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Blackwell Ultra B300 vs Ironwood TPU v7

Complete side-by-side comparison of specs, performance, memory, power efficiency, and pricing.

NVIDIA

Blackwell Ultra B300

100

Spec Wins

GOOGLE

Ironwood TPU v7

95

Detailed Specifications

SpecBlackwell Ultra B300Ironwood TPU v7
ArchitectureBlackwell Ultra Ironwood (TPU v7)
Memory288GB HBM3e 192GB HBM3e
Memory Bandwidth12,000 GB/s 7,400 GB/s
FP16 TFLOPS3,500 2,307
FP8 TFLOPS7,000 4,614
BF16 TFLOPS3,500 2,307
INT8 TOPS14,000 4,614
TDP1400W 1000W
InterconnectNVLink 5.0 (1800 GB/s) (1800 GB/s) ICI (1,200 GB/s) (1200 GB/s)
Perf Score100 95
EcosystemCUDA JAX
Est. Price$40,000 Cloud Only

Blackwell Ultra B300 — Best For

Trillion-Parameter TrainingAGI ResearchSovereign AI

Ironwood TPU v7 — Best For

Frontier TrainingLarge-Scale InferenceJAX

Who Should Choose Each GPU?

Choose Blackwell Ultra B300 if you…

  • Need maximum CUDA/TensorRT/vLLM ecosystem compatibility
  • Need more VRAM (288GB vs 192GB) for large model inference
  • Prioritize raw FP8 throughput (7,000 vs 4,614 TFLOPS)
  • Running Trillion-Parameter Training workloads
  • Running AGI Research workloads
  • Running Sovereign AI workloads

Choose Ironwood TPU v7 if you…

  • Have power-constrained data centers (1000W vs 1400W TDP)
  • Running Frontier Training workloads
  • Running Large-Scale Inference workloads
  • Running JAX workloads

Verdict

The Blackwell Ultra B300 and Ironwood TPU v7 target different priorities. The Blackwell Ultra B300's 288GB of HBM3e gives it a clear edge for large-model inference where fitting the full model in VRAM eliminates quantization overhead. For training throughput, the Blackwell Ultra B300's 7,000 FP8 TFLOPS outpaces the Ironwood TPU v7's 4,614 TFLOPS. Teams already invested in the NVIDIA/CUDA ecosystem will have less friction with the Blackwell Ultra B300, while teams open to JAX can benefit from the Ironwood TPU v7's advantages. Use our TCO Calculator to model the full 3-year cost difference for your specific utilization and power costs.

Blackwell Ultra B300 vs Ironwood TPU v7: Common Questions

Which is faster, Blackwell Ultra B300 or Ironwood TPU v7?+

In FP8 throughput, the Blackwell Ultra B300 leads with 7,000 TFLOPS vs 4,614 TFLOPS. For LLM inference, memory capacity and bandwidth often matter more than raw TFLOPS — the Blackwell Ultra B300 has more VRAM (288GB).

Is Blackwell Ultra B300 or Ironwood TPU v7 better for LLM training?+

For LLM training at scale, the Blackwell Ultra B300 has higher raw throughput. However, the choice also depends on your software stack: Blackwell Ultra B300 offers CUDA compatibility with the widest framework support (PyTorch, JAX, TensorRT).

What is the price difference between Blackwell Ultra B300 and Ironwood TPU v7?+

Pricing for these GPUs varies by vendor and availability. Check our Buy page for current reseller pricing and cloud rental costs.

Which GPU is more power efficient, Blackwell Ultra B300 or Ironwood TPU v7?+

The Ironwood TPU v7 has a lower TDP (1000W vs 1400W). Performance-per-watt depends on your workload — for FP8 inference, divide TFLOPS by TDP: Blackwell Ultra B300 = 5.0 TFLOPS/W vs Ironwood TPU v7 = 4.6 TFLOPS/W.

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