KALYPSO v1.1L is the public coding model of the KALYPSO family by GENOMA Labs. It is Qwen2.5-Coder-14B-Instruct fine-tuned with LoRA (r=64, alpha=128, merged to full fp16 weights) on Kraken-Public, a decontaminated dataset of 18,049 records derived from NVIDIA Nemotron coding data.
It is tuned for agentic coding: multi-step programming tasks, tool-calling scaffolds, and plan-then-implement workflows in Python, C++, and SQL.
Benchmarks (EvalPlus)
Benchmark
KALYPSO v1.1L
Qwen2.5-Coder-14B-Instruct (ref)
HumanEval
87.8
~89
HumanEval+
82.9
~87.2
MBPP
84.7
~84
MBPP+
70.4
~72.8
Honest framing: pure code completion is saturated at the 14B scale, and this model scores at parity with its base. v1.1L is published as the reference fine-tune for the Kraken-Public dataset; its value is agentic breadth, not single-shot completion wins.
Apache-2.0. Built with Qwen (Qwen2.5-Coder-14B-Instruct, Apache-2.0). Training data derived from NVIDIA Nemotron coding datasets; portions of the data lineage may also be subject to the Qwen and DeepSeek license terms of their originating models.