Explore our powerful, parameter-scaled AI models designed for optimal performance and efficiency.
View ModelsSelect the optimal model architecture for your enterprise needs. All models include enterprise-grade security, dedicated support, and SLAs.
Detailed technical comparison of our parameter-scaled models
| Feature | Venkatai 7B | Venkatai 49B | Venkatai 401B |
|---|---|---|---|
| Parameters | 7 Billion | 49 Billion | 401 Billion |
| Context Window | 64K tokens | 128K tokens | 256K tokens |
| Training Data | 1.8T tokens | 3.2T tokens | 6.5T tokens |
| Training Compute | 1.2 PF-days | 18 PF-days | 240 PF-days |
| Hardware Req. | Single GPU (24GB) | 4x GPU Cluster | 8x TPU Pod |
| Memory Requirements | 14GB VRAM | 80GB VRAM | 320GB VRAM |
| Inference Speed | ~120 tok/sec | ~45 tok/sec | ~18 tok/sec |
| Multi-modal Support | Text Only | Text+Image | Full Multi-modal |
| Est. Training Cost | $120k | $2.1M | $18M+ |
| Typical Use Cases | Edge devices, Chatbots | Enterprise automation | Research, AGI systems |
| Pricing Model | $5/mo | $20/mo | Custom |
Why enterprises choose Venkatai's parameter-scaled models
Each model size is optimized for specific hardware configurations, from edge devices to TPU pods.
All models include end-to-end encryption, role-based access control, and audit logging.
Mixture-of-Experts (MoE) design allows dynamic allocation of parameters per task for efficiency.
Answers to common questions about parameter scaling
Choosing the right size depends on your specific needs:
• 7B Model: Ideal for edge deployment, real-time applications (like chatbots), and tasks requiring high speed on lower-end hardware. Now with a 64K context window for better understanding of longer conversations.
• 49B Model: Offers a strong balance between performance and resource usage. Suitable for most enterprise automation, content generation, and complex analysis tasks. Supports basic multi-modal input and features a large 128K context window.
• 401B Model: Reserved for research, cutting-edge applications, and tasks demanding maximum capability, complex reasoning, and full multi-modal fusion. Features a massive 256K context window and requires significant hardware resources.
Yes! Our unified API endpoints allow you to switch between model sizes (e.g., from 7B to 49B) with minimal code changes. While there isn't automatic state transfer between fundamentally different models, we provide guidance and tools to help manage context continuity during transitions if needed for your application.
All models come with enterprise-grade support, including access to documentation, community forums, and standard business hour technical assistance. The 49B model includes 24/7 priority support, while the 401B model features dedicated "white-glove" support with assigned technical account managers and direct access to our research teams.
Yes, custom fine-tuning is a key feature, particularly for our 49B and 401B models. We offer services to adapt the models to your specific datasets and tasks, ensuring optimal performance for your unique use case. The 7B model also supports fine-tuning, often manageable directly by customers using standard frameworks.