Zero of twelve models named CoSchedule first on the direct prompt; zero named Buffer. CoSchedule was named by twelve of the twelve models and Buffer by ten and CoSchedule carries 26 labels and Buffer 11, so the shares are not directly comparable.
Named in two categories this edition.
Named in five categories 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 content marketing platforms page.
| 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 |
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.
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.
“their pricing structures are designed to scale aggressively as your team or channel list grows” Gemini 3.5 Flash · negative prompt · soft negative
“the most common winning plays are HubSpot Content Hub or CoSchedule if you want speed-to-value and reasonable TCO” DeepSeek V4 Flash · scale prompt · first choice
“I'd recommend CoSchedule as the top content planning and production tool.” Grok 4.1 Fast · paraphrase prompt · first choice
“I'd suggest CoSchedule as your primary planning/production hub” DeepSeek V4 Flash · paraphrase prompt · first choice
No label in this category carried a quote.
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.