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DeepSeek vs Amazon

DeepSeek (12 models) vs Amazon (5 models) - compared across composite scores, pricing, capabilities, and context windows.

Models
12
Avg Score
66
Top Model
Score: 87
Price Range
$0.180 - $2.50
per 1M output tokens
12 open source1.0M max context
Models
5
Avg Score
44
Top Model
Score: 61
Price Range
$0.140 - $12.50
per 1M output tokens
1.0M max context

Head-to-Head: DeepSeek vs Amazon Model Matchups

Capability Comparison

CapabilityDeepSeekAmazonLeader
Vision
0/124/5Amazon
Reasoning
10/121/5DeepSeek
Function Calling
11/125/5DeepSeek
JSON Mode
11/120/5DeepSeek
Web Search
0/120/5Tie
Streaming
12/125/5DeepSeek
Image Output
0/120/5Tie

Pricing Comparison

MetricDeepSeekAmazon
Cheapest Input (per 1M tokens)$0.090
DeepSeek V4 Flash 0731
$0.035
Nova Micro 1.0
Cheapest Output (per 1M tokens)$0.180$0.140
Most Expensive Input (per 1M tokens)$0.800
R1
$2.50
Nova Premier 1.0
Most Expensive Output (per 1M tokens)$2.50$12.50
Free Models00
Max Context Window1.0M1.0M

All DeepSeek Models (12)

ModelScoreInput $/MOutput $/M
DeepSeek V4 Pro87$0.435$0.870
DeepSeek V3.281$0.260$0.380
R1 052879$0.500$2.15
R174$0.700$2.50
DeepSeek V3.2 Exp72$0.270$0.410
DeepSeek V3.172$0.250$0.950
DeepSeek V3 032472$0.270$1.12
DeepSeek V370$0.257$1.03
DeepSeek V3.1 Terminus69$0.270$1.00
R1 Distill Llama 70B41$0.800$0.800
DeepSeek V4 Flash 073140$0.090$0.180
DeepSeek V4 Flash 042340$0.140$0.280

All Amazon Models (5)

ModelScoreInput $/MOutput $/M
Nova 2 Lite61$0.300$2.50
Nova Premier 1.040$2.50$12.50
Nova Lite 1.040$0.060$0.240
Nova Micro 1.040$0.035$0.140
Nova Pro 1.040$0.800$3.20
Frequently Asked Questions

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.

DeepSeek vs Amazon - AI Provider Comparison (2026) | LM Market Cap