How to use from
Pi
Start the llama.cpp server
# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf cortexso/cogito-v1:
Configure the model in Pi
# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "cortexso/cogito-v1:"
        }
      ]
    }
  }
}
Run Pi
# Start Pi in your project directory:
pi
Quick Links

Overview

DeepCogito introduces the Cogito-v1 Preview series, a powerful suite of hybrid reasoning models trained with Iterated Distillation and Amplification (IDA). These models are designed to push the boundaries of open-weight LLMs through scalable alignment and self-improvement strategies, offering unmatched performance across coding, STEM, multilingual, and agentic use cases.

Each model in this series operates in both standard (direct answer) and reasoning (self-reflective) modes, significantly outperforming size-equivalent open models such as LLaMA, DeepSeek, and Qwen. The 70B variant notably surpasses the newly released LLaMA 4 109B MoE model in benchmarks.

Variants

Cogito-v1 Preview

No Variant Branch Cortex CLI command
1 Cogito-v1-Preview-LLaMA-3B 3b cortex run cognito-v1:3b
2 Cogito-v1-Preview-LLaMA-8B 8b cortex run cognito-v1:8b
3 Cogito-v1-Preview-Qwen-14B 14b cortex run cognito-v1:14b
4 Cogito-v1-Preview-Qwen-32B 32b cortex run cognito-v1:32b
5 Cogito-v1-Preview-LLaMA-70B 70b cortex run cognito-v1:70b

Each branch contains a default quantized version:

  • LLaMA-3B: q4-km
  • LLaMA-8B: q4-km
  • Qwen-14B: q4-km
  • Qwen-32B: q4-km
  • LLaMA-70B: q4-km

Use it with Jan (UI)

  1. Install Jan using Quickstart
  2. Use in Jan model Hub:
    deepcogito/cognito-v1
    

Use it with Cortex (CLI)

  1. Install Cortex using Quickstart
  2. Run the model with command:
cortex run cognito-v1

Credits

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Model size
4B params
Architecture
llama
Hardware compatibility
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