DeepSeek (13 models) vs Amazon (5 models) - compared across composite scores, pricing, capabilities, and context windows.
| DeepSeek | Score | vs | Amazon | Score |
|---|---|---|---|---|
| R1 0528 | 79 | Nova 2 Lite | 61 | |
| DeepSeek V4 Pro | 76 | Nova Premier 1.0 | 40 | |
| R1 | 73 | Nova Lite 1.0 | 40 | |
| DeepSeek V4 Flash | 72 | Nova Micro 1.0 | 40 | |
| DeepSeek V3 0324 | 72 | Nova Pro 1.0 | 40 |
| Capability | DeepSeek | Amazon | Leader |
|---|---|---|---|
Vision | 0/13 | 4/5 | Amazon |
Reasoning | 11/13 | 1/5 | DeepSeek |
Function Calling | 10/13 | 5/5 | DeepSeek |
JSON Mode | 12/13 | 0/5 | DeepSeek |
Web Search | 0/13 | 0/5 | Tie |
Streaming | 13/13 | 5/5 | DeepSeek |
Image Output | 0/13 | 0/5 | Tie |
| Metric | DeepSeek | Amazon |
|---|---|---|
| Cheapest Input (per 1M tokens) | $0.140 DeepSeek V4 Flash | $0.035 Nova Micro 1.0 |
| Cheapest Output (per 1M tokens) | $0.280 | $0.140 |
| Most Expensive Input (per 1M tokens) | $0.700 R1 | $2.50 Nova Premier 1.0 |
| Most Expensive Output (per 1M tokens) | $2.50 | $12.50 |
| Free Models | 0 | 0 |
| Max Context Window | 1.0M | 1.0M |
| Model | Score | Input $/M | Output $/M |
|---|---|---|---|
| R1 0528 | 79 | $0.500 | $2.15 |
| DeepSeek V4 Pro | 76 | $0.435 | $0.870 |
| R1 | 73 | $0.700 | $2.50 |
| DeepSeek V4 Flash | 72 | $0.140 | $0.280 |
| DeepSeek V3 0324 | 72 | $0.200 | $0.770 |
| DeepSeek V3.2 | 70 | $0.252 | $0.378 |
| DeepSeek V3.2 Exp | 70 | $0.270 | $0.410 |
| DeepSeek V3 | 70 | $0.320 | $0.890 |
| DeepSeek V3.1 Terminus | 69 | $0.270 | $0.950 |
| DeepSeek V3.1 | 69 | $0.150 | $0.750 |
| R1 Distill Llama 70B | 42 | $0.700 | $0.800 |
| DeepSeek V3.2 Speciale | 40 | $0.287 | $0.431 |
| R1 Distill Qwen 32B | 37 | $0.290 | $0.290 |
| 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.
DeepSeek follows a volume-based open source strategy, releasing multiple iterations like V3.0 (44/100) and V3.2 Exp (46/100) to let the community pick winners, while Amazon concentrates resources on fewer proprietary models with Nova 2 Lite hitting 54/100. This results in DeepSeek's $0.290-$2.50/M pricing reflecting compute costs, while Amazon's $0.140-$12.50/M range suggests strategic pricing with loss leaders and premium tiers.
Amazon built 4 of 5 models with vision capabilities for enterprise multimodal use cases, while DeepSeek focused on reasoning with 10 of 11 models supporting complex logic tasks. This reflects target markets: Amazon serves AWS customers needing document processing and visual analysis, while DeepSeek's open source community prioritizes code generation and mathematical reasoning at prices like $0.550/M for DeepSeek V3.1.
Amazon's infrastructure advantage shows in Nova models supporting 1M tokens (6x DeepSeek's max), critical for enterprise document processing, though this capability comes at premium pricing up to $12.50/M output tokens. DeepSeek's 164K limit across all 11 models keeps costs predictable at $0.290-$2.50/M but restricts use cases like analyzing entire codebases or processing long documents.
Amazon mandates function calling across its entire Nova lineup for seamless AWS service integration, essential for their enterprise automation focus. DeepSeek's 73% coverage (8/11 models) reflects its research heritage where models like DeepSeek V3.0 prioritize raw performance over API integration features, though newer releases increasingly add function calling at competitive prices around $0.550/M.
DeepSeek V3.2 Exp's open source nature enables on-premise deployment, fine-tuning, and complete model control that Amazon's proprietary Nova 2 Lite cannot offer despite its 8-point performance advantage. Additionally, 91% of DeepSeek's portfolio supports reasoning tasks versus 20% for Amazon, making DeepSeek the choice for specialized AI research and development even at 6x the price per million tokens.