[AndreasKaratzas]

• Add four-GPU MI355 mirrors and matching native AMD jobs for all five large-model groups: DeepSeek R1 TP/DP, DeepSeek V3.2 TP/DP, and Nemotron Super BF16/FP8.
• Use AITER MLA/MoE for DeepSeek and Triton Mamba/MoE for Nemotron; allow DeepSeek evaluations to execute on CDNA 4 and newer while retaining the older ROCm pool's infrastructure guard.
• Preserve NVIDIA configurations and the full evaluation workload: identical checkpoints and precision, EP and MTP enabled with unchanged draft counts, 1,319 questions, five shots, 95% DeepSeek and 93% Nemotron targets, and the shared eight-percentage-point tolerance; AMD uses TP4/DP4 with EP4.
• Validate all six configurations on both four and eight MI355s: 12 full GSM8K runs passed without skips or invalid answers, with accuracies of 93.03–95.75% and unchanged CI memory defaults.

The merged #57965 split H200 large-model evaluation into five groups without corresponding MI355 mirrors. This follow-up complements #34839 with executable MI355 DeepSeek and Nemotron coverage.

OpenAI Codex assisted with the implementation and local validation.

Configuration	Four-GPU accuracy	Four-GPU total	Eight-GPU accuracy	Eight-GPU total
DeepSeek R1 TP	95.30%	3:10	94.31%	3:23
DeepSeek R1 DP	95.75%	3:59	95.07%	3:41
DeepSeek V3.2 TP	95.53%	3:08	95.75%	3:22
DeepSeek V3.2 DP	95.60%	4:16	95.30%	4:16
Nemotron Super BF16	93.25%	2:04	93.33%	1:59
Nemotron Super FP8	93.03%	2:13	93.10%	2:18

All twelve cases passed the original assertions: DeepSeek's passing floor is 87% and Nemotron's is 85%, after the existing eight-percentage-point tolerance. Every case evaluated all 1,319 questions with five shots, maximum output length 256 and default GPU memory utilization 0.92. Four-GPU CI retains model, precision, attention, Mamba, EP and MTP coverage but does not replace continuous eight-rank coverage.

[claude]

Claude Code Review

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[AndreasKaratzas]

/ci run

[github-actions]

✅ Triggered Buildkite CI #91685 for commit e39b40d79624.