AMD Instinct MI300X vs NVIDIA L40 — GPU Comparison (Jul 2026)
AMD Instinct MI300X (192GB HBM3, 1,307 TFLOPS FP16, CDNA 3) vs NVIDIA L40 (48GB GDDR6, 181 TFLOPS FP16, Ada Lovelace). Cloud pricing: AMD Instinct MI300X from $1.85/hr. Compare specs, VRAM, performance, and pricing across 3 cloud providers to find the best GPU for your AI workload.
Bottom Line: AMD Instinct MI300X vs NVIDIA L40
AMD Instinct MI300X comes out ahead overall, leading in 4 of 5 compared categories.
Where AMD Instinct MI300X leads
- FP16 (1,307 TFLOPS vs 181 TFLOPS)
- VRAM (192 GB vs 48 GB)
- Memory Bandwidth (5,300 GB/s vs 864 GB/s)
- FP32 (163.4 TFLOPS vs 90.5 TFLOPS)
Where NVIDIA L40 leads
- TDP (300W vs 750W)
Choose AMD Instinct MI300X for Large-scale AI training, LLM inference, HPC. Choose NVIDIA L40 for Inference, video processing, rendering.
Frequently Asked Questions
Is AMD Instinct MI300X or NVIDIA L40 better?
Which has a better FP16, AMD Instinct MI300X or NVIDIA L40?
Which has a better VRAM, AMD Instinct MI300X or NVIDIA L40?
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AMD Instinct MI300X
192GB HBM3 · CDNA 3
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NVIDIA L40
48GB GDDR6 · Ada Lovelace
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| Specifications | |||
| Manufacturer | AMD | NVIDIA | |
| Architecture | CDNA 3 | Ada Lovelace | |
| VRAM | 192 GB HBM3 | 48 GB GDDR6 | |
| Memory Bandwidth | 5,300 GB/s | 864 GB/s | |
| FP16 (Tensor) | 1307.0 TFLOPS | 181.0 TFLOPS | |
| FP32 | 163.4 TFLOPS | 90.5 TFLOPS | |
| TDP | 750W | 300W | |
| Release Year | 2023 | 2023 | |
| Segment | Data center | Data center | |
| Best For | Large-scale AI training LLM inference HPC | Inference video processing rendering | |
| Cloud Pricing | |||
| Cheapest On-Demand | $1.85/hr | — | |
| Cheapest Spot | — | — | |
| Providers | 3 | 0 | |
| Provider Pricing (On-Demand) | |||
|
$1.85/hr | N/A | |
|
$1.99/hr | N/A | |
|
$2.19/hr | N/A | |
AMD Instinct MI300X
NVIDIA L40
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These 3 providers offer both AMD Instinct MI300X and NVIDIA L40. Full head-to-head comparison of GPU models, pricing, infrastructure, and developer tools.
Vultr vs DigitalOcean vs Runpod - GPU Provider Comparison (July 2026)
Side-by-side comparison of Vultr vs DigitalOcean vs Runpod. Quickly compare GPU models, hourly pricing, spot instances, billing granularity, VRAM, regions, developer tools, Kubernetes support, and compliance to narrow down your cloud GPU provider shortlist. Data updated July 2026.
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Vultr
High-performance cloud GPU across 32 global regions
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DigitalOcean
Simple, scalable GPU cloud for AI/ML
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Runpod
The cloud built for AI — deploy and scale GPU workloads from serverless inference to instant multi-node clusters on demand.
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|---|---|---|---|
| Overview | |||
| Trustpilot Rating | 1.7 | 4.6 | 3.7 |
| Headquarters | United States | United States | United States |
| Provider Type | Multi-Cloud | N/A | GPU-Focused |
| Best For | AI training inference video rendering HPC Stable Diffusion game development generative AI fine-tuning research | AI training inference fine-tuning LLM deployment LLM serving computer vision startups generative AI research | AI training inference fine-tuning Stable Diffusion batch processing rendering research LLM serving generative AI |
| GPU Hardware | |||
| GPU Models | A16 A40 L40S A100 PCIe GH200 A100 SXM H100 SXM B200 B300 MI300X MI325X MI355X | RTX 4000 Ada RTX 6000 Ada L40S MI300X H100 SXM H200 | B300 B200 H200 H100 SXM H100 PCIe H100 NVL MI300X A100 SXM A100 PCIe RTX 5090 RTX PRO 6000 L40S L40 RTX 6000 Ada RTX 5000 Ada RTX A6000 RTX A5000 RTX 4090 RTX 4080 SUPER RTX 4080 RTX 4070 Ti RTX 3090 Ti RTX 3090 RTX 3080 Ti RTX 3080 RTX 3070 A40 A30 A2 L4 |
| Max VRAM (GB) | 288 | 192 | 288 |
| Max GPUs/Instance | 16 | 8 | 8 |
| Interconnect | NVLink | NVLink | NVLink |
| Pricing | |||
| Starting Price ($/hr) | $0.47/hr | $0.76/hr | $0.06/hr |
| Billing Granularity | Per-hour | Per-second | Per-second |
| Spot/Preemptible | Yes | No | No |
| Reserved Discounts | N/A | N/A | 15-29% (1-month to 1-year plans) |
| Free Credits | Up to $300 free credit for 30 days | $200 free credit for 60 days | $5-$500 bonus after first $10 spend |
| Egress Fees | Standard (varies by plan) | None (included in plan) | None (Free) |
| Storage | 350 GB - 61 TB NVMe (included), Block Storage at $0.10/GB/mo, S3-compatible Object Storage | 500-720 GiB NVMe boot (included), 5 TiB NVMe scratch on larger configs, Volumes at $0.10/GiB/mo | Container/Volume ($0.10/GB/mo), Idle Volume ($0.20/GB/mo), Network Storage ($0.07/GB/mo 1TB) |
| Infrastructure | |||
| Regions | 32 regions across 6 continents (Americas, Europe, Asia, Australia, Africa) | New York (NYC2), Toronto (TOR1), Atlanta (ATL1), Richmond (RIC1), Amsterdam (AMS3) | 31 global regions |
| Uptime SLA | 100% | 99% | 99.99% |
| Developer Experience | |||
| Frameworks | PyTorch TensorFlow CUDA cuDNN ROCm Hugging Face NVIDIA NGC | PyTorch TensorFlow Jupyter Miniconda CUDA ROCm Hugging Face | PyTorch TensorFlow JAX ONNX CUDA |
| Docker Support | Yes | Yes | Yes |
| SSH Access | Yes | Yes | Yes |
| Jupyter Notebooks | Yes | Yes | Yes |
| API / CLI | Yes | Yes | Yes |
| Setup Time | Minutes | Minutes | Instant |
| Kubernetes Support | Yes | Yes | No |
| Business Terms | |||
| Min Commitment | None | None | None |
| Compliance | SOC 2+ (HIPAA) PCI ISO 27001 ISO 27017 ISO 27018 ISO 20000-1 CSA STAR Level 1 | SOC 2 Type II SOC 3 HIPAA (with BAA) CSA STAR Level 1 | SOC 2 Type II |
Vultr
DigitalOcean
Runpod
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