PushFar vs Chronus
Zero of twelve models named PushFar first on the direct prompt; two named Chronus. PushFar was named by eleven of the twelve models and Chronus by twelve and PushFar carries 21 labels and Chronus 34, 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 twelve 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 mentoring software page.
By framing
PushFarFirst choices, of twelve modelsChronus
Across every category in the September 2026 Edition, PushFar and Chronus were named in the same answer thirty-six times, of the 66 answers naming PushFar and the 116 naming Chronus. In those answers Chronus took the first choice two times and PushFar eleven.
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 | | | |
PushFar Chronus first choice named as an alternative argued againstblank: not namedEach cell is one answer, PushFar on the left and Chronus on the right.The direct prompt
Chronus first, PushFar not the choice
2 of 12 modelsPushFar was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
1 of 12 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
9 of 12 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
PushFar39%#1 of 11Chronus0%#11 of 11Chronus9%#4 of 7PushFar0%#– of 7What the models said about PushFar
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.
“PushFar is more affordable but less feature-rich” Kimi K2 · comparative prompt · soft negative
“If you need to scale beyond ~10 people: PushFar (~$200/month flat) is the cheapest way to run a proper company-wide program” DeepSeek V4 Flash · budget prompt · first choice
“PushFar stands out as the top recommendation for mentoring program software” Grok 4.1 Fast · budget prompt · first choice
“start with Mentornity (if under 10 users) or PushFar (~$200/month)” MiniMax M2.5 · budget prompt · first choice
What the models said about Chronus
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“What to avoid for a mid-size budget Chronus — Enterprise-grade but starts around $14,995+ ... Overkill” DeepSeek V4 Flash · paraphrase prompt · hard negative
“Heavyweight systems built for the Fortune 500 (like Chronus or MentorcliQ) are often overkill and budget-prohibitive for this segment.” Gemini 3.5 Flash · paraphrase prompt · soft negative
“Usually not budget-first: Chronus — powerful, but pricing is contact-for-quote and aimed at larger programs” GPT-5.4 mini · budget prompt · soft negative
“Best for: large organizations that need structured, scalable mentoring... For enterprise HR / L&D: Chronus, MentorcliQ, Together, Guider.” GPT-5.4 mini · comparative prompt · first choice
“If you want one name to evaluate first for a mid-market B2B company, I'd start with Chronus.” GPT-5.4 mini · direct prompt · first choice
“Chronus is arguably the best choice for mid-sized organizations that want a formalized program” Qwen 3.7 Flash · paraphrase 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.