B300 vs RTX Pro 6000
Explore a head to head comparison of specifications, performance, and pricing.
B300
The NVIDIA B300 delivers high-performance computing capabilities for AI, machine learning, and data science applications.
RTX Pro 6000
The NVIDIA RTX Pro 6000 delivers high-performance computing capabilities for AI, machine learning, and data science applications.
B300 vs RTX Pro 6000: Which Should You Choose?
The B300 offers 288 GB of VRAM — 3× the 96 GB on the RTX Pro 6000 — making it better suited for large model workloads that require holding more parameters in GPU memory. On FP16 throughput, the RTX Pro 6000 delivers 126 TFLOPS versus 1 TFLOPS on the B300 — 126× faster for mixed-precision training and inference. Memory bandwidth favors the B300 at 0.01 TB/s compared to 0.00 TB/s on the RTX Pro 6000, which directly impacts inference latency for memory-bandwidth-bound models. Architecturally, the B300 is built on Blackwell Ultra while the RTX Pro 6000 uses Blackwell, reflecting different generational capabilities and optimizations. On Shadeform, the RTX Pro 6000 starts from $1.25/hr versus $7.40/hr for the B300 — 492% more expensive — reflecting the performance premium. The RTX Pro 6000 is available across 7 cloud providers on Shadeform compared to 1 for the B300, giving more options for region and pricing flexibility.
B300 — Best Use Cases
- •Next-generation LLM pre-training at scale
- •Trillion-parameter model inference
- •Ultra-high-throughput AI workloads
- •Advanced HPC and scientific computing
Choose B300 when:
- ✓You need 288 GB+ VRAM for large models or long context windows
- ✓Maximum performance justifies the higher cost
- ✓Your workload does not require peak FP16 throughput
- ✓Your preferred provider already has availability
RTX Pro 6000 — Best Use Cases
- •Next-generation LLM pre-training at scale
- •Trillion-parameter model inference
- •Ultra-high-throughput AI workloads
- •Advanced HPC and scientific computing
Choose RTX Pro 6000 when:
- ✓96 GB VRAM is sufficient for your workload
- ✓Cost efficiency is your primary concern
- ✓You are training large models or running high-throughput inference
- ✓You need flexibility across multiple cloud providers or regions
See how the B300 & RTX Pro 6000 compare
Compare detailed hardware specifications and average pricing for the B300 and RTX Pro 6000.
Compare Hardware Specifications
| B300 | RTX Pro 6000 | |
|---|---|---|
| GPU Type | B300 | RTX Pro 6000 |
| VRAM per GPU | 288 GB | 96 GB |
| Manufacturer | NVIDIA | NVIDIA |
| Architecture | Blackwell Ultra | Blackwell |
| Interconnect | SXM6 | PCIe Gen5 |
| Memory Bandwidth | 8 TB/s | 1.59 TB/s |
| FP16 TFLOPS | 1,231.8 TFLOPS (16:1) | 126.0 TFLOPS (1:1) |
| CUDA Cores | 20480 | 24064 |
| Tensor Cores | 640 (5th Gen) | 752 (5th Gen) |
| RT Cores | N/A | 188 (4th Gen) |
| Base Clock | 1665 MHz | 1860 MHz |
| Boost Clock | 2032 MHz | 2600 MHz |
| TDP | 1000W | 400W |
| Process Node | TSMC 4NP | TSMC 4N |
| Data Formats | FP4, FP6, FP8, INT8, BF16, FP16, TF32, FP32, FP64 | FP4, FP6, FP8, INT8, BF16, FP16, TF32, FP32 |
Compare Average On-Demand Pricing
| B300 | RTX Pro 6000 | |
|---|---|---|
| 1 GPU | $7.40 /hr | $1.70 /hr |
| 2 GPUs | $14.80 /hr | $3.30 /hr |
| 4 GPUs | $29.20 /hr | $6.60 /hr |
| 8 GPUs | $57.56 /hr | $14.11 /hr |
Frequently Asked Questions: B300 vs RTX Pro 6000
The main differences are VRAM (288 GB vs 96 GB), FP16 throughput (1 vs 126 TFLOPS), architecture (Blackwell Ultra vs Blackwell). The B300 uses the Blackwell Ultra architecture while the RTX Pro 6000 is based on Blackwell, giving each GPU different generational capabilities.
The RTX Pro 6000 is generally better for large language model training due to its higher throughput and 96 GB of VRAM, which allows fitting larger models or larger batch sizes in a single pass. For smaller models or fine-tuning tasks where cost matters more, both GPUs can be effective.
On Shadeform, the RTX Pro 6000 is available from $1.25/hr. The B300 starts from $7.40/hr. Prices vary by provider, region, and contract length. Reserved commitments can reduce hourly costs significantly compared to on-demand pricing.
The B300 has more VRAM at 288 GB, compared to 96 GB on the RTX Pro 6000. Higher VRAM allows you to run larger models without quantization, use longer context windows, and process larger batch sizes — all of which improve throughput and reduce latency for memory-bound workloads.
Based on TFLOPS per dollar, the RTX Pro 6000 offers better raw compute value at current Shadeform on-demand rates. However, the best choice depends on your specific workload — if you need the extra VRAM or throughput of the B300, paying the premium may be justified by faster job completion and lower total cost.
The RTX Pro 6000 is currently available across 7 cloud providers on Shadeform's network, compared to 1 for the B300. Shadeform lets you deploy either GPU across all available providers from a single platform, so you can always find available capacity without manually checking each cloud.
Mixing different GPU types in a single training cluster is generally not recommended, as it creates performance bottlenecks where faster GPUs wait for slower ones. For best results, use a homogeneous cluster of either B300 or RTX Pro 6000. Shadeform supports on-demand clusters of up to 64 GPUs of the same type with no commitment required.
Explore B300 & RTX Pro 6000 Instances
Browse available instances with B300 and RTX Pro 6000 GPUs. Filter by provider, availability, and more to find the perfect instance for your needs.
Explore more GPU comparisons
Select any two GPUs to compare their specifications and explore pricing across providers.
