B300 SXM vs RTX PRO 6000 Blackwell
NVIDIA B300 SXM (Blackwell Ultra, 288 GB) against NVIDIA RTX PRO 6000 Blackwell (Blackwell, 96 GB): memory, compute, power and rental price, compared for LLM inference and training.
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Side-by-Side Specifications
| Spec | B300 SXM | RTX PRO 6000 Blackwell |
|---|---|---|
| Architecture | Blackwell Ultra | Blackwell |
| Memory | 288 GB HBM3e | 96 GB GDDR7 |
| Memory bandwidth | 8,000 GB/s | 1,792 GB/s |
| FP16 tensor compute | 5,000 TFLOPS | 1,000 TFLOPS |
| INT8 tensor compute | 10,000 TOPS | 2,000 TOPS |
| Interconnect | NVLink 5.0 · 1800 GB/s | PCIe 5.0 · 128 GB/s |
| TDP | 1400 W | 600 W |
| Est. on-demand price | ~$18.00/h | ~$5.00/h |
| FP16 TFLOPS per $/h | 278 | 200 |
Highlighted values indicate the stronger spec. Hourly rates are indicative on-demand estimates.
Verdict
Raw performance: The B300 SXM leads on FP16 tensor compute (5.0x advantage), which translates directly into higher token throughput for inference and shorter training steps.
Memory: With 288 GB per card, the B300 SXM fits larger models on fewer GPUs — fewer cards means less inter-GPU communication and simpler deployments.
Value: At current on-demand rates, the B300 SXM delivers more compute per dollar (278 vs 200 FP16 TFLOPS per $/h). If your model fits in its VRAM budget, it is usually the more economical choice.
GPUs Needed for Popular LLMs
Cards required to serve each model at 8-bit quantization (with 20% overhead for activations and KV cache).
| Model | VRAM (8-bit) | B300 SXM | RTX PRO 6000 Blackwell |
|---|---|---|---|
| GPT-5.6 Sol | 2682 GB | 10x | 28x |
| DeepSeek V4 Pro (671B) | 750 GB | 3x | 8x |
| Muse Spark 1.1 | 335 GB | 2x | 4x |
| Claude 5 Sonnet (175B) | 196 GB | 1x | 3x |
| Nova Premier (80B) | 89 GB | 1x | 1x |
| Nova Core (34B) | 38 GB | 1x | 1x |
| Nova Lite (12B) | 13 GB | 1x | 1x |
| Phi 3.5 (3.8B) | 4 GB | 1x | 1x |
Frequently Asked Questions
Which is better for LLM inference: B300 SXM or RTX PRO 6000 Blackwell?
The B300 SXM delivers more raw FP16 compute (5,000 TFLOPS) and the B300 SXM offers the most memory per card (288 GB). For cost-efficiency, the B300 SXM currently gives more FP16 TFLOPS per dollar of on-demand rental (278 vs 200 TFLOPS per $/h).
How much more memory does the B300 SXM have?
The B300 SXM has 288 GB of HBM3e versus 96 GB of GDDR7 for the RTX PRO 6000 Blackwell — a ratio of 3.00x in favor of the B300 SXM. More VRAM per card means fewer GPUs to fit a given model.
Is the B300 SXM or the RTX PRO 6000 Blackwell cheaper to rent?
Estimated on-demand rates are ~$18.00/h for the B300 SXM and ~$5.00/h for the RTX PRO 6000 Blackwell. Raw hourly price is only part of the story: normalize by throughput (TFLOPS per $/h) and by how many cards you need for your model's VRAM.
How do the B300 SXM and RTX PRO 6000 Blackwell compare on power?
The B300 SXM has a TDP of 1400W versus 600W for the RTX PRO 6000 Blackwell. FP16 compute per watt: 3.6 vs 1.7 TFLOPS/W.
Deploy on a GPU cloud
Rent the B300 SXM or RTX PRO 6000 Blackwell by the hour instead of buying hardware.
