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license: apache-2.0 |
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language: |
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- en |
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pipeline_tag: text-generation |
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tags: |
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- qwen3 |
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- reasoning |
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- long-context |
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- enterprise |
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- research |
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- conversational |
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--- |
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# DeepBrainz-R1-4B-16K |
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DeepBrainz-R1-4B-16K is a compact, long-context reasoning model in the **DeepBrainz-R series**, designed for structured problem-solving, analysis, and enterprise research workflows. |
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The model emphasizes **reasoning quality, instruction robustness, and stability over long contexts**, while remaining efficient to deploy on modern GPU inference runtimes. |
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## Model Highlights |
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- ~4B parameters |
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- 16K context length |
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- Optimized for reasoning-centric math and coding tasks |
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- Designed for modern GPU inference runtimes |
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- **Architecture:** Qwen3-compatible (DeepBrainz-R series, post-trained, and optimized for reasoning-centric workloads) |
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## Intended Use |
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- Advanced reasoning systems |
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- Math and Coding |
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- Research and evaluation |
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- Agentic workflows |
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- Inference-time scaling and test-time compute experiments |
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**Not intended** as a general-purpose chat replacement for large frontier models. |
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## Usage |
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```python |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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model_id = "DeepBrainz/DeepBrainz-R1-4B-16K" |
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tok = AutoTokenizer.from_pretrained(model_id) |
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mdl = AutoModelForCausalLM.from_pretrained(model_id) |
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prompt = "Solve step by step: If x + 5 = 12, what is x?" |
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inputs = tok(prompt, return_tensors="pt") |
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out = mdl.generate( |
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**inputs, |
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max_new_tokens=256, |
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do_sample=True, |
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temperature=0.6, |
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top_p=0.95, |
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) |
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print(tok.decode(out[0], skip_special_tokens=True)) |
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``` |
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## Training Summary |
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The model was produced using a **multi-stage optimization process** involving large-scale on-policy optimization and **iterative refinement** to improve reasoning quality and robustness. |
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Specific training details are intentionally abstracted in this public release. |
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## Limitations |
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Performance depends on task complexity and inference configuration. |
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Larger models may outperform R1-4B-16K on extremely complex tasks. |
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## License |
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Apache 2.0 |
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--- |
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## About DeepBrainz |
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DeepBrainz builds reasoning-first AI systems focused on efficiency, structure, and real-world problem-solving. |
