A5000 vs B300
Explore a head to head comparison of specifications, performance, and pricing.
A5000
The NVIDIA A5000 delivers high-performance computing capabilities for AI, machine learning, and data science applications.
B300
The NVIDIA B300 delivers high-performance computing capabilities for AI, machine learning, and data science applications.
A5000 vs B300: Which Should You Choose?
The B300 offers 288 GB of VRAM — 12× the 24 GB on the A5000 — making it better suited for large model workloads that require holding more parameters in GPU memory. On FP16 throughput, the A5000 delivers 27.77 TFLOPS versus 1 TFLOPS on the B300 — 28× faster for mixed-precision training and inference. Memory bandwidth favors the A5000 at 0.77 TB/s compared to 0.01 TB/s on the B300, which directly impacts inference latency for memory-bandwidth-bound models. Architecturally, the A5000 is built on Ampere while the B300 uses Blackwell Ultra, reflecting different generational capabilities and optimizations. On Shadeform, the A5000 starts from $0.44/hr versus $7.40/hr for the B300 — 1582% more expensive — reflecting the performance premium.
A5000 — Best Use Cases
- •General-purpose deep learning training
- •Fine-tuning models up to 13B parameters
- •AI inference at moderate throughput
- •Computer vision and NLP workloads
Choose A5000 when:
- ✓24 GB VRAM is sufficient for your workload
- ✓Cost efficiency is your primary concern
- ✓You are training large models or running high-throughput inference
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
See how the A5000 & B300 compare
Compare detailed hardware specifications and average pricing for the A5000 and B300.
Compare Hardware Specifications
| A5000 | B300 | |
|---|---|---|
| GPU Type | A5000 | B300 |
| VRAM per GPU | 24 GB | 288 GB |
| Manufacturer | NVIDIA | NVIDIA |
| Architecture | Ampere | Blackwell Ultra |
| Interconnect | PCIe Gen4 | SXM6 |
| Memory Bandwidth | 768 GB/s | 8 TB/s |
| FP16 TFLOPS | 27.77 TFLOPS (1:1) | 1,231.8 TFLOPS (16:1) |
| CUDA Cores | 8192 | 20480 |
| Tensor Cores | 256 (3rd Gen) | 640 (5th Gen) |
| RT Cores | 64 (2nd Gen) | N/A |
| Base Clock | 1170 MHz | 1665 MHz |
| Boost Clock | 1695 MHz | 2032 MHz |
| TDP | 230W | 1000W |
| Process Node | TSMC 8nm | TSMC 4NP |
| Data Formats | INT8, BF16, FP16, TF32, FP32 | FP4, FP6, FP8, INT8, BF16, FP16, TF32, FP32, FP64 |
Compare Average On-Demand Pricing
| A5000 | B300 | |
|---|---|---|
| 1 GPU | $0.93 /hr | $7.40 /hr |
| 2 GPUs | $1.86 /hr | $14.80 /hr |
| 4 GPUs | $3.72 /hr | $29.20 /hr |
| 8 GPUs | $3.52 /hr | $64.81 /hr |
Frequently Asked Questions: A5000 vs B300
The main differences are VRAM (24 GB vs 288 GB), FP16 throughput (27.77 vs 1 TFLOPS), architecture (Ampere vs Blackwell Ultra). The A5000 uses the Ampere architecture while the B300 is based on Blackwell Ultra, giving each GPU different generational capabilities.
The A5000 is generally better for large language model training due to its higher throughput and 24 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 A5000 is available from $0.44/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 24 GB on the A5000. 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 A5000 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 A5000 is currently available across 2 cloud providers on Shadeform's network, compared to 2 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 A5000 or B300. Shadeform supports on-demand clusters of up to 64 GPUs of the same type with no commitment required.
Explore A5000 & B300 Instances
Browse available instances with A5000 and B300 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.
