 s |
| Scale constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 10:31 | yes | 18 | 20 s |
| Scale constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 10:26 | yes | 8 | 84 s |
| Scale constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 11:05 | yes | 5 | 17 s |
| Scale constrained | GPT-6 Luna | gpt-6-luna | 2026-10-01 12:17 | yes | 3 | 15 s |
| Scale constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 10:49 | yes | 11 | 20 s |
| Negative framing | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 13:43 | yes | 18 | 9 s |
| Negative framing | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 13:06 | yes | 3 | 5 s |
| Negative framing | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 10:25 | yes | 22 | 32 s |
| Negative framing | Perplexity Sonar | sonar | 2026-10-01 10:06 | yes | 19 | 4 s |
| Negative framing | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 07:49 | yes | 21 | 7 s |
| Negative framing | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 11:46 | yes | 9 | 5 s |
| Negative framing | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 10:40 | yes | 24 | 48 s |
| Negative framing | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 12:42 | yes | 5 | 2 s |
| Negative framing | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 12:47 | yes | 18 | 28 s |
| Negative framing | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 11:59 | yes | 23 | 22 s |
| Negative framing | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 09:34 | no | 0 | 36 s |
| Negative framing | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 11:57 | yes | 9 | 18 s |
| Negative framing | GPT-6 Luna | gpt-6-luna | 2026-10-01 07:59 | yes | 5 | 25 s |
| Negative framing | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 11:02 | yes | 21 | 36 s |
Normalization in this category
Every judgment call made between the raw labels and the numbers above, listed so it is visible and reversible.
ShowHide
Category-scoped readings
BMC Helix read as BMC Helix ITSM
Ivanti read as Ivanti Neurons for ITSM
ServiceNow read as ServiceNow ITSM
ServiceNow IT Service Management read as ServiceNow ITSM
Unresolved, counted raw
Datadog Incident Response
Derdack
IBM On Call Manager
Incidentio
OnCall
OnSched
SAP Incident Manager
Slack workflows
SolarWinds IT Incident Response
SolarWinds Incident Response (formerly Squadcast)
SplunkOn-Call
Statuspage.io
Xano
monday.com service modules
Discontinued, still offered
No shut-down product was recommended here.