Specifications Compared
| Spec | A10 | GB300 |
|---|---|---|
| TDP | 150W | 1400W |
| VRAM | 24 GB | 288 GB |
| CUDA Cores | 9,216 | |
| Memory Type | GDDR6 | HBM3e |
| Architecture | Ampere | Blackwell Ultra |
| Form Factors | PCIe | SXM |
| Interconnect | NVSwitch, NVLink | |
| Tensor Cores | 288 | |
| FP16 Performance | 31.2 TFLOPS | 2,250 TFLOPS |
| FP32 Performance | 31.2 TFLOPS | 90 TFLOPS |
| INT8 Performance | 250 TOPS | 4,500 TOPS |
| Memory Bandwidth | 600 GB/s | 12,000 GB/s |
Performance Analysis
Raw specifications reveal vast disparities in capability: the GB300's 2250 TFLOPS FP16 performance exceeds the A10's 31.2 TFLOPS by over 72 times, while FP32 reaches 90 TFLOPS versus 31.2 TFLOPS. This delta favors the GB300 for training, where FP16 mixed precision accelerates convergence on massive datasets, and inference, boosted by 4500 TFLOPS FP8 for quantized models. The A10's balanced 1:1 FP16 to FP32 ratio supports versatile precision needs in smaller-scale operations.
Memory defines practical limits: 288 GB HBM3e on the GB300 versus 24 GB GDDR6 on the A10 allows batch sizes scaling to billions of parameters without swapping, critical for LLMs exceeding 100B tokens. The GB300's 12000 GB/s bandwidth, 20 times the A10's 600 GB/s, minimizes bottlenecks in data-intensive phases like gradient accumulation. Consequently, A10 handles modest inference at low latency, while GB300 enables real-time serving of frontier models.
Power efficiency shifts with scale: A10's 150W TDP yields 0.208 TFLOPS per watt in FP16, adequate for edge deployments. GB300's 1400W consumes more yet delivers 1.607 TFLOPS per watt, optimizing dense clusters via NVLink.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
A10
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 LeaderGPU | 10×NVIDIA A10 24GB VRAM | 24GB | 64 vCPU 384GB RAM 2000GB Storage | Netherlands | $0.60/GPU/hr $6.00/hr total (10×) | Available | ||
 Vast.ai | 2×NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 256 vCPU 126GB RAM 769GB Storage | Slovenia | $0.73/GPU/hr $1.47/hr total (2×) | Available | ||
Vast.ai | 2×NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 256 vCPU 126GB RAM 5672GB 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 |
When to Choose the A10
The A10 excels in budget-conscious environments: its pricing starts at $0.60 per hour with an average of $1.06 per hour across three providers makes it ideal for prototyping, small-scale inference, or development where 24 GB VRAM suffices for models under 7B parameters. The 150W TDP and PCIe form factor integrate easily into standard cloud instances without specialized cooling or power infrastructure.
Choose A10 for immediate availability and low overhead in tasks like fine-tuning compact models or Stable Diffusion generation, where 31.2 TFLOPS FP16 meets demands without overprovisioning.
When to Choose the GB300
The GB300 dominates large-scale AI factories: 288 GB VRAM and 12000 GB/s bandwidth support training LLMs with trillions of parameters, far beyond A10's 24 GB limit. FP8 at 4500 TFLOPS accelerates high-throughput inference for production serving.
Opt for GB300 in clustered setups leveraging SXM form factor, NVSwitch, and NVLink for multi-GPU synchronization, ideal for scientific simulations or enterprise inference at 2250 TFLOPS FP16 despite 1400W TDP demands.
Use Cases
GB300's 288 GB HBM3e VRAM and 2250 TFLOPS FP16 handle massive datasets and models exceeding A10's 24 GB GDDR6 limit. NVLink interconnect scales multi-GPU training efficiently.
FP8 performance of 4500 TFLOPS on GB300 supports quantized serving at high throughput, with 12000 GB/s bandwidth enabling large batch sizes. A10's 31.2 TFLOPS FP16 falls short for production-scale LLMs.
A10's 24 GB VRAM and $0.60 per hour pricing suit fine-tuning mid-sized models under 13B parameters cost-effectively. GB300's 1400W TDP overkills such tasks.
A10 delivers 31.2 TFLOPS FP16 for rapid image generation on 24 GB VRAM at low 150W cost. GB300 accelerates hyperscale but lacks current availability.
GB300's 90 TFLOPS FP32 and NVSwitch enable complex simulations on vast datasets. A10's balanced 31.2 TFLOPS limits precision-heavy workloads.
Frequently Asked Questions
What is the VRAM difference between A10 and GB300?▾
The A10 provides 24 GB GDDR6 VRAM, while the GB300 offers 288 GB HBM3e. This 12-fold increase allows GB300 to load models over 100B parameters without fragmentation.
How do FP16 performances compare?▾
A10 achieves 31.2 TFLOPS FP16, contrasted by GB300's 2250 TFLOPS, a 72 times uplift. This gap transforms training speed for deep learning pipelines.
What are the current prices for these GPUs?▾
A10 starts at $0.60 per hour, averaging $1.06 per hour across three live offers. GB300 has no live offers available yet.
Is GB300 more power-efficient?▾
GB300's 1400W TDP yields 1.607 TFLOPS per watt FP16 versus A10's 0.208 at 150W. Efficiency favors GB300 in high-density compute.
What form factors do they use?▾
A10 uses PCIe for broad compatibility. GB300 employs SXM with NVSwitch and NVLink for clustered scaling.
Can A10 handle large LLMs?▾
A10's 24 GB VRAM limits it to models under 7B parameters with small batches at 600 GB/s bandwidth. GB300's 288 GB supports frontier-scale LLMs.
Which is cheaper to rent, the A10 or the GB300?▾
Cloud rental prices for both the A10 and GB300 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 A10 have compared to the GB300?▾
The A10 has 24 GB of GDDR6 memory. The GB300 has 288 GB of HBM3e memory.
Can I find A10 and GB300 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 A10 and the GB300?▾
The A10 uses the Ampere architecture (2021) while the GB300 uses Blackwell Ultra (2025). The GB300 delivers 72.1x the FP16 throughput and 20.0x the memory bandwidth of the A10.