Understanding the Cost Trade-Offs: A100 vs H100 vs H200 for AI Inference
Choosing the right GPU isn’t just about power—it’s about efficiency. Choosing the wrong GPU can cost you 3× more. On Nebula Block, builders can select from A100, H100, and H200 instances, each offering different trade-offs in memory capacity, throughput, latency, and cost.
Whether you’re optimizing for LLM inference, RAG pipelines, or real-time chat agents, here's how to pick the best fit based on real-world performance and pricing.
📊 At a Glance: GPU Comparison
| GPU | Memory (vRAM) | Peak TFLOPS (FP8/FP16) | Memory Bandwidth | Hourly Price (Nebula Block) |
|---|---|---|---|---|
| A100 | 40–80 GB HBM2e | ~312 TFLOPS (FP16) | 2.0 TB/s | ~$1.22/hr |
| H100 | 80 GB HBM3 | ~990 TFLOPS (FP8) | 3.35 TB/s | ~$1.52-$3.2/hr |
| H200 | 141 GB HBM3e | ~990 TFLOPS (FP8) | 4.8 TB/s | ~$3/hr |
Pricing varies by configuration—spot, region, and memory tier. View live pricing at Nebula Block.
Technical Performance Breakdown
| GPU | Usable RAM | Inference Speed | Latency (avg) | Ideal For |
|---|---|---|---|---|
| A100 | ~65GB | Baseline | ~250ms | Small–mid LLMs (≤30B), standard workloads |
| H100 | ~70GB | 2.5–4× A100 | ~120ms | 70B LLMs, APIs, latency-sensitive deployments |
| H200 | ~125GB | 3–5× A100 (batch/RAG) | ~100ms | 100K+ context, multimodal, large-batch systems |
When to Use Which GPU?
1. Throughput-Heavy Inference
If you’re running LLM summarizers or processing token-heavy documents:
- Choose H100 → FP8 acceleration dramatically cuts runtime—lowering per-token cost and making it ideal for production loops.
- Go H200 for batch-heavy or long-context pipelines (e.g., RAG systems).
2. Latency-Sensitive Apps
Real-time agents or chatbots demand low wait times:
- H100 excels at sub-150ms latency, especially with TensorRT-LLM.
- H200 adds stability for larger prompt handling without delay.
- A100 is viable for non-critical, low-traffic apps.
3. Memory-Limited Workloads
Working with LLaMA-3-70B, Claude 4, or long input chains?
- H200’s 141GB RAM avoids model sharding or quantization.
- A100 may struggle on 70B+ or multimodal inputs.
Quick GPU Selection – Real-World Decision Guide
| Scenario / Objective | Best GPU | Why it fits |
|---|---|---|
| Fine-tuning small LLMs (13B–30B) | A100 | Enough memory, lowest cost per hour—great for dev/test or light prod use |
| Low-latency APIs (e.g., chatbots, assistants) | H100 | Delivers real-time responses; better throughput under production loads |
| RAG / 100K+ context with long prompts | H200 | High memory bandwidth + 141GB RAM ensures stable batching + long input |
| Multimodal or embedding-heavy inference | H200 | Handles large image/text fusion models without needing quantization |
| Benchmarking or model comparison | A100 / H100 | Fast spin-up, pay-per-second billing helps optimize before scaling |
| Cost-sensitive workflows / off-peak jobs | A100 (Spot) | Spot pricing makes it ideal for experiments or jobs that can pause/retry |
| Scaling production inference with low wait time | H100 (Spot) | Cost-efficient for high-volume APIs that need throughput + speed |
| Long-sequence agents or retrieval + summarization | H200 | Excels in >100K token history, batch context compression, fast I/O |
✅ Higher hourly cost ≠ higher total cost. H100 and H200 complete jobs faster, saving compute time.
Why Nebula Block?
- Per-Second Billing: Only pay for the exact time your model runs — no hourly rounding or idle charges.
- No Lock-In: Launch and scale freely, without vendor tie-in or infrastructure commitment.
- Serverless Inference: Instantly run preloaded models (DeepSeek, Claude, Mixtral…) via API — zero deployment required.
- One-Click GPU Instances: Spin up A100, H100, or H200 VMs in under 60 seconds — tuned for training and fine-tuning.
- Encrypted Storage: Securely manage datasets, checkpoints, and model weights with built-in storage.
- API & CLI Orchestration: Seamlessly automate workflows and control budgets with developer-friendly tools.
Final Thought
When it comes to GPU selection on Nebula Block, real-world efficiency beats raw specs. The right GPU reduces your total compute bill—not just runtime. Test real-world performance per dollar — start with free credits on Nebula Block.
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