[TRTLLM-15120][test] Prune Step-3.7-Flash functional tests

tests/integration/defs/accuracy/references/gsm8k.yaml

@@ -515,22 +515,3 @@ zai-org/GLM-5.2:
     kv_cache_quant_algo: FP8
     spec_dec_algo: MTP
     accuracy: 90
-# Step-3.7-Flash text decoder (MoE) GSM8K, full 1319-sample split, TP4/EP4 with
-# TRTLLM attention + MoE backends. FP8 measured on the FP8 block-scale
-# checkpoint; NVFP4 measured on the modelopt NVFP4 export (FP8 KV cache). MTP
-# (mtp_nextn=3) is lossless for both FP8 and NVFP4 and reuses the non-spec
-# baseline accuracy.
-stepfun-ai/Step-3.7-Flash:
-  - accuracy: 88
-  - quant_algo: FP8_BLOCK_SCALES
-    accuracy: 88
-  - quant_algo: FP8_BLOCK_SCALES
-    spec_dec_algo: MTP
-    accuracy: 88
-  - quant_algo: NVFP4
-    kv_cache_quant_algo: FP8
-    accuracy: 88
-  - quant_algo: NVFP4
-    kv_cache_quant_algo: FP8
-    spec_dec_algo: MTP
-    accuracy: 88

tests/integration/defs/accuracy/references/mmmu.yaml

@@ -86,22 +86,3 @@ moonshotai/Kimi-K2.5:
   - quant_algo: NVFP4
     kv_cache_quant_algo: FP8
     accuracy: 81.56
-# Step-3.7-Flash multimodal (PerceptionEncoder vision tower + MoE text decoder).
-# Reasoning model: <think>...</think> traces are stripped before MMMU answer
-# extraction (see test_llm_api_pytorch_multimodal.py::TestStep3_7). FP8 measured
-# on the FP8 block-scale checkpoint over the full 900-sample MMMU val split (TP4
-# / EP4, TRTLLM attention + MoE backends); NVFP4 (modelopt export, FP8 KV cache)
-# reuses the FP8 baseline.
-stepfun-ai/Step-3.7-Flash:
-  - quant_algo: FP8_BLOCK_SCALES
-    accuracy: 60
-  - quant_algo: FP8_BLOCK_SCALES
-    spec_dec_algo: MTP
-    accuracy: 60
-  - quant_algo: NVFP4
-    kv_cache_quant_algo: FP8
-    accuracy: 60
-  - quant_algo: NVFP4
-    kv_cache_quant_algo: FP8
-    spec_dec_algo: MTP
-    accuracy: 60

tests/integration/defs/accuracy/test_llm_api_pytorch.py

@@ -8424,88 +8424,3 @@ def test_nvfp4_mtp_index_share_mtp_ar(self, tp_size, ep_size):
             assert aggregate_accept_rate > 0.2, (
                 f"Aggregate acceptance rate {aggregate_accept_rate:.2%} "
                 f"below threshold 20%")
-
-
-@skip_pre_blackwell
-class TestStep3_7(LlmapiAccuracyTestHarness):
-    # Step-3.7-Flash is a MoE model registered under the multimodal
-    # architecture (Step3p7ForConditionalGeneration); text-only GSM8K exercises
-    # the text decoder path. The custom HF config requires trust_remote_code.
-    MODEL_NAME = "stepfun-ai/Step-3.7-Flash"
-
-    @pytest.mark.skip_less_mpi_world_size(8)
-    @pytest.mark.skip_less_device_memory(140000)
-    @parametrize_with_ids("tp_size,ep_size", [(8, 8)])
-    def test_auto_dtype(self, tp_size, ep_size):
-        model_path = f"{llm_models_root()}/Step-3.7-Flash"
-        kv_cache_config = KvCacheConfig(free_gpu_memory_fraction=0.7)
-        with LLM(model_path,
-                 tensor_parallel_size=tp_size,
-                 moe_expert_parallel_size=ep_size,
-                 kv_cache_config=kv_cache_config,
-                 max_seq_len=8192,
-                 trust_remote_code=True) as llm:
-            task = GSM8K(self.MODEL_NAME)
-            task.evaluate(llm)
-
-    @pytest.mark.skip_less_device(4)
-    @pytest.mark.skip_less_device_memory(80000)
-    @parametrize_with_ids("mtp_nextn", [0, 3])
-    @parametrize_with_ids("tp_size,ep_size", [(4, 4)])
-    def test_fp8_block_scales(self, tp_size, ep_size, mtp_nextn):
-        model_path = f"{llm_models_root()}/Step-3.7-Flash-FP8"
-        kv_cache_config = KvCacheConfig(free_gpu_memory_fraction=0.7,
-                                        use_kv_cache_manager_v2=True)
-        pytorch_config = dict(
-            disable_overlap_scheduler=False,
-            cuda_graph_config=CudaGraphConfig(enable_padding=True),
-            moe_config=MoeConfig(backend="TRTLLM"),
-        )
-
-        mtp_config = None
-        if mtp_nextn > 0:
-            mtp_config = MTPDecodingConfig(max_draft_len=mtp_nextn)
-
-        with LLM(model_path,
-                 tensor_parallel_size=tp_size,
-                 moe_expert_parallel_size=ep_size,
-                 kv_cache_config=kv_cache_config,
-                 max_seq_len=8192,
-                 attn_backend="TRTLLM",
-                 speculative_config=mtp_config,
-                 trust_remote_code=True,
-                 **pytorch_config) as llm:
-            assert llm.args.quant_config.quant_algo == QuantAlgo.FP8_BLOCK_SCALES
-            task = GSM8K(self.MODEL_NAME)
-            task.evaluate(llm)
-
-    @pytest.mark.skip_less_device(4)
-    @pytest.mark.skip_less_device_memory(80000)
-    @parametrize_with_ids("mtp_nextn", [0, 3])
-    @parametrize_with_ids("tp_size,ep_size", [(4, 4)])
-    def test_nvfp4(self, tp_size, ep_size, mtp_nextn):
-        model_path = f"{llm_models_root()}/Step-3.7-Flash-NVFP4"
-        kv_cache_config = KvCacheConfig(free_gpu_memory_fraction=0.7,
-                                        use_kv_cache_manager_v2=True)
-        pytorch_config = dict(
-            disable_overlap_scheduler=False,
-            cuda_graph_config=CudaGraphConfig(enable_padding=True),
-            moe_config=MoeConfig(backend="TRTLLM"),
-        )
-
-        mtp_config = None
-        if mtp_nextn > 0:
-            mtp_config = MTPDecodingConfig(max_draft_len=mtp_nextn)
-
-        with LLM(model_path,
-                 tensor_parallel_size=tp_size,
-                 moe_expert_parallel_size=ep_size,
-                 kv_cache_config=kv_cache_config,
-                 max_seq_len=8192,
-                 attn_backend="TRTLLM",
-                 speculative_config=mtp_config,
-                 trust_remote_code=True,
-                 **pytorch_config) as llm:
-            assert llm.args.quant_config.quant_algo == QuantAlgo.NVFP4
-            task = GSM8K(self.MODEL_NAME)
-            task.evaluate(llm)

tests/integration/defs/accuracy/test_llm_api_pytorch_multimodal.py

@@ -29,7 +29,6 @@
 from ..conftest import (
     get_sm_version,
     llm_models_root,
-    parametrize_with_ids,
     skip_post_blackwell_ultra,
     skip_pre_blackwell,
     skip_pre_hopper,
@@ -821,82 +820,3 @@ def test_auto_dtype(
                     sampling_params=sampling_params,
                     extra_evaluator_kwargs=extra_evaluator_kwargs,
                 )
-
-
-@skip_pre_blackwell
-class TestStep3_7(LlmapiAccuracyTestHarness):
-    # Step-3.7-Flash is a reasoning VLM: a PerceptionEncoder vision tower plus a
-    # MoE text decoder, registered under the Step3p7ForConditionalGeneration
-    # architecture (custom HF config -> trust_remote_code). MMMU exercises the
-    # vision path end to end. The model emits <think>...</think> traces before
-    # its answer, so we strip them and extract the final MMMU letter (same
-    # handling as Kimi K2.5); preserve_caller_max_tokens keeps our larger
-    # generation budget instead of lm-eval's 512-token default (too small for
-    # the chain-of-thought). The text-only GSM8K path lives in
-    # test_llm_api_pytorch.py::TestStep3_7.
-    MODEL_NAME = "stepfun-ai/Step-3.7-Flash"
-
-    # Validated with --max_input_length / --max_output_length 4096.
-    sampling_params = SamplingParams(
-        max_tokens=4096,
-        truncate_prompt_tokens=4096,
-    )
-
-    EXTRA_EVALUATOR_KWARGS = dict(
-        post_process_fn=strip_thinking_and_extract_mmmu_answer,
-        preserve_caller_max_tokens=True,
-    )
-
-    kv_cache_config = KvCacheConfig(
-        free_gpu_memory_fraction=0.7,
-        use_kv_cache_manager_v2=True,
-    )
-
-    def _make_llm(self, model_path: str, mtp_nextn: int = 0):
-        pytorch_config = dict(
-            disable_overlap_scheduler=False,
-            cuda_graph_config=CudaGraphConfig(enable_padding=False),
-            moe_config=MoeConfig(backend="TRTLLM"),
-        )
-        mtp_config = None
-        if mtp_nextn > 0:
-            mtp_config = MTPDecodingConfig(max_draft_len=mtp_nextn)
-        return LLM(
-            model_path,
-            tensor_parallel_size=4,
-            moe_expert_parallel_size=4,
-            kv_cache_config=self.kv_cache_config,
-            max_seq_len=8192,
-            attn_backend="TRTLLM",
-            speculative_config=mtp_config,
-            trust_remote_code=True,
-            **pytorch_config,
-        )
-
-    @pytest.mark.skip_less_device(4)
-    @pytest.mark.skip_less_device_memory(80000)
-    @parametrize_with_ids("mtp_nextn", [0, 3])
-    def test_fp8_block_scales(self, mtp_nextn):
-        with self._make_llm(f"{llm_models_root()}/Step-3.7-Flash-FP8", mtp_nextn=mtp_nextn) as llm:
-            assert llm.args.quant_config.quant_algo == QuantAlgo.FP8_BLOCK_SCALES
-            task = MMMU(self.MODEL_NAME)
-            task.evaluate(
-                llm,
-                sampling_params=self.sampling_params,
-                extra_evaluator_kwargs=self.EXTRA_EVALUATOR_KWARGS,
-            )
-
-    @pytest.mark.skip_less_device(4)
-    @pytest.mark.skip_less_device_memory(80000)
-    @parametrize_with_ids("mtp_nextn", [0, 3])
-    def test_nvfp4(self, mtp_nextn):
-        with self._make_llm(
-            f"{llm_models_root()}/Step-3.7-Flash-NVFP4", mtp_nextn=mtp_nextn
-        ) as llm:
-            assert llm.args.quant_config.quant_algo == QuantAlgo.NVFP4
-            task = MMMU(self.MODEL_NAME)
-            task.evaluate(
-                llm,
-                sampling_params=self.sampling_params,
-                extra_evaluator_kwargs=self.EXTRA_EVALUATOR_KWARGS,
-            )

tests/integration/test_lists/qa/llm_function_core.txt

@@ -772,11 +772,6 @@ accuracy/test_llm_api_pytorch.py::TestQwen3_8B::test_fp8_block_scales_early_firs
 accuracy/test_llm_api_pytorch.py::TestQwen3_8B::test_w4a8_mxfp4[fp8-latency]
 accuracy/test_llm_api_pytorch.py::TestQwen3_8B::test_w4a8_mxfp4[mxfp8-latency]
 accuracy/test_llm_api_pytorch.py::TestSeedOss_36B::test_auto_dtype
-accuracy/test_llm_api_pytorch.py::TestStep3_7::test_auto_dtype[tp_size=8-ep_size=8] TIMEOUT (90)
-accuracy/test_llm_api_pytorch.py::TestStep3_7::test_fp8_block_scales[tp_size=4-ep_size=4-mtp_nextn=0] TIMEOUT (90)
-accuracy/test_llm_api_pytorch.py::TestStep3_7::test_fp8_block_scales[tp_size=4-ep_size=4-mtp_nextn=3] TIMEOUT (90)
-accuracy/test_llm_api_pytorch.py::TestStep3_7::test_nvfp4[tp_size=4-ep_size=4-mtp_nextn=0] TIMEOUT (90)
-accuracy/test_llm_api_pytorch.py::TestStep3_7::test_nvfp4[tp_size=4-ep_size=4-mtp_nextn=3] TIMEOUT (90)
 accuracy/test_llm_api_pytorch_encode.py::TestDecoderEncode::test_decoder_encode_cuda_graph_matches_eager_logits[tinyllama-1.1b]
 accuracy/test_llm_api_pytorch_encode.py::TestDecoderEncode::test_decoder_encode_matches_huggingface[gemma-3-1b]
 accuracy/test_llm_api_pytorch_encode.py::TestDecoderEncode::test_decoder_encode_matches_huggingface[qwen2-7b]
@@ -806,10 +801,6 @@ accuracy/test_llm_api_pytorch_multimodal.py::TestQwen3VL_MOE::test_auto_dtype
 accuracy/test_llm_api_pytorch_multimodal.py::TestQwen3_5_27B_VL::test_auto_dtype
 accuracy/test_llm_api_pytorch_multimodal.py::TestQwen3_5_35B_A3B_VL::test_auto_dtype
 accuracy/test_llm_api_pytorch_multimodal.py::TestQwen3_5_35B_A3B_VL::test_fp8_prequantized
-accuracy/test_llm_api_pytorch_multimodal.py::TestStep3_7::test_fp8_block_scales[mtp_nextn=0] TIMEOUT (120)
-accuracy/test_llm_api_pytorch_multimodal.py::TestStep3_7::test_fp8_block_scales[mtp_nextn=3] TIMEOUT (120)
-accuracy/test_llm_api_pytorch_multimodal.py::TestStep3_7::test_nvfp4[mtp_nextn=0] TIMEOUT (120)
-accuracy/test_llm_api_pytorch_multimodal.py::TestStep3_7::test_nvfp4[mtp_nextn=3] TIMEOUT (120)
 accuracy/test_llm_api_pytorch_ray.py::TestLlama3_1_8BInstruct::test_pp2_ray
 unittest/disaggregated/test_cache_transceiver_single_process.py::test_cache_transceiver_v1_masked_dsa_indexer_across_asymmetric_pp
 disaggregated/test_ad_disagg.py::test_async_eagle3_full_model_handoff

tests/integration/test_lists/waives.txt

@@ -169,7 +169,6 @@ full:B300/accuracy/test_llm_api_pytorch.py::TestMiniMaxM3::test_nvfp4[use_msa=Fa
 full:B300/accuracy/test_llm_api_pytorch.py::TestMistralLarge3_675B::test_nvfp4_4gpus[latency_moe_trtllm] SKIP (https://nvbugs/6529874)
 full:B300/accuracy/test_llm_api_pytorch.py::TestNemotronV3Ultra::test_nvfp4_8gpus[attention_dp_off-trtllm] SKIP (https://nvbugs/6474894)
 full:B300/accuracy/test_llm_api_pytorch.py::TestQwen3_30B_A3B::test_dummy_load_format SKIP (https://nvbugs/6525059)
-full:B300/accuracy/test_llm_api_pytorch.py::TestStep3_7::test_fp8_block_scales[tp_size=4-ep_size=4-mtp_nextn=3] SKIP (https://nvbugs/6539941)
 full:B300/accuracy/test_llm_api_pytorch_multimodal.py::TestExaone4_5_33B::test_auto_dtype[forced_chunked_prefill] SKIP (https://nvbugs/6597570)
 full:B300/accuracy/test_llm_api_pytorch_multimodal.py::TestExaone4_5_33B::test_auto_dtype[full_budget] SKIP (https://nvbugs/6597570)
 full:B300/disaggregated/test_disaggregated.py::test_disaggregated_logprobs_serving[llama-3.1-8b-instruct] SKIP (https://nvbugs/6275959)