Specifications Compared
| Spec | A100 | B300 |
|---|---|---|
| TDP | 400W | 1200W |
| VRAM | 40-80 GB | 288 GB |
| CUDA Cores | 6,912 | |
| Memory Type | HBM2e | HBM3e |
| Architecture | Ampere | Blackwell Ultra |
| Form Factors | SXM4, PCIe | SXM |
| Interconnect | NVLink, PCIe 4.0, InfiniBand | NVSwitch, NVLink |
| Tensor Cores | 432 | |
| FP16 Performance | 312 TFLOPS | 2,250 TFLOPS |
| FP32 Performance | 19.5 TFLOPS | 90 TFLOPS |
| FP64 Performance | 9.7 TFLOPS | 45 TFLOPS |
| INT8 Performance | 624 TOPS | 4,500 TOPS |
| Memory Bandwidth | 2,039 GB/s | 12,000 GB/s |
Performance Analysis
The B300 outperforms the A100 dramatically in compute metrics: FP16 reaches 2250 TFLOPS versus 312 TFLOPS, a 7.2-fold increase ideal for mixed-precision training of large language models. FP32 performance hits 90 TFLOPS on the B300 compared to 19.5 TFLOPS on the A100, accelerating single-precision scientific simulations by 4.6 times. The FP8 capability of 4500 TFLOPS on the B300 further optimizes inference for quantized models, reducing latency in deployment scenarios.
Memory differences reshape real-world usage: the B300's 288 GB HBM3e supports batch sizes up to seven times larger than the A100's 40 GB, minimizing overhead in training massive datasets. Bandwidth of 12000 GB/s on the B300, versus 2039 GB/s, sustains high throughput for memory-bound tasks like image generation. However, the B300's 1200W TDP demands robust cooling, compared to the A100's 400W.
These specs translate to faster convergence in training and higher tokens per second in inference for the B300, though the A100 suffices for mid-scale workloads.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
A100 PCIe 40GB
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Vast.ai | 2×NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 256 vCPU 126GB RAM 794GB Storage | Slovenia | $0.73/GPU/hr $1.47/hr total (2×) | Available | ||
 LeaderGPU | 8×NVIDIA A100 PCIe 80GB 80GB VRAM | 80GB | 64 vCPU 384GB RAM 2000GB Storage | Netherlands | $0.90/GPU/hr $7.20/hr total (8×) | Available | ||
Vast.ai | 2×NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 64 vCPU 126GB RAM 1114GB Storage | Czechia | $1.00/GPU/hr $2.00/hr total (2×) | Available | ||
 Denvr | 4×NVIDIA A100 PCIe 80GB 80GB VRAM | 80GB | 64 vCPU 512GB RAM 7600GB Storage | Virginia | $1.15/GPU/hr $4.60/hr total (4×) | |||
Denvr | 8×NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 128 vCPU 1024GB RAM 15200GB Storage | Virginia | $1.15/GPU/hr $9.20/hr total (8×) |
B300 SXM6
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 RunPod | NVIDIA B300 SXM6 262GB VRAM | 262GB | 0 vCPU 0GB RAM | 🌍global | $7.39/GPU/hr | |||
 Scaleway | 8×NVIDIA B300 SXM6 262GB VRAM | 262GB | 224 vCPU 3840GB RAM 22352GB Storage | Paris | $8.73/GPU/hr $69.84/hr total (8×) | Available |
When to Choose the A100 PCIe 40GB
The A100 PCIe 40GB suits budget-conscious projects handling models under 40 GB VRAM. At $0.60 per hour starting price, it undercuts the B300's $2.45, offering strong value for fine-tuning or inference on established frameworks. Its 400W TDP integrates easily into standard cloud instances without excessive power costs.
When to Choose the B300 SXM6
Opt for the B300 SXM6 when scaling to frontier models exceeding 40 GB VRAM, leveraging 288 GB HBM3e for single-GPU training. Its 2250 TFLOPS FP16 and 12000 GB/s bandwidth excel in high-throughput inference and large-batch training. Despite $2.45 per hour starting cost, performance gains justify investment for production AI pipelines.
Use Cases
The B300's 288 GB VRAM and 2250 TFLOPS FP16 handle massive models and datasets far beyond the A100's 40 GB and 312 TFLOPS. This reduces multi-GPU complexity and accelerates convergence.
With 4500 TFLOPS FP8 and 12000 GB/s bandwidth, the B300 delivers higher throughput for quantized inference versus the A100's capabilities. Larger VRAM supports bigger batches without swapping.
Fine-tuning mid-sized models fits the A100's 40 GB VRAM at lower $0.60 per hour cost, but the B300's superior FP16 speeds up iterations for larger adapters.
The A100's 312 TFLOPS FP16 and 2039 GB/s bandwidth suffice for image generation at 40 GB VRAM scale, with cheaper pricing than the B300.
B300's 90 TFLOPS FP32 and 288 GB VRAM excel in simulations requiring high precision and memory, outperforming A100's 19.5 TFLOPS and 40 GB.
Frequently Asked Questions
Which GPU has more VRAM?▾
The B300 provides 288 GB HBM3e, compared to the A100 PCIe 40GB's 40 GB HBM2e. This enables the B300 to load models over seven times larger without distribution. Batch sizes scale accordingly in memory-intensive tasks.
How do prices compare?▾
A100 PCIe 40GB starts at $0.60 per hour, averaging $1.85 across 11 offers. B300 SXM6 begins at $2.45 per hour, averaging $6.44 across 7 offers. The A100 offers better value for cost-sensitive workloads.
What is the FP16 performance difference?▾
B300 achieves 2250 TFLOPS FP16, versus A100's 312 TFLOPS, a 7.2 times uplift. This accelerates mixed-precision training significantly. Inference benefits from the B300's FP8 at 4500 TFLOPS.
Which has higher memory bandwidth?▾
B300 delivers 12000 GB/s, over five times the A100's 2039 GB/s. Higher bandwidth supports larger batches and reduces bottlenecks in data-heavy AI tasks. This impacts training throughput directly.
What are the power requirements?▾
A100 PCIe 40GB has a 400W TDP, suitable for standard setups. B300 SXM6 requires 1200W, necessitating advanced cooling and power infrastructure. Higher TDP correlates with the B300's performance gains.
Is B300 worth the higher price?▾
For workloads needing over 40 GB VRAM or 2250 TFLOPS FP16, the B300 justifies $2.45 per hour starting cost over A100's $0.60. Smaller tasks favor A100's efficiency. Performance scales with model size.
Which is cheaper to rent, the A100 or the B300?▾
Cloud rental prices for both the A100 and B300 vary by provider, configuration, and availability. This page shows live pricing from 25+ providers updated every 60 seconds. Scroll to the Live Cloud Pricing section to compare current rates.
How much VRAM does the A100 have compared to the B300?▾
The A100 has 40 to 80 GB of HBM2e memory. The B300 has 288 GB of HBM3e memory.
Can I find A100 and B300 GPUs available to rent right now?▾
Yes. This page shows real-time availability across 25+ cloud GPU providers. The Live Cloud Pricing section displays only in-stock offers with current pricing.
What is the main difference between the A100 and the B300?▾
The A100 uses the Ampere architecture (2020) while the B300 uses Blackwell Ultra (2025). The B300 delivers 7.2x the FP16 throughput and 5.9x the memory bandwidth of the A100.