From 244531bc4f3bc24a5ca2c0ce77b4df05d515cc14 Mon Sep 17 00:00:00 2001 From: Michael <13900043+michaelzhang-ai@users.noreply.github.com> Date: Tue, 5 May 2026 14:37:14 +0800 Subject: [PATCH] [AMD] Add Kimi-K2.6 in nightly tests for MI30x and MI35x (#23848) --- .../workflows/nightly-test-amd-rocm720.yml | 28 ++-- .github/workflows/nightly-test-amd.yml | 28 ++-- .../accuracy/mi30x/test_kimi_k26_eval_amd.py | 108 +++++++++++++ .../mi35x/test_kimi_k26_eval_mi35x.py | 110 +++++++++++++ .../amd/perf/mi30x/test_kimi_k26_perf_amd.py | 148 +++++++++++++++++ .../perf/mi35x/test_kimi_k26_perf_mi35x.py | 152 ++++++++++++++++++ 6 files changed, 546 insertions(+), 28 deletions(-) create mode 100644 test/registered/amd/accuracy/mi30x/test_kimi_k26_eval_amd.py create mode 100644 test/registered/amd/accuracy/mi35x/test_kimi_k26_eval_mi35x.py create mode 100644 test/registered/amd/perf/mi30x/test_kimi_k26_perf_amd.py create mode 100644 test/registered/amd/perf/mi35x/test_kimi_k26_perf_mi35x.py diff --git a/.github/workflows/nightly-test-amd-rocm720.yml b/.github/workflows/nightly-test-amd-rocm720.yml index e3eda3732..1adc2e618 100644 --- a/.github/workflows/nightly-test-amd-rocm720.yml +++ b/.github/workflows/nightly-test-amd-rocm720.yml @@ -40,7 +40,7 @@ on: - nightly-8-gpu-deepseek-v32-rocm720 - nightly-8-gpu-deepseek-v32-mtp-rocm720 - nightly-8-gpu-deepseek-v3-kv-fp8-rocm720 - - nightly-8-gpu-kimi-k25-rocm720 + - nightly-8-gpu-kimi-k26-rocm720 - nightly-8-gpu-qwen3-235b-rocm720 - nightly-8-gpu-qwen35-rocm720 - nightly-8-gpu-glm51-rocm720 @@ -59,7 +59,7 @@ on: - nightly-perf-8-gpu-mi35x-deepseek-v32-mtp-rocm720 - nightly-8-gpu-mi35x-deepseek-v4-flash-rocm720 - nightly-8-gpu-mi35x-deepseek-v4-pro-rocm720 - - nightly-8-gpu-mi35x-kimi-k25-rocm720 + - nightly-8-gpu-mi35x-kimi-k26-rocm720 - nightly-8-gpu-mi35x-qwen3-235b-mxfp4-rocm720 - nightly-8-gpu-mi35x-qwen35-rocm720 - nightly-8-gpu-mi35x-glm51-rocm720 @@ -565,9 +565,9 @@ jobs: echo "$(> $GITHUB_STEP_SUMMARY || true exit ${TEST_EXIT_CODE:-0} - # 8-GPU Kimi-K2.5 (Accuracy) ROCm 7.2 - nightly-8-gpu-kimi-k25-rocm720: - if: (github.repository == 'sgl-project/sglang' || github.event_name == 'pull_request') && (!(inputs.job_filter || inputs.job_select) || (inputs.job_filter || inputs.job_select) == 'all' || contains(format(',{0},', inputs.job_filter || inputs.job_select), ',nightly-8-gpu-kimi-k25-rocm720,')) + # 8-GPU Kimi-K2.6 (Accuracy) ROCm 7.2 + nightly-8-gpu-kimi-k26-rocm720: + if: (github.repository == 'sgl-project/sglang' || github.event_name == 'pull_request') && (!(inputs.job_filter || inputs.job_select) || (inputs.job_filter || inputs.job_select) == 'all' || contains(format(',{0},', inputs.job_filter || inputs.job_select), ',nightly-8-gpu-kimi-k26-rocm720,')) runs-on: linux-mi325-8gpu-sglang steps: - name: Checkout code @@ -585,13 +585,13 @@ jobs: - name: Install dependencies run: bash scripts/ci/amd/amd_ci_install_dependency.sh --skip-test-time-deps - - name: Accuracy Test ROCm 7.2 (8-GPU Kimi-K2.5) + - name: Accuracy Test ROCm 7.2 (8-GPU Kimi-K2.6) timeout-minutes: 120 run: | > github_summary.md # Clear summary file bash scripts/ci/amd/amd_ci_exec.sh -w /sglang-checkout/test \ -e GITHUB_STEP_SUMMARY="/sglang-checkout/github_summary.md" \ - python3 run_suite.py --hw amd --suite nightly-amd-accuracy-8-gpu-kimi-k25 --nightly --timeout-per-file 3600 ${{ inputs.continue_on_error && '--continue-on-error' || '' }} || TEST_EXIT_CODE=$? + python3 run_suite.py --hw amd --suite nightly-amd-accuracy-8-gpu-kimi-k26 --nightly --timeout-per-file 3600 ${{ inputs.continue_on_error && '--continue-on-error' || '' }} || TEST_EXIT_CODE=$? echo "$(> $GITHUB_STEP_SUMMARY || true exit ${TEST_EXIT_CODE:-0} @@ -1181,9 +1181,9 @@ jobs: echo "$(> $GITHUB_STEP_SUMMARY || true exit ${TEST_EXIT_CODE:-0} - # MI35x 8-GPU Kimi-K2.5 (Accuracy) ROCm 7.2 - nightly-8-gpu-mi35x-kimi-k25-rocm720: - if: (github.repository == 'sgl-project/sglang' || github.event_name == 'pull_request') && (!(inputs.job_filter || inputs.job_select) || (inputs.job_filter || inputs.job_select) == 'all' || contains(format(',{0},', inputs.job_filter || inputs.job_select), ',nightly-8-gpu-mi35x-kimi-k25-rocm720,')) + # MI35x 8-GPU Kimi-K2.6 (Accuracy) ROCm 7.2 + nightly-8-gpu-mi35x-kimi-k26-rocm720: + if: (github.repository == 'sgl-project/sglang' || github.event_name == 'pull_request') && (!(inputs.job_filter || inputs.job_select) || (inputs.job_filter || inputs.job_select) == 'all' || contains(format(',{0},', inputs.job_filter || inputs.job_select), ',nightly-8-gpu-mi35x-kimi-k26-rocm720,')) runs-on: linux-mi35x-gpu-8 steps: - name: Checkout code @@ -1204,13 +1204,13 @@ jobs: # Install tabulate for run_suite.py (missing in MI35x container) bash scripts/ci/amd/amd_ci_exec.sh pip install tabulate - - name: Accuracy Test MI35x ROCm 7.2 (8-GPU Kimi-K2.5) + - name: Accuracy Test MI35x ROCm 7.2 (8-GPU Kimi-K2.6) timeout-minutes: 180 run: | > github_summary.md # Clear summary file bash scripts/ci/amd/amd_ci_exec.sh -w /sglang-checkout/test \ -e GITHUB_STEP_SUMMARY="/sglang-checkout/github_summary.md" \ - python3 run_suite.py --hw amd --suite nightly-amd-accuracy-8-gpu-mi35x-kimi-k25 --nightly --timeout-per-file 7200 ${{ inputs.continue_on_error && '--continue-on-error' || '' }} || TEST_EXIT_CODE=$? + python3 run_suite.py --hw amd --suite nightly-amd-accuracy-8-gpu-mi35x-kimi-k26 --nightly --timeout-per-file 7200 ${{ inputs.continue_on_error && '--continue-on-error' || '' }} || TEST_EXIT_CODE=$? echo "$(> $GITHUB_STEP_SUMMARY || true exit ${TEST_EXIT_CODE:-0} @@ -1572,7 +1572,7 @@ jobs: - nightly-8-gpu-deepseek-v32-rocm720 - nightly-8-gpu-deepseek-v32-mtp-rocm720 - nightly-8-gpu-deepseek-v3-kv-fp8-rocm720 - - nightly-8-gpu-kimi-k25-rocm720 + - nightly-8-gpu-kimi-k26-rocm720 - nightly-8-gpu-qwen3-235b-rocm720 - nightly-8-gpu-qwen35-rocm720 - nightly-8-gpu-glm51-rocm720 @@ -1593,7 +1593,7 @@ jobs: - nightly-perf-8-gpu-mi35x-deepseek-v32-mtp-rocm720 - nightly-8-gpu-mi35x-deepseek-v4-flash-rocm720 - nightly-8-gpu-mi35x-deepseek-v4-pro-rocm720 - - nightly-8-gpu-mi35x-kimi-k25-rocm720 + - nightly-8-gpu-mi35x-kimi-k26-rocm720 - nightly-8-gpu-mi35x-qwen3-235b-mxfp4-rocm720 - nightly-8-gpu-mi35x-qwen35-rocm720 - nightly-8-gpu-mi35x-glm51-rocm720 diff --git a/.github/workflows/nightly-test-amd.yml b/.github/workflows/nightly-test-amd.yml index 73b0dde13..752568fa6 100644 --- a/.github/workflows/nightly-test-amd.yml +++ b/.github/workflows/nightly-test-amd.yml @@ -40,7 +40,7 @@ on: - nightly-8-gpu-deepseek-v32 - nightly-8-gpu-deepseek-v32-mtp - nightly-8-gpu-deepseek-v3-kv-fp8 - - nightly-8-gpu-kimi-k25 + - nightly-8-gpu-kimi-k26 - nightly-8-gpu-qwen3-235b - nightly-8-gpu-qwen35 - nightly-8-gpu-glm51 @@ -57,7 +57,7 @@ on: - nightly-accuracy-8-gpu-mi35x-deepseek-v32-mtp - nightly-perf-8-gpu-mi35x-deepseek-v32-basic - nightly-perf-8-gpu-mi35x-deepseek-v32-mtp - - nightly-8-gpu-mi35x-kimi-k25 + - nightly-8-gpu-mi35x-kimi-k26 - nightly-8-gpu-mi35x-qwen3-235b-mxfp4 - nightly-8-gpu-mi35x-qwen35 - nightly-8-gpu-mi35x-glm51 @@ -568,9 +568,9 @@ jobs: echo "$(> $GITHUB_STEP_SUMMARY || true exit ${TEST_EXIT_CODE:-0} - # 8-GPU Kimi-K2.5 (Accuracy) - nightly-8-gpu-kimi-k25: - if: (github.repository == 'sgl-project/sglang' || github.event_name == 'pull_request') && (!(inputs.job_filter || inputs.job_select) || (inputs.job_filter || inputs.job_select) == 'all' || contains(format(',{0},', inputs.job_filter || inputs.job_select), ',nightly-8-gpu-kimi-k25,')) + # 8-GPU Kimi-K2.6 (Accuracy) + nightly-8-gpu-kimi-k26: + if: (github.repository == 'sgl-project/sglang' || github.event_name == 'pull_request') && (!(inputs.job_filter || inputs.job_select) || (inputs.job_filter || inputs.job_select) == 'all' || contains(format(',{0},', inputs.job_filter || inputs.job_select), ',nightly-8-gpu-kimi-k26,')) runs-on: linux-mi325-8gpu-sglang steps: - name: Checkout code @@ -588,13 +588,13 @@ jobs: - name: Install dependencies run: bash scripts/ci/amd/amd_ci_install_dependency.sh - - name: Accuracy Test (8-GPU Kimi-K2.5) + - name: Accuracy Test (8-GPU Kimi-K2.6) timeout-minutes: 120 run: | > github_summary.md # Clear summary file bash scripts/ci/amd/amd_ci_exec.sh -w /sglang-checkout/test \ -e GITHUB_STEP_SUMMARY="/sglang-checkout/github_summary.md" \ - python3 run_suite.py --hw amd --suite nightly-amd-accuracy-8-gpu-kimi-k25 --nightly --timeout-per-file 3600 ${{ inputs.continue_on_error && '--continue-on-error' || '' }} || TEST_EXIT_CODE=$? + python3 run_suite.py --hw amd --suite nightly-amd-accuracy-8-gpu-kimi-k26 --nightly --timeout-per-file 3600 ${{ inputs.continue_on_error && '--continue-on-error' || '' }} || TEST_EXIT_CODE=$? echo "$(> $GITHUB_STEP_SUMMARY || true exit ${TEST_EXIT_CODE:-0} @@ -1186,9 +1186,9 @@ jobs: echo "$(> $GITHUB_STEP_SUMMARY || true exit ${TEST_EXIT_CODE:-0} - # MI35x 8-GPU Kimi-K2.5 (Accuracy) - nightly-8-gpu-mi35x-kimi-k25: - if: (github.repository == 'sgl-project/sglang' || github.event_name == 'pull_request') && (!(inputs.job_filter || inputs.job_select) || (inputs.job_filter || inputs.job_select) == 'all' || contains(format(',{0},', inputs.job_filter || inputs.job_select), ',nightly-8-gpu-mi35x-kimi-k25,')) + # MI35x 8-GPU Kimi-K2.6 (Accuracy) + nightly-8-gpu-mi35x-kimi-k26: + if: (github.repository == 'sgl-project/sglang' || github.event_name == 'pull_request') && (!(inputs.job_filter || inputs.job_select) || (inputs.job_filter || inputs.job_select) == 'all' || contains(format(',{0},', inputs.job_filter || inputs.job_select), ',nightly-8-gpu-mi35x-kimi-k26,')) runs-on: linux-mi35x-gpu-8 steps: - name: Checkout code @@ -1209,13 +1209,13 @@ jobs: # Install tabulate for run_suite.py (missing in MI35x container) bash scripts/ci/amd/amd_ci_exec.sh pip install tabulate - - name: Accuracy Test MI35x (8-GPU Kimi-K2.5) + - name: Accuracy Test MI35x (8-GPU Kimi-K2.6) timeout-minutes: 180 run: | > github_summary.md # Clear summary file bash scripts/ci/amd/amd_ci_exec.sh -w /sglang-checkout/test \ -e GITHUB_STEP_SUMMARY="/sglang-checkout/github_summary.md" \ - python3 run_suite.py --hw amd --suite nightly-amd-accuracy-8-gpu-mi35x-kimi-k25 --nightly --timeout-per-file 7200 ${{ inputs.continue_on_error && '--continue-on-error' || '' }} || TEST_EXIT_CODE=$? + python3 run_suite.py --hw amd --suite nightly-amd-accuracy-8-gpu-mi35x-kimi-k26 --nightly --timeout-per-file 7200 ${{ inputs.continue_on_error && '--continue-on-error' || '' }} || TEST_EXIT_CODE=$? echo "$(> $GITHUB_STEP_SUMMARY || true exit ${TEST_EXIT_CODE:-0} @@ -1441,7 +1441,7 @@ jobs: - nightly-8-gpu-deepseek-v32 - nightly-8-gpu-deepseek-v32-mtp - nightly-8-gpu-deepseek-v3-kv-fp8 - - nightly-8-gpu-kimi-k25 + - nightly-8-gpu-kimi-k26 - nightly-8-gpu-qwen3-235b - nightly-8-gpu-qwen35 - nightly-8-gpu-glm51 @@ -1458,7 +1458,7 @@ jobs: - nightly-8-gpu-mi35x-deepseek-r1-mxfp4-ar-fusion - nightly-accuracy-8-gpu-mi35x-deepseek-v32 - nightly-accuracy-8-gpu-mi35x-deepseek-v32-mtp - - nightly-8-gpu-mi35x-kimi-k25 + - nightly-8-gpu-mi35x-kimi-k26 - nightly-8-gpu-mi35x-qwen3-235b-mxfp4 - nightly-8-gpu-mi35x-qwen35 - nightly-8-gpu-mi35x-glm51 diff --git a/test/registered/amd/accuracy/mi30x/test_kimi_k26_eval_amd.py b/test/registered/amd/accuracy/mi30x/test_kimi_k26_eval_amd.py new file mode 100644 index 000000000..fcbbffe1a --- /dev/null +++ b/test/registered/amd/accuracy/mi30x/test_kimi_k26_eval_amd.py @@ -0,0 +1,108 @@ +"""AMD Kimi-K2.6 GSM8K Completion Evaluation Test (8-GPU) + +Tests moonshotai/Kimi-K2.6 with GSM8K few-shot benchmark on MI325. + +Kimi-K2.6 shares the same architecture as Kimi-K2.5 (per the model card the +deployment method is directly reused), so the AMD server arguments match the +existing Kimi-K2.5 MI30x test. + +Registry: nightly-amd-accuracy-8-gpu-kimi-k26 suite +""" + +import os +import unittest +from types import SimpleNamespace + +import requests + +from sglang.srt.utils import kill_process_tree +from sglang.test.ci.ci_register import register_amd_ci +from sglang.test.few_shot_gsm8k import run_eval as run_eval_few_shot_gsm8k +from sglang.test.test_utils import ( + DEFAULT_URL_FOR_TEST, + CustomTestCase, + is_in_ci, + popen_launch_server, + write_github_step_summary, +) + +# Register for AMD CI - Kimi K2.6 accuracy test (~60 min) +register_amd_ci( + est_time=3600, suite="nightly-amd-accuracy-8-gpu-kimi-k26", nightly=True +) + +KIMI_K26_MODEL_PATH = "moonshotai/Kimi-K2.6" +SERVER_LAUNCH_TIMEOUT = 3600 +ACCURACY_THRESHOLD = 0.92 +TP_SIZE = 8 + + +class TestKimiK26EvalAMD(CustomTestCase): + """Kimi-K2.6 GSM8K Completion Evaluation Test for AMD MI325.""" + + @classmethod + def setUpClass(cls): + cls.model = KIMI_K26_MODEL_PATH + cls.base_url = DEFAULT_URL_FOR_TEST + other_args = [ + "--tp", + str(TP_SIZE), + "--decode-attention-backend", + "triton", + "--prefill-attention-backend", + "aiter", + "--trust-remote-code", + "--model-loader-extra-config", + '{"enable_multithread_load": true}', + ] + env = os.environ.copy() + env["SGLANG_USE_AITER"] = "1" + env["SGLANG_ROCM_FUSED_DECODE_MLA"] = "0" + cls.process = popen_launch_server( + cls.model, + cls.base_url, + timeout=SERVER_LAUNCH_TIMEOUT, + other_args=other_args, + env=env, + ) + + @classmethod + def tearDownClass(cls): + kill_process_tree(cls.process.pid) + + def test_kimi_k26_gsm8k_accuracy(self): + """Test Kimi-K2.6 with GSM8K few-shot completion benchmark.""" + requests.get(self.base_url + "/flush_cache") + + args = SimpleNamespace( + num_shots=8, + data_path=None, + num_questions=1319, + parallel=1319, + max_new_tokens=512, + host="http://127.0.0.1", + port=int(self.base_url.split(":")[-1]), + ) + metrics = run_eval_few_shot_gsm8k(args) + acc = metrics["accuracy"] + + passed = acc >= ACCURACY_THRESHOLD + status = "✅ PASS" if passed else "❌ FAIL" + print(f" accuracy={acc:.3f} threshold={ACCURACY_THRESHOLD} {status}") + + if is_in_ci(): + summary = "### Kimi-K2.6 Model (MI325)\n\n" + summary += "| Model | TP | Accuracy | Threshold | Status |\n" + summary += "| ----- | -- | -------- | --------- | ------ |\n" + summary += f"| {KIMI_K26_MODEL_PATH} | {TP_SIZE} | {acc:.3f} | {ACCURACY_THRESHOLD} | {status} |\n" + write_github_step_summary(summary) + + self.assertGreaterEqual( + acc, + ACCURACY_THRESHOLD, + f"Kimi-K2.6 accuracy {acc:.3f} below threshold {ACCURACY_THRESHOLD}", + ) + + +if __name__ == "__main__": + unittest.main() diff --git a/test/registered/amd/accuracy/mi35x/test_kimi_k26_eval_mi35x.py b/test/registered/amd/accuracy/mi35x/test_kimi_k26_eval_mi35x.py new file mode 100644 index 000000000..652fa8276 --- /dev/null +++ b/test/registered/amd/accuracy/mi35x/test_kimi_k26_eval_mi35x.py @@ -0,0 +1,110 @@ +"""MI35x Kimi-K2.6 GSM8K Completion Evaluation Test (8-GPU) + +Tests moonshotai/Kimi-K2.6 with GSM8K few-shot benchmark on MI35x. + +Kimi-K2.6 shares the same architecture as Kimi-K2.5 (per the model card the +deployment method is directly reused), so the AMD server arguments match the +existing Kimi-K2.5 MI35x test. + +Registry: nightly-amd-accuracy-8-gpu-mi35x-kimi-k26 suite +""" + +import os +import unittest +from types import SimpleNamespace + +import requests + +from sglang.srt.utils import kill_process_tree +from sglang.test.ci.ci_register import register_amd_ci +from sglang.test.few_shot_gsm8k import run_eval as run_eval_few_shot_gsm8k +from sglang.test.test_utils import ( + DEFAULT_URL_FOR_TEST, + CustomTestCase, + is_in_ci, + popen_launch_server, + write_github_step_summary, +) + +# Register for AMD CI - Kimi K2.6 accuracy test on MI35x (~90 min) +register_amd_ci( + est_time=5400, suite="nightly-amd-accuracy-8-gpu-mi35x-kimi-k26", nightly=True +) + +KIMI_K26_MODEL_PATH = "moonshotai/Kimi-K2.6" +SERVER_LAUNCH_TIMEOUT = 5400 +ACCURACY_THRESHOLD = 0.92 +TP_SIZE = 8 + + +class TestKimiK26EvalMI35x(CustomTestCase): + """Kimi-K2.6 GSM8K Completion Evaluation Test for AMD MI35x.""" + + @classmethod + def setUpClass(cls): + cls.base_url = DEFAULT_URL_FOR_TEST + + def test_kimi_k26_gsm8k_accuracy(self): + """Test Kimi-K2.6 with GSM8K few-shot completion benchmark.""" + other_args = [ + "--tp", + str(TP_SIZE), + "--decode-attention-backend", + "triton", + "--prefill-attention-backend", + "aiter", + "--trust-remote-code", + "--model-loader-extra-config", + '{"enable_multithread_load": true}', + "--watchdog-timeout", + "1200", + ] + env = os.environ.copy() + env["SGLANG_USE_AITER"] = "1" + env["SGLANG_ROCM_FUSED_DECODE_MLA"] = "0" + + process = popen_launch_server( + KIMI_K26_MODEL_PATH, + self.base_url, + timeout=SERVER_LAUNCH_TIMEOUT, + other_args=other_args, + env=env, + ) + + try: + requests.get(self.base_url + "/flush_cache") + + args = SimpleNamespace( + num_shots=8, + data_path=None, + num_questions=1319, + parallel=1319, + max_new_tokens=512, + host="http://127.0.0.1", + port=int(self.base_url.split(":")[-1]), + ) + metrics = run_eval_few_shot_gsm8k(args) + acc = metrics["accuracy"] + + passed = acc >= ACCURACY_THRESHOLD + status = "✅ PASS" if passed else "❌ FAIL" + print(f" accuracy={acc:.3f} threshold={ACCURACY_THRESHOLD} {status}") + + if is_in_ci(): + summary = "### Kimi-K2.6 Model (MI35x)\n\n" + summary += "| Model | TP | Accuracy | Threshold | Status |\n" + summary += "| ----- | -- | -------- | --------- | ------ |\n" + summary += f"| {KIMI_K26_MODEL_PATH} | {TP_SIZE} | {acc:.3f} | {ACCURACY_THRESHOLD} | {status} |\n" + write_github_step_summary(summary) + + self.assertGreaterEqual( + acc, + ACCURACY_THRESHOLD, + f"Kimi-K2.6 accuracy {acc:.3f} below threshold {ACCURACY_THRESHOLD}", + ) + finally: + kill_process_tree(process.pid) + + +if __name__ == "__main__": + unittest.main() diff --git a/test/registered/amd/perf/mi30x/test_kimi_k26_perf_amd.py b/test/registered/amd/perf/mi30x/test_kimi_k26_perf_amd.py new file mode 100644 index 000000000..f14d85e04 --- /dev/null +++ b/test/registered/amd/perf/mi30x/test_kimi_k26_perf_amd.py @@ -0,0 +1,148 @@ +"""AMD Nightly performance benchmark for Kimi-K2.6 model. + +This test benchmarks moonshotai/Kimi-K2.6 with TP=8 on MI325/MI300X. + +Kimi-K2.6 shares the same architecture as Kimi-K2.5 (per the model card the +deployment method is directly reused), so the AMD server arguments match the +existing Kimi-K2.5 MI30x accuracy test (mixed aiter prefill + triton decode). + +The model path can be configured via KIMI_K26_MODEL_PATH environment variable. + +Registry: nightly-perf-8-gpu-kimi-k26 suite + +Example usage: + KIMI_K26_MODEL_PATH=moonshotai/Kimi-K2.6 python -m pytest test_kimi_k26_perf_amd.py -v +""" + +import os +import unittest +from typing import List + +from sglang.test.ci.ci_register import register_amd_ci +from sglang.test.nightly_bench_utils import BenchmarkResult +from sglang.test.nightly_utils import NightlyBenchmarkRunner +from sglang.test.test_utils import DEFAULT_URL_FOR_TEST, _parse_int_list_env + +# Register for AMD CI - Kimi K2.6 perf benchmark (~90 min) +register_amd_ci(est_time=5400, suite="nightly-perf-8-gpu-kimi-k26", nightly=True) + + +def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str: + """Generate a simplified markdown report without traces and cost columns. + + Skips the first result if it's a warmup run (duplicate batch_size). + """ + model_header = results[0].model_path + if results[0].run_name and results[0].run_name != "default": + model_header += f" ({results[0].run_name})" + + gpu_config = os.getenv("GPU_CONFIG", "MI325") + if gpu_config: + model_header += f" [{gpu_config}]" + + summary = f"### {model_header}\n" + summary += "| batch size | input len | latency (s) | input throughput (tok/s) | output throughput (tok/s) | ITL (ms) |\n" + summary += "| ---------- | --------- | ----------- | ------------------------ | ------------------------- | -------- |\n" + + report_results = ( + results[1:] + if len(results) > 1 and results[0].batch_size == results[1].batch_size + else results + ) + + for result in report_results: + itl = 1 / (result.output_throughput / result.batch_size) * 1000 + summary += f"| {result.batch_size} | {result.input_len} | {result.latency:.2f} | {result.input_throughput:.2f} | {result.output_throughput:.2f} | {itl:.2f} |\n" + + return summary + + +KIMI_K26_MODEL_PATH = os.environ.get("KIMI_K26_MODEL_PATH", "moonshotai/Kimi-K2.6") +PROFILE_DIR = "performance_profiles_kimi_k26" + + +class TestNightlyKimiK26Performance(unittest.TestCase): + """AMD Nightly performance benchmark for Kimi-K2.6 model. + + Tests Kimi-K2.6 with TP=8 mixed-attention configuration on MI325/MI300X. + """ + + @classmethod + def setUpClass(cls): + cls.base_url = DEFAULT_URL_FOR_TEST + cls.batch_sizes = [1, 8, 16, 64] + cls.input_lens = tuple(_parse_int_list_env("NIGHTLY_INPUT_LENS", "4096")) + cls.output_lens = tuple(_parse_int_list_env("NIGHTLY_OUTPUT_LENS", "512")) + + # Kimi-K2.6 shares Kimi-K2.5's architecture: aiter for prefill, + # triton for decode (aiter ASM MLA decode requires heads_per_gpu % 16, + # but TP=8 with 64 heads gives 8 heads/GPU, so we use triton decode). + cls.model_config = { + "name": "default", + "model_path": KIMI_K26_MODEL_PATH, + "other_args": [ + "--trust-remote-code", + "--tp", + "8", + "--decode-attention-backend", + "triton", + "--prefill-attention-backend", + "aiter", + "--mem-fraction-static", + "0.85", + "--model-loader-extra-config", + '{"enable_multithread_load": true}', + "--watchdog-timeout", + "1200", + ], + "env_vars": { + "SGLANG_USE_AITER": "1", + "SGLANG_ROCM_FUSED_DECODE_MLA": "0", + }, + } + + cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url) + cls.runner.setup_profile_directory() + cls.runner.full_report = f"## {cls.__name__}\n" + + def test_bench_kimi_k26(self): + """Run benchmark for Kimi-K2.6.""" + old_env = {} + for key, value in self.model_config.get("env_vars", {}).items(): + old_env[key] = os.environ.get(key) + os.environ[key] = value + + try: + result_tuple = self.runner.run_benchmark_for_model( + model_path=self.model_config["model_path"], + batch_sizes=self.batch_sizes, + input_lens=self.input_lens, + output_lens=self.output_lens, + other_args=self.model_config["other_args"], + variant=self.model_config["name"], + extra_bench_args=["--trust-remote-code"], + enable_profile=False, + timeout=5400, + ) + results = result_tuple[0] + success = result_tuple[1] + + if results: + self.runner.full_report += ( + generate_simple_markdown_report(results) + "\n" + ) + + self.assertTrue( + success, f"Benchmark failed for {self.model_config['model_path']}" + ) + finally: + for key, value in old_env.items(): + if value is None: + os.environ.pop(key, None) + else: + os.environ[key] = value + self.runner.write_final_report() + + +if __name__ == "__main__": + unittest.main() diff --git a/test/registered/amd/perf/mi35x/test_kimi_k26_perf_mi35x.py b/test/registered/amd/perf/mi35x/test_kimi_k26_perf_mi35x.py new file mode 100644 index 000000000..0605ae993 --- /dev/null +++ b/test/registered/amd/perf/mi35x/test_kimi_k26_perf_mi35x.py @@ -0,0 +1,152 @@ +"""MI35x Nightly performance benchmark for Kimi-K2.6 model. + +This test benchmarks moonshotai/Kimi-K2.6 with TP=8 on MI35x. + +Kimi-K2.6 shares the same architecture as Kimi-K2.5 (per the model card the +deployment method is directly reused), so the AMD server arguments match the +existing Kimi-K2.5 MI35x accuracy test (mixed aiter prefill + triton decode). + +The model path can be configured via KIMI_K26_MODEL_PATH environment variable. + +Registry: nightly-perf-8-gpu-mi35x-kimi-k26 suite + +Example usage: + KIMI_K26_MODEL_PATH=moonshotai/Kimi-K2.6 python -m pytest test_kimi_k26_perf_mi35x.py -v +""" + +import os + +os.environ.setdefault("HF_HOME", "/data2/models/huggingface") +os.environ.setdefault("HF_HUB_CACHE", "/data2/models/huggingface/hub") + +import unittest +from typing import List + +from sglang.test.ci.ci_register import register_amd_ci +from sglang.test.nightly_bench_utils import BenchmarkResult +from sglang.test.nightly_utils import NightlyBenchmarkRunner +from sglang.test.test_utils import DEFAULT_URL_FOR_TEST, _parse_int_list_env + +# Register for AMD CI - Kimi K2.6 perf benchmark on MI35x (~90 min) +register_amd_ci(est_time=5400, suite="nightly-perf-8-gpu-mi35x-kimi-k26", nightly=True) + + +def generate_simple_markdown_report(results: List[BenchmarkResult]) -> str: + """Generate a simplified markdown report without traces and cost columns. + + Skips the first result if it's a warmup run (duplicate batch_size). + """ + model_header = results[0].model_path + if results[0].run_name and results[0].run_name != "default": + model_header += f" ({results[0].run_name})" + + gpu_config = os.getenv("GPU_CONFIG", "MI35x") + if gpu_config: + model_header += f" [{gpu_config}]" + + summary = f"### {model_header}\n" + summary += "| batch size | input len | latency (s) | input throughput (tok/s) | output throughput (tok/s) | ITL (ms) |\n" + summary += "| ---------- | --------- | ----------- | ------------------------ | ------------------------- | -------- |\n" + + report_results = ( + results[1:] + if len(results) > 1 and results[0].batch_size == results[1].batch_size + else results + ) + + for result in report_results: + itl = 1 / (result.output_throughput / result.batch_size) * 1000 + summary += f"| {result.batch_size} | {result.input_len} | {result.latency:.2f} | {result.input_throughput:.2f} | {result.output_throughput:.2f} | {itl:.2f} |\n" + + return summary + + +KIMI_K26_MODEL_PATH = os.environ.get("KIMI_K26_MODEL_PATH", "moonshotai/Kimi-K2.6") +PROFILE_DIR = "performance_profiles_kimi_k26_mi35x" + + +class TestNightlyKimiK26PerformanceMI35x(unittest.TestCase): + """MI35x Nightly performance benchmark for Kimi-K2.6 model. + + Tests Kimi-K2.6 with TP=8 mixed-attention configuration on MI35x. + """ + + @classmethod + def setUpClass(cls): + cls.base_url = DEFAULT_URL_FOR_TEST + cls.batch_sizes = [1, 8, 16, 64] + cls.input_lens = tuple(_parse_int_list_env("NIGHTLY_INPUT_LENS", "4096")) + cls.output_lens = tuple(_parse_int_list_env("NIGHTLY_OUTPUT_LENS", "512")) + + # Kimi-K2.6 shares Kimi-K2.5's architecture: aiter for prefill, + # triton for decode (aiter ASM MLA decode requires heads_per_gpu % 16, + # but TP=8 with 64 heads gives 8 heads/GPU, so we use triton decode). + cls.model_config = { + "name": "default", + "model_path": KIMI_K26_MODEL_PATH, + "other_args": [ + "--trust-remote-code", + "--tp", + "8", + "--decode-attention-backend", + "triton", + "--prefill-attention-backend", + "aiter", + "--mem-fraction-static", + "0.85", + "--model-loader-extra-config", + '{"enable_multithread_load": true}', + "--watchdog-timeout", + "1200", + ], + "env_vars": { + "SGLANG_USE_AITER": "1", + "SGLANG_ROCM_FUSED_DECODE_MLA": "0", + }, + } + + cls.runner = NightlyBenchmarkRunner(PROFILE_DIR, cls.__name__, cls.base_url) + cls.runner.setup_profile_directory() + cls.runner.full_report = f"## {cls.__name__}\n" + + def test_bench_kimi_k26(self): + """Run benchmark for Kimi-K2.6.""" + old_env = {} + for key, value in self.model_config.get("env_vars", {}).items(): + old_env[key] = os.environ.get(key) + os.environ[key] = value + + try: + result_tuple = self.runner.run_benchmark_for_model( + model_path=self.model_config["model_path"], + batch_sizes=self.batch_sizes, + input_lens=self.input_lens, + output_lens=self.output_lens, + other_args=self.model_config["other_args"], + variant=self.model_config["name"], + extra_bench_args=["--trust-remote-code"], + enable_profile=False, + timeout=5400, + ) + results = result_tuple[0] + success = result_tuple[1] + + if results: + self.runner.full_report += ( + generate_simple_markdown_report(results) + "\n" + ) + + self.assertTrue( + success, f"Benchmark failed for {self.model_config['model_path']}" + ) + finally: + for key, value in old_env.items(): + if value is None: + os.environ.pop(key, None) + else: + os.environ[key] = value + self.runner.write_final_report() + + +if __name__ == "__main__": + unittest.main()