NVIDIA GeForce RTX 4070 vs NVIDIA RTX PRO 6000 — GPU Comparison (Apr 2026)
NVIDIA GeForce RTX 4070 (12GB GDDR6X, 29.1 TFLOPS FP16, Ada Lovelace) vs NVIDIA RTX PRO 6000 (96GB GDDR7, 252 TFLOPS FP16, Blackwell). Cloud pricing: NVIDIA RTX PRO 6000 from $1.71/hr. Compare specs, VRAM, performance, and pricing across 2 cloud providers to find the best GPU for your AI workload.
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NVIDIA GeForce RTX 4070
12GB GDDR6X · Ada Lovelace
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NVIDIA RTX PRO 6000
96GB GDDR7 · Blackwell
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|---|---|---|---|
| Specifications | |||
| Manufacturer | NVIDIA | NVIDIA | |
| Architecture | Ada Lovelace | Blackwell | |
| VRAM | 12 GB GDDR6X | 96 GB GDDR7 | |
| Memory Bandwidth | 504 GB/s | 1,792 GB/s | |
| FP16 (Tensor) | 29.1 TFLOPS | 252.0 TFLOPS | |
| FP32 | 14.6 TFLOPS | 125.0 TFLOPS | |
| TDP | 200W | 600W | |
| Release Year | 2023 | 2025 | |
| Segment | Consumer | Professional | |
| Best For | Budget inference gaming | Professional AI development large model fine-tuning visualization | |
| Cloud Pricing | |||
| Cheapest On-Demand | — | $1.71/hr | |
| Cheapest Spot | — | $1.69/hr | |
| Providers | 0 | 2 | |
| Provider Pricing (On-Demand) | |||
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N/A | $1.71/hr | |
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N/A | $1.89/hr | |
NVIDIA GeForce RTX 4070
NVIDIA RTX PRO 6000
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Top Providers for NVIDIA GeForce RTX 4070 and NVIDIA RTX PRO 6000
These 2 providers offer both NVIDIA GeForce RTX 4070 and NVIDIA RTX PRO 6000. Full head-to-head comparison of GPU models, pricing, infrastructure, and developer tools.
Latitude.sh vs RunPod - GPU Provider Comparison (April 2026)
Head-to-head comparison of Latitude.sh and RunPod. Compare GPU models, hourly pricing, billing granularity, spot instances, VRAM, infrastructure, developer tools, Kubernetes support, and compliance before choosing a provider. Data refreshed April 2026.
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Latitude.sh
Bare metal GPU cloud across 23 global locations
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RunPod
The cloud built for AI — deploy and scale GPU workloads from serverless inference to instant multi-node clusters on demand.
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|---|---|---|
| Overview | ||
| Trustpilot Rating | 3.7 | 3.7 |
| Headquarters | Brazil | United States |
| Provider Type | Bare Metal | GPU-Focused |
| Best For | AI training inference bare metal GPU fine-tuning research dedicated workloads generative AI | AI training inference fine-tuning Stable Diffusion batch processing rendering research LLM serving generative AI |
| GPU Hardware | ||
| GPU Models | A30 RTX A5000 RTX A6000 L40S RTX 6000 Ada A100 SXM H100 SXM GH200 RTX PRO 6000 | B300 B200 H200 H100 SXM H100 PCIe H100 NVL MI300X A100 SXM A100 PCIe RTX 5090 RTX PRO 6000 L40S L40 RTX 6000 Ada RTX 5000 Ada RTX A6000 RTX A5000 RTX 4090 RTX 4080 SUPER RTX 4080 RTX 4070 Ti RTX 3090 Ti RTX 3090 RTX 3080 Ti RTX 3080 RTX 3070 A40 A30 A2 L4 |
| Max VRAM (GB) | 96 | 288 |
| Max GPUs/Instance | 8 | 8 |
| Interconnect | NVLink | NVLink |
| Pricing | ||
| Starting Price ($/hr) | $0.35/hr | $0.06/hr |
| Billing Granularity | Per-hour | Per-second |
| Spot/Preemptible | No | Yes |
| Reserved Discounts | N/A | 15-29% (1-month to 1-year plans) |
| Free Credits | $200 via referral program | $5-$500 bonus after first $10 spend |
| Egress Fees | None | None (Free) |
| Storage | Local NVMe included (up to 4x 3.8TB), Block Storage $0.10/GB/mo, Filesystem Storage $0.05/GB/mo | Container/Volume ($0.10/GB/mo), Idle Volume ($0.20/GB/mo), Network Storage ($0.07/GB/mo 1TB) |
| Infrastructure | ||
| Regions | 23 locations: US (8 cities), LATAM (5), Europe (5), APAC (4), Mexico City. GPU in Dallas, Frankfurt, Sydney, Tokyo | 31 global regions |
| Uptime SLA | 99.9% | 99.99% |
| Developer Experience | ||
| Frameworks | ML-optimized images PyTorch TensorFlow (user-installed) CUDA | PyTorch TensorFlow JAX ONNX CUDA |
| Docker Support | Yes | Yes |
| SSH Access | Yes | Yes |
| Jupyter Notebooks | No | Yes |
| API / CLI | Yes | Yes |
| Setup Time | Seconds | Instant |
| Kubernetes Support | No | No |
| Business Terms | ||
| Min Commitment | None | None |
| Compliance | Single-tenant isolation DPA available | SOC 2 Type II |
Latitude.sh
RunPod
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