NVIDIA B200
The NVIDIA B200 (Blackwell architecture) represents a generational leap in AI compute. 192GB HBM3e memory, 8TB/s bandwidth, and 2nd-gen Transformer Engine deliver 2.5× faster LLM training than H100. Key innovations: FP4 precision for even faster inference, 5th-generation NVLink for scaling to 10,000s of GPUs, and improved power efficiency. Expected availability late 2024/early 2025 on major clouds. Designed for: training GPT-5-scale models (trillions of parameters), real-time inference at unprecedented scale, next-generation multimodal AI. Early adopters: OpenAI, Microsoft, Meta announced deployments.
Overview
B200 sets new standard for AI performance. Train trillion-parameter models, fine-tune 70B models in 1 hour (vs 3 hours H100), serve inference at 2.5× throughput. 192GB memory enables training even larger models on single GPU. FP4 precision doubles inference throughput again (4× vs H100). Expected to power GPT-5, Claude 4, and other next-generation AI systems. Pricing expected $35K-$50K per unit, cloud rental $4-6/hr (estimated).
Key Specifications
- **Memory**: 192GB HBM3e, 8TB/s bandwidth
- **Compute**: 2.5× H100 for LLM training (estimated)
- **FP4 Precision**: 4-bit floating point for inference
- **NVLink**: 5th-gen, 1.8TB/s for multi-GPU
- **Power**: ~700-1000W (estimated)
- **Availability**: Late 2024/Q1 2025
Business Impact
B200 enables AI capabilities impossible today. Train custom foundation models (100B+ parameters) at startup scale. Serve real-time multimodal AI (vision + language + audio) with single-digit millisecond latency. Reduce inference costs 50-70% through FP4 precision. For enterprises investing in AI infrastructure 2025+, B200 represents 3-5 year future-proofing vs H100/H200.