Nimbus-Labs/Nimbus-4B
Nimbus-Labs/Nimbus-4B is a 4.5 billion parameter coding model developed by Nimbus-Labs, built upon the Qwen3.5 foundation. This model is specifically designed for balanced performance in local coding assistance, debugging, and bounded agentic workflows. It excels at implementation tasks and achieves strong results on coding benchmarks, including 73.8% pass@1 on HumanEval and 75.4% on MBPP. The model supports a 32768 token context length and includes multimodal components, though GGUF artifacts are text-only.
Loading preview...
Nimbus-4B: A Balanced Local Coding Model
Nimbus-4B is a 4.5 billion parameter model from Nimbus-Labs, fine-tuned from Qwen3.5-4B-Base, designed for local coding tasks. It offers a balance between speed and reasoning capabilities within the Nimbus family of models, which also includes Nimbus-2B (for speed) and Nimbus-9B v2.1 (for deeper reasoning).
Key Capabilities & Performance
- Coding Assistance: Optimized for implementation, debugging, code explanation, and test generation.
- Agentic Workflows: Supports bounded tool-aware workflows, requiring host applications to enforce permissions and sandboxing.
- Strong Benchmarks: Achieves a pass@1 score of 73.8% on HumanEval and 75.4% on MBPP, demonstrating robust performance on coding challenges.
- Multimodal Components: The Transformers checkpoint includes multimodal components, though GGUF versions are text-only.
- Context Length: Features a substantial context window of 32768 tokens.
When to Use Nimbus-4B
- Balanced Performance: Ideal for developers seeking a good compromise between execution speed and coding reasoning for local development environments.
- Implementation & Debugging: Particularly suited for tasks involving code implementation and identifying/resolving bugs.
- Local Deployment: Designed for local execution, offering flexibility for various development setups.
Limitations
Users should be aware that the model can produce incorrect, insecure, or incomplete code. Benchmark performance does not guarantee project-level correctness, and generated code requires validation before execution.