Route abliterated language models across providers with automatic fallbacks, modality-aware selection, and one place to compare availability and token prices.
Modality-aware selection is the part I would test first, since a router that picks well for text can still miss on other inputs. With availability and token prices compared in one place, the practical question is whether a fallback changes the cost mid-request, or if the price quoted up front is the one you actually pay.
The fallback is something I'd want to see in the response metadata. A successful request can still mean a different provider or model handled it.
About AllModels on Product Hunt
“Explore every abliterated model”
AllModels launched on Product Hunt on October 26th, 2026 and earned 75 upvotes and 3 comments, placing #24 on the daily leaderboard. Route abliterated language models across providers with automatic fallbacks, modality-aware selection, and one place to compare availability and token prices.
AllModels was featured in Developer Tools (522.5k followers), Artificial Intelligence (482.9k followers) and Security (3k followers) on Product Hunt. Together, these topics include over 233.9k products, making this a competitive space to launch in.
Who hunted AllModels?
AllModels was hunted by Moe Adham. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how AllModels stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Moe Adham
Modality-aware selection is the part I would test first, since a router that picks well for text can still miss on other inputs. With availability and token prices compared in one place, the practical question is whether a fallback changes the cost mid-request, or if the price quoted up front is the one you actually pay.