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   "metric": "throughput_offline",
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   "size_class": "unknown",
   "batch": "unknown",
   "like_for_like": true,
   "differs": [],
   "confidence": "A",
   "confidence_label": "A – audited (MLPerf closed)",
   "power_w": null,
   "power_label": "no power published",
   "power_kind": "unknown",
   "perf_per_w": null,
   "date": "2026-09-16 (published)",
   "older_than_18_months": false,
   "superseded": false,
   "power_basis": "unknown",
   "price_usd": null,
   "price_label": "unknown",
   "price_date": null,
   "price_launch_usd": null,
   "edge": false,
   "date_basis": "published",
   "form_factor": "datacenter server",
   "vendor": "AMD",
   "source": {
    "name": "MLPerf Inference v6.1 (closed, datacenter) system 8xMI350X_2xEPYC_9655",
    "url": "https://github.com/mlcommons/inference_results_v6.1/tree/main/closed/AMD/results/8xMI350X_2xEPYC_9655",
    "date": null
   },
   "power_source": null,
   "price_source": null,
   "fit": {
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    "power": null,
    "budget": null
   },
   "meets_all": true,
   "unknowns": 0,
   "eligible": true,
   "headroom": null,
   "rank_score": 0.0863,
   "unknown_badges": [
    "power unknown",
    "perf/W unknown",
    "price unknown"
   ],
   "evidence_tier": 1
  },
  {
   "platform": "NVIDIA DGX B200 (8x NVIDIA B200-SXM-180GB)",
   "platform_url": "/platform/nvidia-dgx-b200-8x-nvidia-b200-sxm-180gb.html",
   "perf": 0.0464402,
   "perf_unit": "FPS",
   "metric": "throughput_offline",
   "model": "MLPerf wan-2.2-t2v-a14b",
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   "stack": "TensorRT 10.14, CUDA 13.1, cuDNN 9.17, TensorRT-LLM feat/1.2-mlpinf, NVIDIA Dynamo mlperf-v6.0-dynamo-v0.8.0, vLLM CentM",
   "size_class": "unknown",
   "batch": "unknown",
   "like_for_like": true,
   "differs": [],
   "confidence": "A",
   "confidence_label": "A – audited (MLPerf closed)",
   "power_w": null,
   "power_label": "no power published",
   "power_kind": "unknown",
   "perf_per_w": null,
   "date": "2026-04-01 (published)",
   "older_than_18_months": false,
   "superseded": false,
   "power_basis": "unknown",
   "price_usd": null,
   "price_label": "unknown",
   "price_date": null,
   "price_launch_usd": null,
   "edge": false,
   "date_basis": "published",
   "form_factor": "datacenter server",
   "vendor": "NVIDIA",
   "source": {
    "name": "MLPerf Inference v6.0 (closed, datacenter) ID 6.0-0072",
    "url": "https://github.com/mlcommons/submissions_inference_v6.0/tree/main/closed/NVIDIA/results/B200-SXM-180GBx8_TRT",
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   },
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   "fit": {
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    "power": null,
    "budget": null
   },
   "meets_all": true,
   "unknowns": 0,
   "eligible": true,
   "headroom": null,
   "rank_score": 0.0709,
   "unknown_badges": [
    "power unknown",
    "perf/W unknown",
    "price unknown"
   ],
   "evidence_tier": 1
  },
  {
   "platform": "XE7745_8xMI350P_2xEPYC_9455 (8x AMD Instinct MI350P)",
   "platform_url": "/platform/xe7745-8xmi350p-2xepyc-9455-8x-amd-instinct-mi350p.html",
   "perf": 0.0345875,
   "perf_unit": "FPS",
   "metric": "throughput_offline",
   "model": "MLPerf wan-2.2-t2v-a14b",
   "precision": "bf16, fp8, fp4",
   "stack": "vLLM 0.22.0, PyTorch 2.10.0, ROCm 7.2.2",
   "size_class": "unknown",
   "batch": "unknown",
   "like_for_like": true,
   "differs": [],
   "confidence": "A",
   "confidence_label": "A – audited (MLPerf closed)",
   "power_w": null,
   "power_label": "no power published",
   "power_kind": "unknown",
   "perf_per_w": null,
   "date": "2026-09-16 (published)",
   "older_than_18_months": false,
   "superseded": false,
   "power_basis": "unknown",
   "price_usd": null,
   "price_label": "unknown",
   "price_date": null,
   "price_launch_usd": null,
   "edge": false,
   "date_basis": "published",
   "form_factor": "datacenter server",
   "vendor": "Dell_AMD",
   "source": {
    "name": "MLPerf Inference v6.1 (closed, datacenter) system XE7745_8xMI350P_2xEPYC-9455",
    "url": "https://github.com/mlcommons/inference_results_v6.1/tree/main/closed/Dell_AMD/results/XE7745_8xMI350P_2xEPYC-9455",
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   },
   "power_source": null,
   "price_source": null,
   "fit": {
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    "power": null,
    "budget": null
   },
   "meets_all": true,
   "unknowns": 0,
   "eligible": true,
   "headroom": null,
   "rank_score": 0.0528,
   "unknown_badges": [
    "power unknown",
    "perf/W unknown",
    "price unknown"
   ],
   "evidence_tier": 1
  },
  {
   "platform": "HPE Cray XD670 (8x NVIDIA H200-SXM-141GB)",
   "platform_url": "/platform/hpe-cray-xd670-8x-nvidia-h200-sxm-141gb.html",
   "perf": 0.0241194,
   "perf_unit": "FPS",
   "metric": "throughput_offline",
   "model": "MLPerf wan-2.2-t2v-a14b",
   "precision": "bfloat16",
   "stack": "KISS-V: Krai Inference Serving Solution for Video (Fast Mode)",
   "size_class": "unknown",
   "batch": "unknown",
   "like_for_like": true,
   "differs": [],
   "confidence": "B",
   "confidence_label": "B – documented third-party method",
   "power_w": null,
   "power_label": "no power published",
   "power_kind": "unknown",
   "perf_per_w": null,
   "date": "2026-04-01 (published)",
   "older_than_18_months": false,
   "superseded": false,
   "power_basis": "unknown",
   "price_usd": null,
   "price_label": "unknown",
   "price_date": null,
   "price_launch_usd": null,
   "edge": false,
   "date_basis": "published",
   "form_factor": "datacenter server",
   "vendor": "Krai",
   "source": {
    "name": "MLPerf Inference v6.0 (open, datacenter) ID 6.0-0108",
    "url": "https://github.com/mlcommons/submissions_inference_v6.0/tree/main/open/Krai/results/h200_n1-kissv",
    "date": null
   },
   "power_source": null,
   "price_source": null,
   "fit": {
    "perf": null,
    "power": null,
    "budget": null
   },
   "meets_all": true,
   "unknowns": 0,
   "eligible": true,
   "headroom": null,
   "rank_score": 0.0368,
   "unknown_badges": [
    "power unknown",
    "perf/W unknown",
    "price unknown"
   ],
   "evidence_tier": 1
  },
  {
   "platform": "NVIDIA Jetson AGX Orin 64GB",
   "platform_url": "/platform/nvidia-jetson-agx-orin-64gb.html",
   "perf": 0.08,
   "perf_unit": "FPS",
   "metric": "latency_single_stream",
   "model": "MLPerf stable-diffusion-xl",
   "precision": "per MLPerf v4.0 submission",
   "stack": "TensorRT 9.0.1, JetPack 5.1.1, CUDA 11.4",
   "size_class": "unknown",
   "batch": "unknown",
   "like_for_like": true,
   "differs": [],
   "confidence": "D",
   "confidence_label": "D – vendor-published",
   "power_w": 65,
   "power_label": "platform spec envelope (not measured with this result)",
   "power_kind": "spec",
   "perf_per_w": 0.001231,
   "date": "2024-03-27 (published)",
   "older_than_18_months": true,
   "superseded": false,
   "power_basis": "max TDP per OpenNav report / mypcrig price",
   "price_usd": 3499,
   "price_label": "NVIDIA marketplace list price (US), Jetson AGX Orin Developer Kit (64GB), 2026-10-16",
   "price_date": "2026-10-16",
   "price_launch_usd": 1999,
   "edge": true,
   "date_basis": "published",
   "form_factor": "edge module",
   "vendor": "NVIDIA",
   "source": {
    "name": "NVIDIA Jetson Benchmarks (MLPerf v4.0 results table)",
    "url": "https://developer.nvidia.com/embedded/jetson-benchmarks",
    "date": null
   },
   "power_source": "https://opennav.org/news/opennav-robotics-workload-benchmark/",
   "price_source": "https://marketplace.nvidia.com/en-us/enterprise/robotics-edge/jetson-agx-orin-developer-kit/",
   "fit": {
    "perf": null,
    "power": null,
    "budget": null
   },
   "meets_all": true,
   "unknowns": 0,
   "eligible": true,
   "headroom": null,
   "rank_score": 0.5611,
   "unknown_badges": [],
   "evidence_tier": 0
  }
 ],
 "no_data": null,
 "legend": "Confidence: A audited MLPerf closed, B documented third-party, C community, D vendor-published, E estimate. Unknown is never assumed."
}