Amplitude vs PostHog
Ten of fourteen models named Amplitude first on the direct prompt; zero named PostHog. Both were named by all fourteen models and both carry 71 labels, so the shares below are directly comparable.
United States. Named in ten categories this edition.
Named in nine categories this edition.
Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all fourteen models, for a mid-market B2B company; rank is within the category; every quote names the model and the prompt it came from. Both figures come from the product analytics page.
By framing
AmplitudeFirst choices, of fourteen modelsPostHog
Across every category in the November 2026 Edition, Amplitude and PostHog were named in the same answer 260 times, of the 503 answers naming Amplitude and the 486 naming PostHog. In those answers PostHog took the first choice seventy-two times and Amplitude sixty.
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 4.20 | | | | | | |
| 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 | | | | | |
Amplitude PostHog first choice named as an alternative argued againstblank: not namedEach cell is one answer, Amplitude on the left and PostHog on the right.The direct prompt
Amplitude first, PostHog an alternative
10 of 14 modelsPostHog was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
3 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
1 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
PostHog62%#1 of 7Amplitude5%#3 of 7Amplitude46%#1 of 8PostHog33%#2 of 8Amplitude61%#1 of 9PostHog4%#5 of 9What the models said about Amplitude
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of four in this category shown.
“Why to avoid: Amplitude receives a high share of negative labels (31% in one analysis)” Mistral Small · negative prompt · hard negative
“Amplitude: Strong all-rounder for behavioral analytics, AI insights, experimentation, and enterprise governance. Best if you need depth + scalability.” Grok 4.20 · scale prompt · first choice
“The Gold Standard for Deep Insights: Amplitude ... widely considered the leader in the space for large-scale B2B SaaS companies.” Qwen 3.7 Flash · paraphrase prompt · first choice
“the best default choice is usually Amplitude if you want the strongest all-around product analytics platform” GPT-5.4 mini · direct prompt · first choice
What the models said about PostHog
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of four in this category shown.
“PostHog's interface assumes more technical comfort, with the HogQL query editor being powerful but requiring SQL knowledge” Claude Haiku 4.5 · negative prompt · soft negative
“its broad all-in-one toolkit can create operational complexity. Be cautious if you lack engineering ownership” Perplexity Sonar · negative prompt · soft negative
“For a limited budget, PostHog (open-source, generous free tier, all-in-one features) is often the best starting point.” GLM 4.7 FlashX · budget prompt · first choice
“For most lean startups today, PostHog is widely recommended as the best balance of price, power, and flexibility.” Qwen 3.7 Flash · budget prompt · first choice
Comparisons are drawn for the top eight products in each category, each against each. The output is the models' output; nothing here is a recommendation by the index.