What is available
Checked November 4: Ricursive’s announcement and linked Hugging Face repository list Ripple-65B Preview as public model weights—the learned settings distributed as files for running on equipment you control. Its card describes a model with 65 billion learned settings and up to one million tokens of context. Tokens are small pieces of text; context is the material considered in a request. These are the provider’s specifications. [1] [2]
The repository includes an Apache 2.0 license. We checked the card and license file; the exact first-public hour remains unestablished. [2] [3]
Use the actual setup recipe
One supplied setup example uses two NVIDIA B200 graphics processors and about 16,000 tokens of context by default. That is a documented recipe, not a universal minimum or a demonstration of the advertised maximum context. Compare the chosen recipe’s equipment requirements with what you have before planning a local installation. [4]
Ricursive’s coding scores are its own reports. We have not reproduced them, downloaded model files, or run the model. [1]
Our take
The useful opportunity is to compare another model against a small problem you already understand. Ask it to fix a short function with a known failing example in a disposable copy. Check the actual result and the changed code.
A model’s size, a long context claim, and a benchmark table cannot make that decision for you. Keep a record of the exact version and setup so the comparison remains meaningful.