NVIDIA B300 Blackwell Ultra Cloud Pricing & Rental Rates
The B300 Blackwell Ultra pushes VRAM to 288 GB with 9 TB/s bandwidth. Built for frontier multi-trillion parameter training clusters requiring maximum memory per socket.
Target Workload: Frontier multi-trillion parameter cluster reservation tiers
Market Availability & Early Reservation Watch
No verified on-demand rental instances are currently available in public spot markets. Cloud providers are accepting private cluster reservation inquiries for Q4 2026 delivery.
Telemetry Status: Theoretical & Lab Sizing Estimates
Hardware not yet widely deployed in multi-tenant public clouds. Specifications sourced from NVIDIA architectural whitepapers and lab benchmarks.
Models That Fit NVIDIA B300 Blackwell Ultra (288GB HBM3e)
Deterministic VRAM calculation (FP8) via entity graph. Only editorial and enriched models shown.
| MODEL | PARAMS | CONTEXT | FP8 VRAM | FIT? | CALCULATOR |
|---|---|---|---|---|---|
| DeepSeek R1 Distill 70B | 70B | 128K | 93.9 GB | ✓ fits | Pre-filled → |
| DeepSeek R1 Distill Qwen 32B | 32B | 128K | 42.9 GB | ✓ fits | Pre-filled → |
| Llama 3.3 70B Instruct | 70.6B | 128K | 94.7 GB | ✓ fits | Pre-filled → |
| Llama 3.1 8B Instruct | 8.03B | 128K | 10.8 GB | ✓ fits | Pre-filled → |
| Llama 3.2 3B Instruct | 3.2B | 128K | 4.3 GB | ✓ fits | Pre-filled → |
| Llama 3.2 1B Instruct | 1B | 128K | 1.3 GB | ✓ fits | Pre-filled → |
| Qwen 2.5 Coder 32B | 32.5B | 128K | 43.6 GB | ✓ fits | Pre-filled → |
| Qwen 2.5 Coder 14B | 14.7B | 128K | 19.7 GB | ✓ fits | Pre-filled → |
| Qwen 2.5 Coder 7B | 7.61B | 128K | 10.2 GB | ✓ fits | Pre-filled → |
| Qwen 2.5 72B Instruct | 72.7B | 128K | 97.5 GB | ✓ fits | Pre-filled → |
| Qwen 2.5 14B Instruct | 14.7B | 128K | 19.7 GB | ✓ fits | Pre-filled → |
| Qwen 2.5 7B Instruct | 7.61B | 128K | 10.2 GB | ✓ fits | Pre-filled → |
Inference & Serving Capacity
Architectural Simulation / Manufacturer Target Spec — numbers below are theoretical estimates.
Llama 3.3 70B
FEASIBLEBF16 on single GPU, no quantization needed
DeepSeek 671B
FEASIBLESingle-GPU inference possible with FP8
Qwen 2.5 32B
FEASIBLEFull BF16 precision, maximum quality
vLLM Throughput (FP8)
~200 tok/s (vLLM, Llama 70B FP8, batch=1)
Estimated tokens/second, single GPU, Llama-class model
Max Context Window (Llama 70B)
128k+ tokens (FP16) — entire 70B model + full context on one GPU
Maximum context length before KV-cache eviction
Hardware Bottleneck Analysis
Whether NVIDIA B300 Blackwell Ultra is compute-bound (TFLOPS) or memory-bandwidth bound (GB/s) across workloads.
Bottleneck Classification
Compute-bound — 9 TB/s bandwidth exceeds 2,500 TFLOPS FP8 demand
Recommended Quantization
FP4 / FP8 / BF16 — all precisions native, no quality tradeoff
Best Cluster Topology
8-way NVLink 5.0 Full Mesh, multi-node via NVLink-C2C
Deep Analysis
The B300 is compute-bound at FP8 and FP4 — 9 TB/s HBM3e bandwidth far exceeds what 2,500 FP8 TFLOPS can consume. This is by design: frontier model training requires maximum memory per socket (288 GB) to fit large parameter shards, and the excess bandwidth ensures KV-cache expansion at 1M+ context windows never stalls. At FP4 (5,000 TFLOPS), the B300 delivers 2x the inference throughput of the B200 with identical memory footprint.
Architecture & Die Breakdown
Architecture
Blackwell Ultra GB300 — 4NP TSMC
TDP
1200W
Memory Subsystem
288GB HBM3e at 9.0 TB/s bandwidth. High Bandwidth Memory provides the throughput needed to keep tensor cores fed during large batch inference.
Interconnect
NVLink 5.0 (1.8 TB/s). Enables multi-GPU tensor parallelism with high-bandwidth, low-latency GPU-to-GPU communication.
Precision Performance
| Precision | TFLOPS | Use Case |
|---|---|---|
| FP4 | 5,000 | Extreme-throughput inference, quantized serving |
| FP8 | 2,500 | Training & inference with mixed-precision |
| FP16 | 1,250 | Full-precision training, fine-tuning, evaluation |
Break-Even ROI Calculator
Monthly hours where reserved pricing beats spot for NVIDIA B300 Blackwell Ultra. Above the break-even point, reserve commits save money.
Spheron
RunPod
Lambda Labs
Break-even at 260 hours/month: if you run NVIDIA B300 Blackwell Ultra more than 260 hours per month, reserved pricing on all three providers saves money. At 720 hours/month (24/7), reserved saves $377+/mo vs on-demand.
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Frequently Asked Questions
How much does it cost to rent an NVIDIA B300 Blackwell Ultra per hour?▾
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Can an NVIDIA B300 Blackwell Ultra run 70B parameter LLMs?▾
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