NVIDIA NIM
Listed at https://build.nvidia.com
Overall Rank #15 ⭐ Consider
❌ Proxy required (US-based platform, export control restrictions apply) | 🌍 International
💰 Token Pricing
| Type | Price | Note |
|---|---|---|
| Input | Partner-dependent (Nemotron-3 Ultra 550B: $0.50-0.90/1M tokens) | per million tokens |
| Output | Partner-dependent (Nemotron-3 Ultra 550B: $1.70-3.60/1M tokens) | per million tokens |
💡 Free Credits: Free serverless API endpoints for prototyping (no credit card required, generate API key to start)
🤖 Supported Models (80)
Nemotron-3 Ultra 550B (a55B)Nemotron-3 Super 120B (a12B)Nemotron-3 Nano 30B (a3B)Llama-3.3-Nemotron-Super-49B v1.5Llama-3.1-Nemotron-Ultra-253B v1Llama-3.1-Nemotron-Nano-8B v1Nemotron-Mini-4B-InstructNemotron-3-Nano-Omni-30B (reasoning)
✨ Pros
- ✓NVIDIA's own Nemotron-3 series: LatentMoE (Mamba-2 + MoE + Attention) hybrid architecture
- ✓Llama-Nemotron optimized models (Llama fine-tuned by NVIDIA on their own GPUs)
- ✓OpenAI-compatible API (/v1/chat/completions), zero SDK rewrite
- ✓Free prototyping endpoints, no credit card required
- ✓80+ models covering Llama / Qwen / Mistral / DeepSeek / Kimi / GLM / Gemma / Phi
- ✓Powered by NVIDIA TensorRT-LLM inference engine for optimal GPU utilization
⚠️ Cons
- ×NVIDIA does not directly operate the API — partner endpoint pricing and QoS vary
- ×China access requires stable proxy, subject to US export controls
- ×No unified billing — each partner charges separately with individual signup
- ×Speed benchmarks not publicly published; limited third-party data
- ×Non-NVIDIA models' inference performance not publicly optimized
🎯 Best For
Teams needing the latest NVIDIA Nemotron models; developers exploring the LiveAgent platform; AI engineering teams multi-endpoint deployment testing