# LiveCodeBench eval: Kimi-K2.5 (Ollama, IQ4_XS GGUF)
# Competitive programming from LeetCode, AtCoder, CodeForces
# Pull model: ollama pull hf.co/unsloth/Kimi-K2.5-GGUF:IQ4_XS
#
# WARNING: Kimi-K2.5 is a 1T-param MoE (32B active). ALL GGUF quants are
# sharded (smallest is 240 GB), and Ollama does not support sharded GGUFs
# yet (see github.com/ollama/ollama/issues/5245). This config is a
# placeholder -- use vLLM or wait for Ollama sharded GGUF support.
# The IQ4_XS GGUF is 547 GB and would require 7x H100 80GB GPUs.

[meta]
name = "livecodebench-kimi-k25"
description = "LiveCodeBench on Kimi-K2.5 IQ4_XS via Ollama"

[defaults]
temperature = 0.0
max_tokens = 4096

[judge]
model = "gpt-5-mini-2025-08-07"
temperature = 0.0
engine = "cloud"

[run]
max_workers = 1
output_dir = "results/neurips-2026/baselines/kimi-k25-ollama/livecodebench/"
seed = 42

[[models]]
name = "hf.co/unsloth/Kimi-K2.5-GGUF:IQ4_XS"
engine = "ollama"
param_count_b = 1000.0
active_params_b = 32.0
num_gpus = 7

[[benchmarks]]
name = "livecodebench"
backend = "jarvis-direct"
max_samples = 20
