ripple-preview

114 Downloads Updated an hour ago

65B dense model built for agentic coding, with up to 1M tokens of context.

tools thinking 65b

ollama run ripple-preview

curl http://localhost:11434/api/chat \
  -d '{
    "model": "ripple-preview",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

from ollama import chat

response = chat(
    model='ripple-preview',
    messages=[{'role': 'user', 'content': 'Hello!'}],
)
print(response.message.content)

import ollama from 'ollama'

const response = await ollama.chat({
  model: 'ripple-preview',
  messages: [{role: 'user', content: 'Hello!'}],
})
console.log(response.message.content)

Applications

Claude Code ollama launch claude --model ripple-preview

OpenCode ollama launch opencode --model ripple-preview

Hermes Agent ollama launch hermes --model ripple-preview

OpenClaw ollama launch openclaw --model ripple-preview

Models

View all →

Name

7 models

Size / Usage

Context

Input

ripple-preview:latest

39GB - 46GB · 2M context window · Text · 2 hours ago

ripple-preview:latest

39GB - 46GB

Text

ripple-preview:65b

latest

39GB - 46GB · 2M context window · Text · 2 hours ago

ripple-preview:65b latest

39GB - 46GB

Text

Readme

Ripple-65B Preview is a 65B dense model from Ricursive Intelligence, built for agentic coding. It is a general-purpose version of the model behind Ricursive’s AI chip-design platform.

Get started

ollama run ripple-preview

Key Features

Agentic coding: trained with large-scale reinforcement learning to work like a coding agent, carrying out multi-step tasks in a terminal.
Dense, trained from scratch: 65B parameters, all active on every token, pretrained by Ricursive on 12 trillion tokens.
Long context: up to 1M tokens, enough for large codebases and long agent sessions.
Faster generation: on Ollama’s MLX engine, Ripple uses DFlash 2 speculative decoding to generate faster..
Open license: Apache 2.0, commercial use allowed.

Benchmarks

Ricursive reports a score of 80.5 on Terminal-Bench 2.1. See the launch post for details.

Reference

Ricursive launch post · Hugging Face card

![images.png](/assets/library/ripple-preview/c905c99a-002b-40e7-bb5e-2d8666a77011)

Ripple-65B Preview is a 65B dense model from Ricursive Intelligence, built for agentic coding. It is a general-purpose version of the model behind Ricursive's AI chip-design platform.

### Get started

```
ollama run ripple-preview
```
### Key Features
- **Agentic coding**: trained with large-scale reinforcement learning to work like a coding agent, carrying out multi-step tasks in a terminal.
- **Dense, trained from scratch**: 65B parameters, all active on every token, pretrained by Ricursive on 12 trillion tokens.
- **Long context**: up to 1M tokens, enough for large codebases and long agent sessions.
- **Faster generation**: on Ollama’s MLX engine, Ripple uses DFlash 2 speculative decoding to generate faster..
- **Open license**: Apache 2.0, commercial use allowed.

### Benchmarks
Ricursive reports a score of 80.5 on Terminal-Bench 2.1. See the [launch post](https://www.ricursive.com/ripple) for details.

### Reference

[Ricursive launch post](https://www.ricursive.com/ripple) · [Hugging Face card](https://huggingface.co/ricursiveAI/Ripple-65B-Preview)

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