K2-Horizon Delivers Frontier Results with 4B Active Parameters
π‘A 4B-active open model claims frontier-level reasoning with a native 512K context.
β‘ 30-Second TL;DR
What Changed
Uses 36B total parameters with 4B active parameters per token.
Why It Matters
The model could make frontier-style reasoning and agent workloads more practical on constrained inference hardware. Its planned release of training artifacts may also benefit researchers studying capability progression and sparse model efficiency.
What To Do Next
Download the K2-Horizon-MoVA-36B-A4B GGUF and benchmark its reasoning, context retention, and tokens-per-second performance on your target hardware.
Key Points
- β’Uses 36B total parameters with 4B active parameters per token.
- β’Offers a native 524,288-token context window from midtraining onward.
- β’Claims strong agentic and reasoning results against much larger open and closed models.
- β’IFM plans to release intermediate checkpoints, training data, recipe, and code.
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Original source: Reddit r/LocalLLaMA β
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