AI chip design firm Ricursive Intelligence has trained an open language model. Ripple-65B Preview was pretrained on 12 trillion tokens and, according to the company, achieved a score of 80.52 on the TerminalBench 2.1 coding benchmark, the best result among open US models. Ripple partly uses Terminus 2 and partly OpenCode as its harness. Other benchmark results show that Ripple does not match the also newly released Inkling 2 Small, but Ripple is likely easier to deploy on users’ own hardware. According to Ricursive, total development and training costs amounted to just $32 million, covering all research and development expenses.
| Benchmark | Ripple-65B Preview | Inkling 2 Small |
|---|---|---|
| SWE-Bench Pro v2.0 Hard | 79.1% | 86.3% |
| DeepSWE v1.1 | 44.3% | 72.1% |
| MCP Atlas | 71.67% | 85.4/85.0% |
The model uses a dense Transformer architecture with 65 billion parameters instead of the more common mixture-of-experts approach and is optimized for Nvidia hardware. Ripple-65B Preview is available on Hugging Face under the Apache 2.0 license.
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