Written by Jakub Rusinowski · Last updated July 10, 2026
Deep Cogito's hybrid reasoning model family released March 2026. Unique 'think-or-not-think' architecture lets the model decide at inference time whether to use chain-of-thought reasoning based on query difficulty — saving compute on simple tasks while using deep reasoning for hard ones. Apache 2.0 licensed with sizes from 3B to 70B, all runnable on consumer hardware.
| Cogito v1 3B | Min 3 GB VRAM · Q4_K_M · 32,000 ctx · ollama run cogito:3b |
| Cogito v1 8B | Min 6 GB VRAM · Q4_K_M · 32,000 ctx · ollama run cogito:8b |
| Cogito v1 14B | Min 9 GB VRAM · Q4_K_M · 64,000 ctx · ollama run cogito:14b |
| Cogito v1 32B | Min 20 GB VRAM · Q4_K_M · 64,000 ctx · ollama run cogito:32b |
| Cogito v1 70B | Min 43 GB VRAM · Q4_K_M · 128,000 ctx · ollama run cogito:70b |
The cheapest GPU that runs Cogito v1 locally (min 3 GB VRAM) is the Intel Arc B570 (10 GB).
Install Ollama then run: ollama run cogito:3b
Minimum VRAM: 3 GB. For best results use Q4_K_M quantization.
Cogito v1 needs about 3 GB VRAM at Q4_K_M quantization for its smallest variant. Variants: Cogito v1 3B (3 GB, Q4_K_M); Cogito v1 8B (6 GB, Q4_K_M); Cogito v1 14B (9 GB, Q4_K_M); Cogito v1 32B (20 GB, Q4_K_M). On Apple Silicon, unified memory counts toward this requirement.
Yes — Cogito v1 runs on an RTX 4090 (24 GB) and other 24 GB cards such as the RTX 3090. Smaller variants also fit comfortably on 8–16 GB GPUs at Q4_K_M.
Q4_K_M is the best balance of quality and VRAM for Cogito v1 in most cases. Choose Q8_0 for near-lossless quality if you have spare VRAM, or smaller quants (Q3/Q2) only when memory is tight.
Install Ollama, then run: ollama run cogito:3b. This downloads Cogito v1 and starts a local, OpenAI-compatible endpoint — no internet connection is needed after the initial download.