NVIDIA (9 models) vs Amazon (5 models) - compared across composite scores, pricing, capabilities, and context windows.
| Capability | NVIDIA | Amazon | Leader |
|---|---|---|---|
Vision | 2/9 | 4/5 | Amazon |
Reasoning | 9/9 | 1/5 | NVIDIA |
Function Calling | 9/9 | 5/5 | NVIDIA |
JSON Mode | 6/9 | 0/5 | NVIDIA |
Web Search | 0/9 | 0/5 | Tie |
Streaming | 9/9 | 5/5 | NVIDIA |
Image Output | 0/9 | 0/5 | Tie |
| Metric | NVIDIA | Amazon |
|---|---|---|
| Cheapest Input (per 1M tokens) | $0.040 Nemotron Nano 9B V2 | $0.035 Nova Micro 1.0 |
| Cheapest Output (per 1M tokens) | $0.160 | $0.140 |
| Most Expensive Input (per 1M tokens) | $0.100 Nemotron 3 Super | $2.50 Nova Premier 1.0 |
| Most Expensive Output (per 1M tokens) | $0.450 | $12.50 |
| Free Models | 5 | 0 |
| Max Context Window | 262K | 1.0M |
| Model | Score | Input $/M | Output $/M |
|---|---|---|---|
| Llama 3.3 Nemotron Super 49B V1.5 | 61 | $0.100 | $0.400 |
| Nemotron 3 Nano Omni (free) | 40 | Free | Free |
| Nemotron 3 Super (free) | 40 | Free | Free |
| Nemotron 3 Super | 40 | $0.090 | $0.450 |
| Nemotron 3 Nano 30B A3B (free) | 40 | Free | Free |
| Nemotron 3 Nano 30B A3B | 40 | $0.050 | $0.200 |
| Nemotron Nano 12B 2 VL (free) | 40 | Free | Free |
| Nemotron Nano 9B V2 (free) | 40 | Free | Free |
| Nemotron Nano 9B V2 | 40 | $0.040 | $0.160 |
| Model | Score | Input $/M | Output $/M |
|---|---|---|---|
| Nova 2 Lite | 61 | $0.300 | $2.50 |
| Nova Premier 1.0 | 40 | $2.50 | $12.50 |
| Nova Lite 1.0 | 40 | $0.060 | $0.240 |
| Nova Micro 1.0 | 40 | $0.035 | $0.140 |
| Nova Pro 1.0 | 40 | $0.800 | $3.20 |
Compare any two AI providers side-by-side.
NVIDIA prioritizes open-source accessibility with 100% of models open and 4 free options, accepting lower average performance for broader ecosystem adoption. Amazon's concentrated approach delivers higher quality per model (Nova 2 Lite hits 54/100 vs NVIDIA's best Nemotron at 45/100) but requires payment for all access, reflecting AWS's enterprise-first strategy.
Amazon's 4 out of 5 models supporting vision makes them the clear choice for multimodal applications, while NVIDIA's vision coverage at just 2 of 11 models limits their utility for image analysis pipelines. This gap is particularly striking given NVIDIA's GPU heritage, suggesting their LLM strategy prioritizes reasoning capabilities (91% coverage) over visual processing.
Amazon's 1M token context on Nova models enables processing entire codebases or lengthy documents that would require chunking on NVIDIA's best 262K limit. This 4x advantage costs significantly more at $12.50/M output tokens for Amazon's highest tier versus NVIDIA's $1.80/M max, making NVIDIA more suitable for typical sub-100K token workloads at 86% lower maximum pricing.
NVIDIA's 4 free models and complete open-source availability enable local deployment, fine-tuning, and avoiding vendor lock-in despite the 12% higher entry price. Amazon's proprietary stack with 100% function calling support targets production workloads where the 9-point quality advantage (54 vs 45 top scores) justifies API dependence.
NVIDIA equips 10 of 11 models with reasoning capabilities, positioning for complex analytical tasks and research applications where open-source flexibility matters more than raw performance. Amazon's single reasoning-capable model out of 5 suggests optimization for standard business queries, supported by their universal function calling coverage for application integration.