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sglang/test/registered/8-gpu-models/test_minimax_m25.py
2026-03-07 01:15:34 -08:00

54 lines
1.7 KiB
Python

import unittest
from sglang.test.accuracy_test_runner import AccuracyTestParams
from sglang.test.ci.ci_register import register_cuda_ci
from sglang.test.performance_test_runner import PerformanceTestParams
from sglang.test.run_combined_tests import run_combined_tests
from sglang.test.test_utils import ModelLaunchSettings
# Runs on both H200 and B200 via nightly-8-gpu-common suite
register_cuda_ci(est_time=1800, suite="nightly-8-gpu-common", nightly=True)
MINIMAX_M25_MODEL_PATH = "MiniMaxAI/MiniMax-M2.5"
class TestMiniMaxM25(unittest.TestCase):
"""Unified test class for MiniMax-M2.5 performance and accuracy.
Single variant with TP=8 + EP=8 configuration.
Runs BOTH:
- Performance test (using NightlyBenchmarkRunner with extra_bench_args)
- Accuracy test (using run_eval with gsm8k)
"""
def test_minimax_m25(self):
"""Run performance and accuracy for MiniMax-M2.5."""
base_args = [
"--trust-remote-code",
"--ep=8",
"--mem-fraction-static=0.85",
"--reasoning-parser=minimax-append-think",
]
variants = [
ModelLaunchSettings(
MINIMAX_M25_MODEL_PATH,
tp_size=8,
extra_args=base_args,
variant="TP8+EP8",
),
]
run_combined_tests(
models=variants,
test_name="MiniMax-M2.5",
accuracy_params=AccuracyTestParams(dataset="gsm8k", baseline_accuracy=0.80),
performance_params=PerformanceTestParams(
profile_dir="performance_profiles_minimax_m25",
),
)
if __name__ == "__main__":
unittest.main()