[Bugfix] Update TrtLLM MoE routing methods

[wzhao18]

Purpose

The PR introduces various fixes related to Trtllm MoE routing methods:

• Revert _supports_router_logits_dtype change from [Model]Support Step-3.7-Flash #43859, which causes regression in nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-FP8, see CI failure

ValueError: FP8 MoE backend FLASHINFER_TRTLLM does not support the deployment configuration since kernel does not support quantization scheme QuantKey(f8e4m3fn,scale(f32,static,per_tensor),symmetric)xQuantKey(f8e4m3fn,scale(f32,static,per_tensor),symmetric).

• Update RoutingMethodType in correspondence with flashinfer.
• Refine get_routing_method_type to prevent stepfun-ai/Step-3.7-Flash from being categorized into Minimax-M2 routing.
• Remove casting of e_score_correction_bias as fixed in flashinfer.

Test Plan

• GSM8k eval:
  • Deepseek R1 (fp8 and nvfp4)
  • Minimax M2.7 (fp8 and nvfp4)
  • Nemotron-3-Nano (fp8)
  • Step-3.7-Flash (bf16, fp8 and nvfp4)

Test Result

# Nemotron-3-Nano
vllm serve nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-FP8 --enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --moe-backend=flashinfer_trtllm --trust-remote-code

|Tasks|Version|     Filter     |n-shot|  Metric   |   |Value |   |Stderr|
|-----|------:|----------------|-----:|-----------|---|-----:|---|-----:|
|gsm8k|      3|flexible-extract|     5|exact_match|↑  |0.5648|±  |0.0137|
|     |       |strict-match    |     5|exact_match|↑  |0.8514|±  |0.0098|

# DeepSeek R1 FP8
vllm serve deepseek-ai/DeepSeek-R1 --trust-remote-code --tensor-parallel-size 8

|Tasks|Version|     Filter     |n-shot|  Metric   |   |Value |   |Stderr|
|-----|------:|----------------|-----:|-----------|---|-----:|---|-----:|
|gsm8k|      3|flexible-extract|     5|exact_match|↑  |0.9575|±  |0.0056|
|     |       |strict-match    |     5|exact_match|↑  |0.9560|±  |0.0056|

# DeepSeek R1 NVFP4
vllm serve nvidia/DeepSeek-R1-NVFP4 --trust-remote-code --tensor-parallel-size 8

|Tasks|Version|     Filter     |n-shot|  Metric   |   |Value |   |Stderr|
|-----|------:|----------------|-----:|-----------|---|-----:|---|-----:|
|gsm8k|      3|flexible-extract|     5|exact_match|↑  |0.9409|±  |0.0065|
|     |       |strict-match    |     5|exact_match|↑  |0.9386|±  |0.0066|

# Minimax M2 FP8
vllm serve MiniMaxAI/MiniMax-M2.5 --trust-remote-code --tensor-parallel-size 4

|Tasks|Version|     Filter     |n-shot|  Metric   |   |Value |   |Stderr|
|-----|------:|----------------|-----:|-----------|---|-----:|---|-----:|
|gsm8k|      3|flexible-extract|     5|exact_match|↑  |0.9204|±  |0.0075|
|     |       |strict-match    |     5|exact_match|↑  |0.9174|±  |0.0076|

|Tasks|Version|     Filter     |n-shot|  Metric   |   |Value |   |Stderr|
|-----|------:|----------------|-----:|-----------|---|-----:|---|-----:|
|gsm8k|      3|flexible-extract|     5|exact_match|↑  |0.9318|±  |0.0069|
|     |       |strict-match    |     5|exact_match|↑  |0.9280|±  |0.0071|

# Minimax M2 NVFP4
vllm serve nvidia/MiniMax-M2.5-NVFP4 --trust-remote-code --tensor-parallel-size 4

# Step-3.7-Flash BF16
vllm serve stepfun-ai/Step-3.7-Flash \
--tensor-parallel-size 8 \
--enable-expert-parallel \
--disable-cascade-attn \
--reasoning-parser step3p5 \
--enable-auto-tool-choice \
--tool-call-parser step3p5 \
--speculative_config '{"method": "mtp", "num_speculative_tokens": 3}' \
--trust-remote-code

|Tasks|Version|     Filter     |n-shot|  Metric   |   |Value |   |Stderr|
|-----|------:|----------------|-----:|-----------|---|-----:|---|-----:|
|gsm8k|      3|flexible-extract|     5|exact_match|↑  |0.8901|±  |0.0086|
|     |       |strict-match    |     5|exact_match|↑  |0.8901|±  |0.0086|

# Step-3.7-Flash FP8
vllm serve stepfun-ai/Step-3.7-Flash-FP8 \
  --tensor-parallel-size 8 \
  --enable-expert-parallel \
  --disable-cascade-attn \
  --reasoning-parser step3p5 \
  --enable-auto-tool-choice \
  --tool-call-parser step3p5 \
  --speculative_config '{"method": "mtp", "num_speculative_tokens": 3}' \
  --trust-remote-code

|Tasks|Version|     Filter     |n-shot|  Metric   |   |Value |   |Stderr|
|-----|------:|----------------|-----:|-----------|---|-----:|---|-----:|
|gsm8k|      3|flexible-extract|     5|exact_match|↑  |0.8855|±  |0.0088|
|     |       |strict-match    |     5|exact_match|↑  |0.8840|±  |0.0088|

# Step-3.7-Flash NVFP4
python3 -m vllm.entrypoints.openai.api_server \
--model stepfun-ai/Step-3.7-Flash-NVFP4 \
--served-model-name step3p7 \
--tensor-parallel-size 4 \
--gpu-memory-utilization 0.9 \
--enable-expert-parallel \
--trust-remote-code \
--quantization modelopt \
--kv-cache-dtype fp8 \
--max-model-len 8192 \
--reasoning-parser step3p5 \
--enable-auto-tool-choice \
--tool-call-parser step3p5 \
--async-scheduling

|Tasks|Version|     Filter     |n-shot|  Metric   |   |Value |   |Stderr|
|-----|------:|----------------|-----:|-----------|---|-----:|---|-----:|
|gsm8k|      3|flexible-extract|     5|exact_match|↑  |0.8817|±  |0.0089|
|     |       |strict-match    |     5|exact_match|↑  |0.8817|±  |0.0089|

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Essential Elements of an Effective PR Description Checklist

• The purpose of the PR, such as "Fix some issue (link existing issues this PR will resolve)".
• The test plan, such as providing test command.
• The test results, such as pasting the results comparison before and after, or e2e results
• (Optional) The necessary documentation update, such as updating supported_models.md and examples for a new model.