Model Detail

numbat is a code generation model with 3424.7B parameters released by burner22. It has accumulated 7K downloads on Hugging Face since publication.

numbat ships with 3424.7B parameters. Total weight footprint is approximately 6849.4 GB, which is the relevant figure when planning local-inference VRAM.

Downloads of numbat have moved +5.0% over the past 24 hours. That is a slight downtrend, consistent with normal cooling as newer models compete for the same workloads. These numbers are signal, not guarantee — week-over-week download counts on Hugging Face also reflect mirror traffic, CI scrapes, and one-off benchmarking runs.

numbat is best fit for code completion, repository-scale Q&A, and pair-programming integrations. It is a less obvious choice for one-shot generation of security-critical code without review. Treat this as a starting matrix rather than a benchmark verdict — the right deployment usually depends on the specific evaluation suite that mirrors your workload.