# Long-horizon eval: Kimi-K2.5 (vLLM, TP=8)
# 4 benchmarks: GAIA, FRAMES, DeepPlanning, LifelongAgent KG
# NOTE: BF16 weights are 595GB — tight on 8xH100 80GB.
# Consider using FP8/INT4 quantization if available.

[meta]
name = "long-horizon-kimik25"
description = "Long-horizon benchmarks on Kimi-K2.5"

[defaults]
temperature = 0.6
max_tokens = 8192

[judge]
model = "gpt-5-mini-2025-08-07"
temperature = 0.0
max_tokens = 4096

[run]
max_workers = 1
output_dir = "results/long-horizon-kimik25/"
seed = 42
telemetry = true
gpu_metrics = true

[[models]]
name = "moonshotai/Kimi-K2.5"
engine = "vllm"
param_count_b = 1000.0
active_params_b = 32.0
gpu_peak_tflops = 989.5
gpu_peak_bandwidth_gb_s = 3350.0
num_gpus = 8

[[benchmarks]]
name = "gaia"
backend = "jarvis-agent"
agent = "monitor_operative"
max_samples = 50
tools = ["think", "calculator", "code_interpreter", "web_search", "file_read"]

[[benchmarks]]
name = "frames"
backend = "jarvis-direct"
max_samples = 50

[[benchmarks]]
name = "deepplanning"
backend = "jarvis-agent"
agent = "monitor_operative"
max_samples = 50
tools = ["think", "calculator", "code_interpreter"]

[[benchmarks]]
name = "lifelong-agent"
backend = "jarvis-agent"
agent = "monitor_operative"
max_samples = 50
subset = "knowledge_graph"
tools = ["think", "calculator", "code_interpreter"]
