Reasoning-first Small Language Models for agentic systems in production
DeepBrainz AI & Labs builds reasoning-first, agentic Small Language Models (SLMs) optimized for reliability, controllability, and efficiency in real-world AI systems.
We focus on behavioral intelligence β training models to reason, plan, and act β rather than scaling parameters or gaming benchmarks.
If youβre new to DeepBrainz-R1, start with one of these:
DeepBrainz-R1-4B β flagship model
Best overall reasoning quality and stability for production agentic systems.
DeepBrainz-R1-2B β balanced model
Strong reasoning with lower latency and cost.
DeepBrainz-R1-0.6B-v2 β small & efficient
Designed for local inference, edge agents, and cost-sensitive workflows.
All other variants are experimental or research-only.
We explicitly optimize against:
We treat intelligence as a behavior to be trained, not a side-effect of model size.
We focus on small, efficient language models that demonstrate strong reasoning behavior without relying on brute-force scale.
Our research explores:
DeepBrainz-R1 is our primary open research line.
It is a family of reasoning-first SLMs designed for:
We publish multiple variants to support transparency and reproducibility.
Only selected releases are considered supported.
DeepBrainz AI & Labs is an independent research lab.
Our work is public, iterative, and driven by first-principles experimentation.
Follow the organization to track ongoing releases and research updates.