diff --git a/.buildkite/lm-eval-harness/configs/Qwen3-235B-A22B-Thinking-2507-FP8.yaml b/.buildkite/lm-eval-harness/configs/Qwen3-235B-A22B-Thinking-2507-FP8.yaml
new file mode 100644
index 000000000000..42a20536d811
--- /dev/null
+++ b/.buildkite/lm-eval-harness/configs/Qwen3-235B-A22B-Thinking-2507-FP8.yaml
@@ -0,0 +1,10 @@
+model_name: "Qwen/Qwen3-235B-A22B-Thinking-2507-FP8"
+tasks:
+  - name: "mmlu_pro"
+    metrics:
+    - name: "exact_match,custom-extract"
+      value: 0.77
+num_fewshot: 5
+limit: 250 # will run on 250 * 14 subjects = 3500 samples
+max_model_len: 8096
+gen_kwargs: "top_p=1,top_k=0,max_gen_toks=1536"
diff --git a/.buildkite/lm-eval-harness/configs/Qwen3-8B.yaml b/.buildkite/lm-eval-harness/configs/Qwen3-8B.yaml
new file mode 100644
index 000000000000..7a7b128e0b75
--- /dev/null
+++ b/.buildkite/lm-eval-harness/configs/Qwen3-8B.yaml
@@ -0,0 +1,10 @@
+model_name: "Qwen/Qwen3-8B"
+tasks:
+  - name: "mmlu_pro"
+    metrics:
+    - name: "exact_match,custom-extract"
+      value: 0.60
+num_fewshot: 5
+limit: 250 # will run on 250 * 14 subjects = 3500 samples
+max_model_len: 8096
+gen_kwargs: "top_p=1,top_k=0,max_gen_toks=1536"
diff --git a/.buildkite/lm-eval-harness/configs/models-large-h100.txt b/.buildkite/lm-eval-harness/configs/models-large-h100.txt
index 4fb0b84bc4d8..81381e47134e 100644
--- a/.buildkite/lm-eval-harness/configs/models-large-h100.txt
+++ b/.buildkite/lm-eval-harness/configs/models-large-h100.txt
@@ -1 +1,2 @@
 Meta-Llama-4-Maverick-17B-128E-Instruct-FP8.yaml
+Qwen3-235B-A22B-Thinking-2507-FP8.yaml
diff --git a/.buildkite/lm-eval-harness/configs/models-small.txt b/.buildkite/lm-eval-harness/configs/models-small.txt
index 36e0543879b3..5b87af9fe18f 100644
--- a/.buildkite/lm-eval-harness/configs/models-small.txt
+++ b/.buildkite/lm-eval-harness/configs/models-small.txt
@@ -1,6 +1,6 @@
-Qwen2.5-1.5B-Instruct.yaml
 Meta-Llama-3.2-1B-Instruct-INT8-compressed-tensors.yaml
 Meta-Llama-3-8B-Instruct-INT8-compressed-tensors-asym.yaml
 Meta-Llama-3-8B-Instruct-nonuniform-compressed-tensors.yaml
 Qwen2.5-VL-3B-Instruct-FP8-dynamic.yaml
 Qwen1.5-MoE-W4A16-compressed-tensors.yaml
+Qwen3-8B.yaml
diff --git a/.buildkite/lm-eval-harness/test_lm_eval_correctness.py b/.buildkite/lm-eval-harness/test_lm_eval_correctness.py
index f10de82b1d8e..d2ffcb5a2039 100644
--- a/.buildkite/lm-eval-harness/test_lm_eval_correctness.py
+++ b/.buildkite/lm-eval-harness/test_lm_eval_correctness.py
@@ -40,6 +40,7 @@ def launch_lm_eval(eval_config, tp_size):
         # existing text models in CI, so only apply it for mm.
         apply_chat_template=backend == "vllm-vlm",
         batch_size=batch_size,
+        gen_kwargs=eval_config.get("gen_kwargs", None),
     )
     return results
 
diff --git a/.buildkite/test-pipeline.yaml b/.buildkite/test-pipeline.yaml
index 984e2108f88e..9b9a276eff03 100644
--- a/.buildkite/test-pipeline.yaml
+++ b/.buildkite/test-pipeline.yaml
@@ -1096,7 +1096,7 @@ steps:
   - tests/weight_loading
   commands:
     - bash weight_loading/run_model_weight_loading_test.sh -c weight_loading/models-large.txt
-  
+
 - label: NixlConnector PD accuracy tests (Distributed) # 30min
   timeout_in_minutes: 30
   working_dir: "/vllm-workspace/tests"
@@ -1152,6 +1152,17 @@ steps:
     - pytest -v -s tests/distributed/test_context_parallel.py
     - CUDA_VISIBLE_DEVICES=1,2 VLLM_ALL2ALL_BACKEND=deepep_high_throughput VLLM_USE_DEEP_GEMM=1 VLLM_LOGGING_LEVEL=DEBUG python3 examples/offline_inference/data_parallel.py --model Qwen/Qwen1.5-MoE-A2.7B --tp-size=1  --dp-size=2 --max-model-len 2048
 
+- label: LM Eval Large Models (H200) # optional
+  gpu: h200
+  optional: true
+  num_gpus: 4
+  working_dir: "/vllm-workspace/.buildkite/lm-eval-harness"
+  source_file_dependencies:
+  - csrc/
+  - vllm/model_executor/layers/quantization
+  commands:
+    - pytest -s -v test_lm_eval_correctness.py --config-list-file=configs/models-large-h100.txt --tp-size=4
+
 ##### B200 test #####
 - label: Distributed Tests (B200) # optional
   gpu: b200