OpsLevel vs Humanitec
Zero of fourteen models named OpsLevel first on the direct prompt; zero named Humanitec. OpsLevel was named by fourteen of the fourteen models and Humanitec by eleven and OpsLevel carries 41 labels and Humanitec 20, so the shares are not directly comparable.
Named in one category this edition.
Named in one category 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 internal developer portals page.
By framing
OpsLevelFirst choices, of fourteen modelsHumanitec
Across every category in the October 2026 Edition, OpsLevel and Humanitec were named in the same answer forty times, of the 112 answers naming OpsLevel and the 65 naming Humanitec. In those answers Humanitec took the first choice two times and OpsLevel four.
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 | | | |
OpsLevel Humanitec first choice named as an alternative argued againstblank: not namedEach cell is one answer, OpsLevel on the left and Humanitec on the right.The direct prompt
Neither was the first choice, one was named
9 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
5 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
Humanitec5%#6 of 9OpsLevel3%#7 of 9What the models said about OpsLevel
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Most proprietary portals (Port.io, OpsLevel, Atlassian Compass, etc.) carry vendor lock-in risks” DeepSeek V4 Flash · negative prompt · soft negative
“Commercial tools like Cortex and OpsLevel often require 6+ months to implement.” GLM 4.7 FlashX · scale prompt · soft negative
“OpsLevel - Limited Flexibility ... Rigid data model” Kimi K2 · negative prompt · soft negative
“OpsLevel: The best option if you want a quick, service-catalog-first setup with straightforward ownership and maturity tracking.” Gemini 3.5 Flash · scale prompt · first choice
“you likely want a managed SaaS portal (Port, OpsLevel, or Cortex)” DeepSeek V4 Flash · scale prompt · first choice
“Top Recommendation: Port or OpsLevel” Kimi K2 · paraphrase prompt · first choice
What the models said about Humanitec
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of seven in this category shown.
“Humanitec - Opaque Pricing & Complexity ... Vendor lock-in concerns” Kimi K2 · negative prompt · soft negative
“if you mainly want a portal UI, it may be more than you need” GPT-5.4 mini · comparative prompt · soft negative
“Overkill or less dev-portal focus” Grok 4.1 Fast · paraphrase prompt · soft negative
“my default recommendation would be Humanitec if you want a true internal developer platform (IDP) foundation” GPT-5.4 mini · paraphrase prompt · first choice
“Choose this if your architecture is complex (multi-cloud) and you don't care much about the visual catalog/UI.” Qwen 3.7 Flash · paraphrase prompt · alternative
“Humanitec is called out for opinionated platform automation, suitable for centralized platform teams” Muse Glimmer 30B · comparative prompt · alternative
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.