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==== 1. Per-accelerator assumptions (TPU v7 Ironwood vs MI450X vs Rubin) ==== Specs I’m using (from public info + one explicit assumption): * TPU v7 Ironwood - FP8: 4.6 PFLOP/s per chip The Register<ref>{{cite web|title=The Register|url=https://www.theregister.com/2025/11/06/googles_ironwood_tpus_ai/|publisher=The Register|date=2025-11-06|access-date=2025-11-29}}</ref> - HBM: 192 GB HBM3E, 7.4 TB/s bandwidth Google Cloud<ref>{{cite web|title=Google Cloud|url=https://cloud.google.com/blog/products/compute/inside-the-ironwood-tpu-codesigned-ai-stack|publisher=Google Cloud|access-date=2025-11-29}}</ref> - Power: you told me to assume 1000 W (this lines up with 9,216 chips ≈ 10 MW in Google material → ~1 kW/chip). XPU.pub<ref>{{cite web|title=XPU.pub|url=https://xpu.pub/2025/04/16/google-ironwood/|publisher=xpu.pub|date=2025-04-16|access-date=2025-11-29}}</ref> - FP4: not published. I’ll assume 2× FP8 throughput ≈ 9.2 PFLOP/s (same pattern as other tensor cores). This is a model assumption, not a spec. * AMD Instinct MI450X - From AMD Helios rack numbers: 72 MI450 → 1.4 EF FP8, 2.9 EF FP4 per rack, so per GPU: - FP8 ≈ 19.4 PFLOP/s, FP4 ≈ 40.3 PFLOP/s AMD<ref>{{cite web|title=AMD|url=https://www.amd.com/en/blogs/2025/amd-helios-ai-rack-built-on-metas-2025-ocp-design.html|publisher=amd.com|access-date=2025-11-29}}</ref> - HBM4: 432 GB, 19.6 TB/s per GPU AMD<ref>{{cite web|title=AMD|url=https://www.amd.com/en/blogs/2025/amd-helios-ai-rack-built-on-metas-2025-ocp-design.html|publisher=amd.com|access-date=2025-11-29}}</ref> - Power (your assumption): 1400 W * NVIDIA Vera Rubin (VR200 / Rubin GPU) - FP4: 50 PFLOP/s per GPU (2 reticle-limited dies, 50 PF FP4) Glenn K. Lockwood<ref>{{cite web|title=Glenn K. Lockwood|url=https://www.glennklockwood.com/garden/processors/R200|publisher=Glenn K. Lockwood|access-date=2025-11-29}}</ref> - FP8: from NVL72 system numbers: 3.6 EF FP4 vs 1.2 EF FP8 → per GPU ≈ 16.7 PF FP8 Jon Peddie Research<ref>{{cite web|title=Jon Peddie Research|url=https://www.jonpeddie.com/news/nvidia-prepares-vera-rubin-for-next-ai-wave/|publisher=Jon Peddie Research|access-date=2025-11-29}}</ref> - HBM4: 288 GB, ~20 TB/s bandwidth Tom's Hardware<ref>{{cite web|title=Tom's Hardware|url=https://www.tomshardware.com/pc-components/gpus/nvidias-vera-rubin-platform-in-depth-inside-nvidias-most-complex-ai-and-hpc-platform-to-date|publisher=Tom's Hardware|access-date=2025-11-29}}</ref> - Power (your assumption, consistent with leaks of 2.3–2.5 kW Rubin Ultra): 2300 W TweakTown<ref>{{cite web|title=TweakTown|url=https://www.tweaktown.com/news/108068/nvidia-could-change-cooling-solution-for-rubin-ultra-ai-gpus-for-huge-2300w-thermal-concerns/index.html|publisher=tweaktown.com|access-date=2025-11-29}}</ref> ===== Per-chip comparison ===== (All FLOPs are dense, no sparsity; TF/W is “teraFLOPs per watt.”) | Accelerator | Power (W) | FP8 (PF) | FP8 (TF/W) | FP4 (PF) | FP4 (TF/W) | HBM (GB) | HBM BW (TB/s) | | --------------- | --------- | -------- | ---------- | -------- | ---------- | -------- | ------------- | | TPU v7 Ironwood | 1000 | 4.6 | 4.6 | 9.2* | 9.2 | 192 | 7.4 | | AMD MI450X | 1400 | 19.4 | 13.9 | 40.3 | 28.8 | 432 | 19.6 | | NVIDIA Rubin | 2300 | 16.7 | 7.25 | 50 | 21.7 | 288 | ~20 | *Ironwood FP4 is an assumption (2× FP8) because Google hasn’t published FP4 peak. Quick takeaways per device: * Perf/W: MI450X is the clear winner in FP8 and FP4 TF/W under your power assumptions. * Raw FP4: Rubin wins on absolute FP4 per chip (50 PF vs ~40 PF MI450X). * Memory capacity: MI450X has 1.5× Rubin’s HBM and 2.25× Ironwood’s (432 GB vs 288 GB vs 192 GB). GamingBench<ref>{{cite web|title=GamingBench|url=https://gamingbench.net/amd-ceo-confirms-instinct-mi450-is-built-on-2nm-process-technology/|publisher=gamingbench.net|access-date=2025-11-29}}</ref> * Memory bandwidth: MI450X is also top on per-chip HBM BW at 19.6 TB/s, slightly above Rubin and far above Ironwood.
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