README.md

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title: README
emoji: 🏃
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colorTo: indigo
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short_description: Reasoning-first, agentic small language models (SLMs).

DeepBrainz AI & Labs

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 — training models to reason, plan, and act — rather than scaling parameters or gaming benchmarks.

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🔑 Start Here (Recommended Models)

If you’re new to DeepBrainz-R1, start with one of these:

• DeepBrainz-R1-4B — flagship model
  Best overall reasoning quality and stability for production agentic systems.

• DeepBrainz-R1-2B — balanced model
  Strong reasoning with lower latency and cost.

• DeepBrainz-R1-0.6B-v2 — small & efficient
  Designed for local inference, edge agents, and cost-sensitive workflows.

All other variants are experimental or research-only.

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🧠 Capabilities

What DeepBrainz-R1 Is Built For

• Multi-step reasoning
• Tool-calling and agent loops
• Long-context analysis
• Deterministic, inspectable behavior

🚫 What It Is Not Optimized For

• Open-ended chat or roleplay
• Creative writing
• Prompt-memorization benchmarks

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🧪 Research Philosophy

We explicitly optimize against:

• Shallow pattern matching
• Benchmark gaming
• Prompt memorization

We treat intelligence as a behavior to be trained, not a side-effect of model size.

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What We Work On

We focus on small, efficient language models that demonstrate strong reasoning behavior without relying on brute-force scale.

Our research explores:

• Reinforcement learning–based post-training
• Test-time and inference-time scaling
• Long-context efficiency
• Agentic reasoning workflows
• Systematic ablations over architecture, data, and context length

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DeepBrainz-R Series

DeepBrainz-R1 is our primary open research line.

It is a family of reasoning-first SLMs designed for:

• Multi-step reasoning
• Long-context understanding
• Research and agentic experimentation

We publish multiple variants to support transparency and reproducibility.
Only selected releases are considered supported.

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🧱 Model Support Status

• ✅ Supported / Production — curated, validated releases
• 🧪 Experimental — exploratory variants
• 🧱 Research Checkpoints — raw checkpoints for reproducibility
• 👥 Community Maintained — third-party quantizations (GGUF, low-bit)

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Open Research

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.