GTX 1080 on Vast.ai
Visit Vast.aiVast.ai's NVIDIA GeForce GTX 1080 offering leverages a decentralized marketplace to deliver Pascal architecture GPUs with 8GB GDDR5X VRAM at absolute lowest costs, ideal for cost-sensitive ML engineers. This consumer-tier card provides ~9 TFLOPS FP32 performance, excelling in inference, fine-tuning small models (e.g., BERT-base), prototyping, and distributed experiments. Noteworthy for granular filters like DLPerf per dollar, enabling value-optimized rentals from $0.05-$0.15/hr via on-demand or spot instances. Target audience: researchers, hobbyists, and teams prioritizing budget over peak throughput, where abundant global consumer hardware undercuts enterprise providers. Key propositions include instant scaling across thousands of hosts, per-minute billing, and Docker-based ML templates (PyTorch, TensorFlow). While host variability exists, verified instances offer reliable CUDA 11.x support. Limitations: not suited for VRAM-heavy training (>6GB models) or latency-critical production.
Why NVIDIA GeForce GTX 1080 on Vast.ai?
Vast.ai pairs perfectly with GTX 1080 for ultra-low-cost access to capable Pascal GPUs from underutilized consumer rigs worldwide. Decentralized model crushes prices—often 70-90% below traditional clouds—via competitive bidding and spot auctions. Unique advantages: DLPerf/$ sorting maximizes ML perf per spend; abundant 1080 inventory suits bursty, experimental workloads. GTX 1080's 8GB VRAM and PCIe interconnect complement Vast.ai's flexible hosting, enabling quick spins for inference or swarm training without commitments. Per-hour billing with no egress fees enhances affordability. Choose this for high-volume prototyping where reliability trade-offs are acceptable; vet hosts via scores for best results.
Live Pricing
Real-time NVIDIA GeForce GTX 1080 offers from Vast.ai
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Vast.ai | NVIDIA GeForce GTX 1080 Ti 11GB VRAM | 11GB | 8 vCPU 31GB RAM 122GB Storage | United Kingdom | $0.02/GPU/hr | Sold Out | ||
Vast.ai | 2×NVIDIA GeForce GTX 1080 Ti 11GB VRAM | 11GB | 32 vCPU 31GB RAM 738GB Storage | Germany | $0.02/GPU/hr $0.04/hr total (2×) | Sold Out | ||
Vast.ai | NVIDIA GeForce GTX 1080 Ti 11GB VRAM | 11GB | 12 vCPU 16GB RAM 392GB Storage | South Korea | $0.03/GPU/hr | Sold Out | ||
Vast.ai | NVIDIA GeForce GTX 1080 Ti 11GB VRAM | 11GB | 20 vCPU 15GB RAM 393GB Storage | South Korea | $0.03/GPU/hr | Sold Out | ||
Vast.ai | 2×NVIDIA GeForce GTX 1080 8GB VRAM | 8GB | 4 vCPU 15GB RAM 312GB Storage | Shanghai | $0.03/GPU/hr $0.05/hr total (2×) | Sold Out |
Performance Notes
GTX 1080 on Vast.ai yields solid consumer-grade perf: ~9 TFLOPS FP32, ResNet-50 inference at 100-150 img/s, viable for small-batch training (<4GB models). DLPerf ~0.5-1.0 across benchmarks. Network: 100Mbps-10Gbps host-dependent; select gigabit+ for distributed jobs. Storage: 100GB-2TB NVMe SSDs typical, ample for <50GB datasets. Multi-GPU: 2-4x PCIe scaling possible, no NVLink. CUDA 11.x standard on verified hosts. Consistent perf known from user benchmarks; unknowns include exact CPU/RAM (often i7/32GB). Honest: great for prototyping/inference, lags pro GPUs in FP16/large-scale training; check host specs.
A decentralized marketplace for absolute lowest costs and distributed experiments.
Best For
Unique Features
- Granular search filters like DLPerf/$
- Decentralized marketplace
VRAM
8GB
Architecture
Pascal
Tier
consumer
Platform Features
Getting Started
Launch NVIDIA GeForce GTX 1080 on Vast.ai via intuitive dashboard: search global inventory, filter for value, rent instantly with ML-optimized images. Connect via SSH/Jupyter for seamless PyTorch/TensorFlow workflows. Perfect for rapid experimentation at minimal cost.
Steps
- 1Sign up on Vast.ai, verify email, add payment method via dashboard.
- 2Search 'GTX 1080', filter by DLPerf/$, reliability >4.5 stars, sort lowest $/hr.
- 3Select on-demand/spot instance, pick Docker image (e.g., runpod/pytorch), configure RAM/SSD, rent.
- 4Access via SSH with provided key/IP; run 'nvidia-smi' to confirm GPU.
- 5Deploy workloads; use templates for multi-GPU or auto-scaling if needed.
Pro Tips
- Filter hosts by high DLPerf/$ and uptime >99% to balance cost with reliable ML performance and minimize interruptions.
- Opt for spot instances on non-urgent tasks to slash costs by 50-80%, monitoring for interruptions via Vast.ai alerts.
- Use pre-built templates for PyTorch/TensorFlow to launch in <2 minutes, saving setup time for iterative experiments.
Frequently Asked Questions
What is Vast.ai's billing model for NVIDIA GeForce GTX 1080?▾
Vast.ai bills per-hour for GPU instances including NVIDIA GeForce GTX 1080. Hourly billing means you pay for full hours even if your job completes mid-hour. Plan your workloads accordingly to maximize cost efficiency.
Does Vast.ai offer spot instances for NVIDIA GeForce GTX 1080?▾
Yes, Vast.ai offers spot/preemptible instances for NVIDIA GeForce GTX 1080, which can reduce costs by 50-80% compared to on-demand pricing. Spot instances are ideal for fault-tolerant workloads like batch inference, hyperparameter tuning, and training jobs with checkpointing. Note that spot instances can be interrupted when demand is high, so ensure your workflow can handle preemption gracefully.
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