Update README.md

README.md

@@ -24,14 +24,20 @@ _The **G**eneral **R**easoning **A**gent (for) **P**roject **E**xploration_
 # Capabilities
 
 The GRaPE Family was trained on about **14 billion** tokens of data after pre-training. About half was code related tasks, with the rest being heavy on STEAM. Ensuring the model has a sound logical basis.
-> Disclaimer: *GRaPE Flash does not have thinking capabilities, primarily in favor of instant responses.*
+> *GRaPE Flash does not have thinking capabilities, primarily in favor of instant responses.*
 ***
 
+GRaPE Flash and Nano are monomodal models, only accepting text. GRaPE Mini being trained most recently supports image and video inputs.
+
+# GRaPE Flash as a Model
+
+GRaPE Flash was designed for one thing: Speed. If you need a model that can quickly fill in tons of JSON data, this is your model. GRaPE Flash was chosen to **not** recieve thinking training as the model architecture would not benefit from it.
+
 # Architecture
 
 * GRaPE Flash: Built on the `OlMoE` Architecture, allowing for incredibly fast speeds where it matters. Allows for retaining factual information, but lacks in logical tasks.
 
-* GRaPE Mini: Built on the `Qwen3 VL` Architecture, allowing for edge case deployments, where logic nor speed can be sacrificed.
+* GRaPE Mini: Built on the `Qwen3 VL` Architecture, allowing for edge case deployments, where logic cannot be sacrificed.
 
 * GRaPE Nano: Built on the `LFM 2` Architecture, allowing for the fastest speed, and the most knowledge in the tiniest package.
 
@@ -43,4 +49,6 @@ The GRaPE Family started all the way back in August of 2025, meaning these model
 
 GRaPE 2 will come sooner than the GRaPE 1 family had, and will show multiple improvements.
 
-There are no benchmarks for GRaPE 1 Models due to the costly nature of running them, as well as prioritization of newer models.
+There are no benchmarks for GRaPE 1 Models due to the costly nature of running them, as well as prioritization of newer models.
+
+Updates for GRaPE 2 models will be posted here on Huggingface, as well as [Skinnertopia](https://www.skinnertopia.com/)