Add vLLM v0.18.1 source tree with KV transfer abort fix

third_party/vllm/ now tracked in git for direct patch management.
Based on vLLM v0.18.1 release with one patch applied:

  vllm/v1/core/sched/scheduler.py:
    Replace fatal assert with graceful skip when KV transfer callback
    arrives for an already-aborted request during PD disaggregated serving.

Future vLLM modifications should be made directly in third_party/vllm/
and committed normally. The patches/ directory is kept as documentation
of what changed from upstream.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
2026-05-22 00:30:38 +08:00
parent b6591950bc
commit 445e491123
4285 changed files with 1111303 additions and 1 deletions

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model_name: "deepseek-ai/DeepSeek-R1"
accuracy_threshold: 0.95
num_questions: 1319
num_fewshot: 5
startup_max_wait_seconds: 1200
server_args: >-
--enforce-eager
--max-model-len 4096
--data-parallel-size 8
--enable-expert-parallel
--speculative-config '{"method":"mtp","num_speculative_tokens":3}'

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@@ -0,0 +1,11 @@
model_name: "deepseek-ai/DeepSeek-R1"
accuracy_threshold: 0.95
num_questions: 1319
num_fewshot: 5
startup_max_wait_seconds: 1200
server_args: >-
--enforce-eager
--max-model-len 4096
--tensor-parallel-size 8
--enable-expert-parallel
--speculative-config '{"method":"mtp","num_speculative_tokens":3}'

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@@ -0,0 +1,5 @@
model_name: "RedHatAI/DeepSeek-Coder-V2-Lite-Instruct-FP8"
accuracy_threshold: 0.72
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 4096"

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@@ -0,0 +1,11 @@
model_name: "deepseek-ai/DeepSeek-V3.2"
accuracy_threshold: 0.95
num_questions: 1319
num_fewshot: 5
startup_max_wait_seconds: 1200
server_args: >-
--enforce-eager
--max-model-len 4096
--data-parallel-size 8
--enable-expert-parallel
--speculative-config '{"method":"mtp","num_speculative_tokens":3}'

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@@ -0,0 +1,11 @@
model_name: "deepseek-ai/DeepSeek-V3.2"
accuracy_threshold: 0.95
num_questions: 1319
num_fewshot: 5
startup_max_wait_seconds: 1200
server_args: >-
--enforce-eager
--max-model-len 4096
--tensor-parallel-size 8
--enable-expert-parallel
--speculative-config '{"method":"mtp","num_speculative_tokens":3}'

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@@ -0,0 +1,5 @@
model_name: "nm-testing/Meta-Llama-3-8B-Instruct-nonuniform-test"
accuracy_threshold: 0.74
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 4096"

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@@ -0,0 +1,5 @@
model_name: "RedHatAI/Llama-3.2-1B-Instruct-quantized.w8a8"
accuracy_threshold: 0.31
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 4096"

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model_name: "nm-testing/Qwen1.5-MoE-A2.7B-Chat-quantized.w4a16"
accuracy_threshold: 0.45
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 4096"

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@@ -0,0 +1,5 @@
model_name: "RedHatAI/Qwen2.5-VL-3B-Instruct-FP8-Dynamic"
accuracy_threshold: 0.60
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 4096"

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@@ -0,0 +1,5 @@
model_name: "Qwen/Qwen3-0.6B-FP8"
accuracy_threshold: 0.375
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 4096"

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@@ -0,0 +1,5 @@
model_name: nm-testing/Qwen3-30B-A3B-MXFP4A16
accuracy_threshold: 0.88
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 4096"

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@@ -0,0 +1,5 @@
model_name: "nvidia/Qwen3-30B-A3B-FP4"
accuracy_threshold: 0.89
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 4096"

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model_name: "nm-testing/Qwen3-Next-80B-A3B-Instruct-NVFP4"
accuracy_threshold: 0.75
num_questions: 1319
num_fewshot: 5
server_args: >-
--enforce-eager
--max-model-len 4096
--tensor-parallel-size 2
--enable-expert-parallel
--speculative-config '{"method":"qwen3_next_mtp","num_speculative_tokens":1}'
--moe-backend=flashinfer_trtllm

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@@ -0,0 +1,10 @@
model_name: "Qwen/Qwen3-Next-80B-A3B-Instruct-FP8"
accuracy_threshold: 0.85
num_questions: 1319
num_fewshot: 5
server_args: >-
--max-model-len 4096
--tensor-parallel-size 2
--enable-expert-parallel
--async-scheduling
--moe-backend=flashinfer_trtllm

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@@ -0,0 +1,9 @@
model_name: "Qwen/Qwen3-Next-80B-A3B-Instruct-FP8"
accuracy_threshold: 0.85
num_questions: 1319
num_fewshot: 5
server_args: >-
--max-model-len 4096
--tensor-parallel-size 2
--enable-expert-parallel
--async-scheduling

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@@ -0,0 +1,9 @@
model_name: "Qwen/Qwen3.5-35B-A3B"
accuracy_threshold: 0.84
tolerance: 0.03
num_questions: 1319
num_fewshot: 5
server_args: >-
--max-model-len 4096
--data-parallel-size 2
--enable-expert-parallel

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@@ -0,0 +1,10 @@
model_name: "Qwen/Qwen3.5-35B-A3B-FP8"
accuracy_threshold: 0.79
tolerance: 0.03
num_questions: 1319
num_fewshot: 5
server_args: >-
--max-model-len 4096
--data-parallel-size 2
--enable-expert-parallel
--kv-cache-dtype fp8

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@@ -0,0 +1,9 @@
model_name: "nvidia/Qwen3.5-397B-A17B-NVFP4"
accuracy_threshold: 0.88
tolerance: 0.03
num_questions: 1319
num_fewshot: 5
server_args: >-
--max-model-len 4096
--data-parallel-size 2
--enable-expert-parallel

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@@ -0,0 +1,7 @@
Qwen3-0.6B-FP8.yaml
Qwen2.5-VL-3B-Instruct-FP8-dynamic.yaml
Qwen1.5-MoE-W4A16-CT.yaml
DeepSeek-V2-Lite-Instruct-FP8.yaml
Qwen3-30B-A3B-NVFP4.yaml
Qwen3-Next-80B-A3B-NVFP4-EP2.yaml
Qwen3-Next-FP8-EP2.yaml

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DeepSeek-R1-TP.yaml
DeepSeek-R1-DP.yaml
DeepSeek-V3.2-TP.yaml
DeepSeek-V3.2-DP.yaml

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@@ -0,0 +1,5 @@
Qwen3-0.6B-FP8.yaml
Qwen2.5-VL-3B-Instruct-FP8-dynamic.yaml
Qwen1.5-MoE-W4A16-CT.yaml
DeepSeek-V2-Lite-Instruct-FP8.yaml
Qwen3-Next-FP8-EP2_MI355.yaml

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@@ -0,0 +1,3 @@
Qwen3.5-35B-A3B-DEP2.yaml
Qwen3.5-35B-A3B-FP8-DEP2.yaml
Qwen3.5-397B-A17B-NVFP4-DEP2.yaml

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Qwen3-0.6B-FP8.yaml
Llama-3.2-1B-Instruct-INT8-CT.yaml
Llama-3-8B-Instruct-nonuniform-CT.yaml
Qwen2.5-VL-3B-Instruct-FP8-dynamic.yaml
Qwen1.5-MoE-W4A16-CT.yaml
DeepSeek-V2-Lite-Instruct-FP8.yaml
Qwen3-30B-A3B-MXFP4A16.yaml

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model_name: "nvidia/Llama-4-Scout-17B-16E-Instruct-FP8"
accuracy_threshold: 0.92
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --data-parallel-size 2 --enable-expert-parallel --moe-backend=triton"
env:
VLLM_USE_DEEP_GEMM: "0"

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model_name: "Qwen/Qwen3-30B-A3B"
accuracy_threshold: 0.88
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --data-parallel-size 2 --enable-expert-parallel"

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model_name: "Qwen/Qwen3-Coder-30B-A3B-Instruct-FP8"
accuracy_threshold: 0.88
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --data-parallel-size 2 --enable-expert-parallel --all2all-backend deepep_high_throughput"
env:
VLLM_USE_DEEP_GEMM: "1"
VLLM_USE_DEEP_GEMM_MOE: "1"

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@@ -0,0 +1,8 @@
model_name: "Qwen/Qwen3-Coder-30B-A3B-Instruct-FP8"
accuracy_threshold: 0.88
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --data-parallel-size 2 --enable-expert-parallel --all2all-backend deepep_low_latency --disable-uvicorn-access-log"
env:
VLLM_USE_DEEP_GEMM: "1"
VLLM_USE_DEEP_GEMM_MOE: "1"

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@@ -0,0 +1,8 @@
model_name: "Qwen/Qwen3-Coder-30B-A3B-Instruct-FP8"
accuracy_threshold: 0.88
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --data-parallel-size 2 --enable-expert-parallel"
env:
VLLM_USE_DEEP_GEMM: "1"
VLLM_USE_DEEP_GEMM_MOE: "1"

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@@ -0,0 +1,8 @@
model_name: "RedHatAI/Qwen3-30B-A3B-FP8-block"
accuracy_threshold: 0.85
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --data-parallel-size 2 --enable-expert-parallel --all2all-backend deepep_high_throughput"
env:
VLLM_USE_DEEP_GEMM: "1"
VLLM_USE_DEEP_GEMM_MOE: "1"

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@@ -0,0 +1,8 @@
model_name: "RedHatAI/Qwen3-30B-A3B-FP8-block"
accuracy_threshold: 0.85
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --data-parallel-size 2 --enable-expert-parallel --all2all-backend deepep_low_latency --disable-uvicorn-access-log"
env:
VLLM_USE_DEEP_GEMM: "1"
VLLM_USE_DEEP_GEMM_MOE: "1"

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@@ -0,0 +1,8 @@
model_name: "RedHatAI/Qwen3-30B-A3B-FP8-block"
accuracy_threshold: 0.85
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --data-parallel-size 2 --enable-expert-parallel"
env:
VLLM_USE_DEEP_GEMM: "1"
VLLM_USE_DEEP_GEMM_MOE: "1"

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@@ -0,0 +1,5 @@
model_name: "RedHatAI/Qwen3-30B-A3B-NVFP4"
accuracy_threshold: 0.88
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --data-parallel-size 2 --enable-expert-parallel --all2all-backend deepep_low_latency --moe-backend=flashinfer_cutedsl"

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@@ -0,0 +1,5 @@
model_name: "RedHatAI/Qwen3-30B-A3B-NVFP4"
accuracy_threshold: 0.88
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --data-parallel-size 2 --enable-expert-parallel --moe-backend=flashinfer_cutlass"

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@@ -0,0 +1,5 @@
model_name: "nvidia/Qwen3-30B-A3B-NVFP4"
accuracy_threshold: 0.88
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --data-parallel-size 2 --enable-expert-parallel --all2all-backend deepep_low_latency --moe-backend=flashinfer_cutedsl"

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@@ -0,0 +1,5 @@
model_name: "nvidia/Qwen3-30B-A3B-NVFP4"
accuracy_threshold: 0.88
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --data-parallel-size 2 --enable-expert-parallel --moe-backend=flashinfer_cutlass"

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@@ -0,0 +1,5 @@
model_name: "nvidia/Qwen3-30B-A3B-NVFP4"
accuracy_threshold: 0.88
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --data-parallel-size 2 --enable-expert-parallel --moe-backend=flashinfer_trtllm"

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@@ -0,0 +1,12 @@
Qwen3-30B-A3B-NvFp4-CT-fi-cutedsl-deepep-ll.yaml
Qwen3-30B-A3B-NvFp4-ModelOpt-fi-cutedsl-deepep-ll.yaml
Qwen3-30B-A3B-NvFp4-CT-fi-cutlass.yaml
Qwen3-30B-A3B-NvFp4-ModelOpt-fi-trtllm.yaml
Qwen3-30B-A3B-NvFp4-ModelOpt-fi-cutlass.yaml
Qwen3-30B-A3B-Fp8-AutoFp8-deepgemm-deepep-ht.yaml
Qwen3-30B-A3B-Fp8-AutoFp8-deepgemm-deepep-ll.yaml
Qwen3-30B-A3B-Fp8-AutoFp8-deepgemm.yaml
Qwen3-30B-A3B-Fp8-CT-Block-deepgemm-deepep-ht.yaml
Qwen3-30B-A3B-Fp8-CT-Block-deepgemm-deepep-ll.yaml
Qwen3-30B-A3B-Fp8-CT-Block-deepgemm.yaml
Qwen3-30B-A3B-BF16-triton.yaml

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model_name: "meta-llama/Llama-4-Scout-17B-16E-Instruct"
accuracy_threshold: 0.92
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --enable-expert-parallel --moe-backend=flashinfer_cutlass"

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@@ -0,0 +1,6 @@
model_name: "meta-llama/Llama-4-Scout-17B-16E-Instruct"
accuracy_threshold: 0.92
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2"

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@@ -0,0 +1,5 @@
model_name: "RedHatAI/Llama-4-Scout-17B-16E-Instruct-FP8-dynamic"
accuracy_threshold: 0.92
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2"

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@@ -0,0 +1,5 @@
model_name: "nvidia/Llama-4-Scout-17B-16E-Instruct-FP8"
accuracy_threshold: 0.92
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --moe-backend=flashinfer_cutlass"

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@@ -0,0 +1,5 @@
model_name: "nvidia/Llama-4-Scout-17B-16E-Instruct-FP8"
accuracy_threshold: 0.92
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --moe-backend=flashinfer_trtllm"

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@@ -0,0 +1,7 @@
model_name: "nvidia/Llama-4-Scout-17B-16E-Instruct-FP8"
accuracy_threshold: 0.92
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2"
env:
VLLM_TEST_FORCE_FP8_MARLIN: "1"

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@@ -0,0 +1,5 @@
model_name: "nvidia/Llama-4-Scout-17B-16E-Instruct-FP8"
accuracy_threshold: 0.92
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --moe-backend=triton"

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model_name: "mistralai/Mixtral-8x7B-v0.1"
accuracy_threshold: 0.58
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --enable-expert-parallel --moe-backend=flashinfer_cutlass"

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@@ -0,0 +1,5 @@
model_name: "mistralai/Mixtral-8x7B-v0.1"
accuracy_threshold: 0.58
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2"

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@@ -0,0 +1,6 @@
# TODO(rob): enable
# model_name: "amd/Mixtral-8x7B-Instruct-v0.1-FP8-KV"
# accuracy_threshold: 0.62
# num_questions: 1319
# num_fewshot: 5
# server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --moe-backend=flashinfer_cutlass"

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@@ -0,0 +1,5 @@
model_name: "amd/Mixtral-8x7B-Instruct-v0.1-FP8-KV"
accuracy_threshold: 0.62
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2"

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@@ -0,0 +1,5 @@
model_name: "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-FP8"
accuracy_threshold: 0.29
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --moe-backend=flashinfer_trtllm"

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@@ -0,0 +1,5 @@
model_name: "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-NVFP4"
accuracy_threshold: 0.29
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --moe-backend=flashinfer_cutlass"

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@@ -0,0 +1,5 @@
model_name: "Qwen/Qwen3-30B-A3B"
accuracy_threshold: 0.88
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --enable-expert-parallel --moe-backend=flashinfer_cutlass"

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@@ -0,0 +1,5 @@
model_name: "Qwen/Qwen3-30B-A3B"
accuracy_threshold: 0.88
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2"

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@@ -0,0 +1,8 @@
model_name: "Qwen/Qwen3-Coder-30B-A3B-Instruct-FP8"
accuracy_threshold: 0.88
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2"
env:
VLLM_USE_DEEP_GEMM: "1"
VLLM_USE_DEEP_GEMM_MOE: "1"

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@@ -0,0 +1,5 @@
model_name: "Qwen/Qwen3-Coder-30B-A3B-Instruct-FP8"
accuracy_threshold: 0.88
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --moe-backend=flashinfer_cutlass"

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@@ -0,0 +1,5 @@
model_name: "Qwen/Qwen3-Coder-30B-A3B-Instruct-FP8"
accuracy_threshold: 0.88
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --moe-backend=flashinfer_trtllm"

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@@ -0,0 +1,7 @@
model_name: "Qwen/Qwen3-Coder-30B-A3B-Instruct-FP8"
accuracy_threshold: 0.88
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2"
env:
VLLM_TEST_FORCE_FP8_MARLIN: "1"

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@@ -0,0 +1,7 @@
model_name: "Qwen/Qwen3-Coder-30B-A3B-Instruct-FP8"
accuracy_threshold: 0.88
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --moe-backend=triton"
env:
VLLM_USE_DEEP_GEMM: "0"

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@@ -0,0 +1,8 @@
model_name: "RedHatAI/Qwen3-30B-A3B-FP8-block"
accuracy_threshold: 0.85
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2"
env:
VLLM_USE_DEEP_GEMM: "1"
VLLM_USE_DEEP_GEMM_MOE: "1"

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@@ -0,0 +1,5 @@
model_name: "RedHatAI/Qwen3-30B-A3B-FP8-block"
accuracy_threshold: 0.85
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --moe-backend=flashinfer_cutlass"

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@@ -0,0 +1,7 @@
model_name: "RedHatAI/Qwen3-30B-A3B-FP8-block"
accuracy_threshold: 0.85
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2"
env:
VLLM_TEST_FORCE_FP8_MARLIN: "1"

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@@ -0,0 +1,7 @@
model_name: "RedHatAI/Qwen3-30B-A3B-FP8-block"
accuracy_threshold: 0.85
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --moe-backend=triton"
env:
VLLM_USE_DEEP_GEMM: "0"

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@@ -0,0 +1,7 @@
model_name: "RedHatAI/Qwen3-30B-A3B-FP8-dynamic"
accuracy_threshold: 0.85
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2"
env:
VLLM_TEST_FORCE_FP8_MARLIN: "1"

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@@ -0,0 +1,5 @@
model_name: "RedHatAI/Qwen3-30B-A3B-FP8-dynamic"
accuracy_threshold: 0.85
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2"

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@@ -0,0 +1,5 @@
model_name: "RedHatAI/Qwen3-30B-A3B-NVFP4"
accuracy_threshold: 0.88
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --moe-backend=flashinfer_cutlass"

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@@ -0,0 +1,5 @@
model_name: "RedHatAI/Qwen3-30B-A3B-NVFP4"
accuracy_threshold: 0.88
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --moe-backend=flashinfer_trtllm"

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model_name: "RedHatAI/Qwen3-30B-A3B-NVFP4"
accuracy_threshold: 0.88
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2"
env:
VLLM_TEST_FORCE_FP8_MARLIN: "1"

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model_name: "RedHatAI/Qwen3-30B-A3B-NVFP4"
accuracy_threshold: 0.88
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --moe-backend=cutlass"

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@@ -0,0 +1,5 @@
model_name: "nvidia/Qwen3-30B-A3B-NVFP4"
accuracy_threshold: 0.88
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --moe-backend=flashinfer_cutlass"

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@@ -0,0 +1,5 @@
model_name: "nvidia/Qwen3-30B-A3B-NVFP4"
accuracy_threshold: 0.88
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --moe-backend=flashinfer_trtllm"

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@@ -0,0 +1,7 @@
model_name: "nvidia/Qwen3-30B-A3B-NVFP4"
accuracy_threshold: 0.88
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2"
env:
VLLM_TEST_FORCE_FP8_MARLIN: "1"

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@@ -0,0 +1,5 @@
model_name: "nvidia/Qwen3-30B-A3B-NVFP4"
accuracy_threshold: 0.88
num_questions: 1319
num_fewshot: 5
server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --moe-backend=cutlass"

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@@ -0,0 +1,17 @@
Llama-4-Scout-Fp8-CT-vllm-cutlass.yaml
Llama-4-Scout-Fp8-ModelOpt-fi-trtllm.yaml
Qwen3-30B-A3B-Fp8-AutoFp8-fi-trtllm.yaml
Qwen3-30B-A3B-NvFp4-CT-vllm-cutlass.yaml
Qwen3-30B-A3B-NvFp4-CT-marlin.yaml
Qwen3-30B-A3B-NvFp4-CT-fi-trtllm.yaml
Qwen3-30B-A3B-NvFp4-CT-fi-cutlass.yaml
Qwen3-30B-A3B-NvFp4-ModelOpt-vllm-cutlass.yaml
Qwen3-30B-A3B-NvFp4-ModelOpt-marlin.yaml
Qwen3-30B-A3B-NvFp4-ModelOpt-fi-trtllm.yaml
Qwen3-30B-A3B-NvFp4-ModelOpt-fi-cutlass.yaml
Llama-4-Scout-BF16-fi-cutlass.yaml
Llama-4-Scout-BF16-triton.yaml
Mixtral-8x7B-BF16-fi-cutlass.yaml
Mixtral-8x7B-BF16-triton.yaml
Nemotron-Nano-30B-Fp8-ModelOpt-fi-trtllm.yaml
Nemotron-Nano-30B-NvFp4-ModelOpt-fi-cutlass.yaml

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@@ -0,0 +1,12 @@
Mixtral-8x7B-Fp8-AutoFp8-triton.yaml
Qwen3-30B-A3B-Fp8-AutoFp8-deepgemm.yaml
Qwen3-30B-A3B-Fp8-AutoFp8-fi-cutlass.yaml
Qwen3-30B-A3B-Fp8-AutoFp8-marlin.yaml
Qwen3-30B-A3B-Fp8-AutoFp8-triton.yaml
Qwen3-30B-A3B-Fp8-CT-Block-deepgemm.yaml
Qwen3-30B-A3B-Fp8-CT-Block-marlin.yaml
Qwen3-30B-A3B-Fp8-CT-Block-triton.yaml
Qwen3-30B-A3B-Fp8-CT-Channel-marlin.yaml
Qwen3-30B-A3B-Fp8-CT-Channel-vllm-cutlass.yaml
Qwen3-30B-A3B-BF16-fi-cutlass.yaml
Qwen3-30B-A3B-BF16-triton.yaml

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@@ -0,0 +1 @@
Qwen3-30B-A3B-NvFp4-CT-marlin.yaml