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Consistent Character by fofr
✓ verifiedPaid
Pay-per-use cloud API to run, fine-tune, and deploy thousands of open-source and proprietary AI models with one line of code.
1.3M visits/mo17K saves
Pricing
Unlimited Proxy (Christmas Special): Starting from $62.85 / day
Residential Proxy (10GB): $9.00
Residential Proxy (60GB): $52.00
Residential Proxy (100GB): $85.00
Residential Proxy (300GB): $240.00
Residential Proxy (1000GB): $750.00
Residential Proxy (3000GB): $2000.00
Residential Proxy (5000GB): $3000.00
Residential Proxy (10000GB): $5000.00
Long Acting ISP Proxy: Starting from $0.27/GB
CPU (Small): $0.000025/sec ($0.09/hr)
Nvidia A100 80GB: $0.0014/sec ($5.04/hr)
Nvidia H100: $0.001525/sec ($5.49/hr)
Free trial available
No public pricing
Core features
- ✦100M+ Premium Residential Proxies
- ✦Blazing-Fast Internet Access
- ✦Rotating and Static Proxies
- ✦Country/State/City Targeting
- ✦HTTP/SOCKS5 Support
- ✦All-in-One Dashboard for management
- ✦Developer-Friendly Integration
- ✦24/7 Support
- ✦Real-Time Usage Analytics
- ✦One-line API calls to run community and proprietary AI models
- ✦Support for image, video, speech, and LLM generation models
- ✦Fine-tuning and custom model deployment via Cog
- ✦Per-second usage billing on shared or dedicated hardware
- ✦Automatic scaling for high-traffic private models
- ✦Thousands of community-published models with production APIs
- ✦Fast tensor operations
- ✦Differentiable tensors for gradient-based optimization
- ✦Network connectivity
- ✦Integration with Bun and Flashlight
- ✦Support for GPU computation with CUDA (Linux) and CPU computation (macOS)
Use cases
- →Market Research
- →Brand Protection
- →Human-like Scraping
- →Bypass Restrictions
- →Ad Verification
- →SERP Monitoring
- →Social Media Management
- →E-commerce Data Collection
- →Developers embedding image/video/speech generation into an app via API
- →Teams deploying and scaling their own fine-tuned models
- →Builders comparing outputs from multiple AI models in one playground
- →Companies avoiding GPU infrastructure management for ML inference
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
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