| Signal | DeepSeek V3.2 | Delta | Nova Pro 1.0 |
|---|---|---|---|
Capabilities | 67 | +17 | |
Benchmarks | 70 | +70 | |
Pricing | 0 | -3 | |
Context window size | 83 | -4 | |
Recency | 100 | +53 | |
Output Capacity | 20 | -42 | |
| Overall Result | 3 wins | of 6 | 3 wins |
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DeepSeek
Amazon
DeepSeek V3.2 saves you $195.00/month
That's $2340.00/year compared to Nova Pro 1.0 at your current usage level of 100K calls/month.
| Metric | DeepSeek V3.2 | Nova Pro 1.0 | Winner |
|---|---|---|---|
| Overall Score | 74 | 58 | DeepSeek V3.2 |
| Rank | #113 | #232 | DeepSeek V3.2 |
| Quality Rank | #113 | #232 | DeepSeek V3.2 |
| Adoption Rank | #113 | #232 | DeepSeek V3.2 |
| Parameters | -- | -- | -- |
| Context Window | 164K | 300K | Nova Pro 1.0 |
| Pricing | $0.26/$0.38/M | $0.80/$3.20/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 50 | DeepSeek V3.2 |
| Benchmarks | 70 | -- | DeepSeek V3.2 |
| Pricing | 0 | 3 | Nova Pro 1.0 |
| Context window size | 83 | 87 | Nova Pro 1.0 |
| Recency | 100 | 47 | DeepSeek V3.2 |
| Output Capacity | 20 | 62 | Nova Pro 1.0 |
Our composite score (0–100) combines six weighted signals: benchmark performance (25%), pricing efficiency (25%), context window size (15%), model recency (15%), output capacity (10%), and capability versatility (10%). Here's what the scores mean for these two models:
Scores 74/100 (rank #113), placing it in the top 61% of all 290 models tracked.
Scores 58/100 (rank #232), placing it in the top 20% of all 290 models tracked.
DeepSeek V3.2 has a 16-point advantage, which typically translates to noticeably stronger performance on complex reasoning, code generation, and multi-step tasks.
DeepSeek V3.2 offers 84% better value per quality point. At 1M tokens/day, you'd spend $9.60/month with DeepSeek V3.2 vs $60.00/month with Nova Pro 1.0 - a $50.40 monthly difference.
Both models have comparable response speeds. For most applications, the latency difference is negligible.
When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.
Code generation & review
Higher benchmark score (0/100) indicates stronger performance on coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Faster response time (speed score 0/100) is critical for user-facing chat. DeepSeek V3.2 also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (300K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.38/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (74/100) correlates with better nuance, coherence, and style in long-form content
Image understanding & OCR
Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly
DeepSeek V3.2 clearly outperforms Nova Pro 1.0 with a significant 15.899999999999991-point lead. For most general use cases, DeepSeek V3.2 is the stronger choice. However, Nova Pro 1.0 may still excel in niche scenarios.
Best for Quality
DeepSeek V3.2
Marginally better benchmark scores; both are excellent
Best for Cost
DeepSeek V3.2
84% lower pricing; better value at scale
Best for Reliability
DeepSeek V3.2
Higher uptime and faster response speeds
Best for Prototyping
DeepSeek V3.2
Stronger community support and better developer experience
Best for Production
DeepSeek V3.2
Wider enterprise adoption and proven at scale
by DeepSeek
| Capability | DeepSeek V3.2 | Nova Pro 1.0 |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
DeepSeek
Amazon
DeepSeek V3.2 saves you $4.36/month
That's 83% cheaper than Nova Pro 1.0 at 1,000 tokens/request and 100 requests/day.
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | DeepSeek V3.2 | Nova Pro 1.0 |
|---|---|---|
| Context Window | 164K | 300K |
| Max Output Tokens | -- | 5,120 |
| Open Source | Yes | No |
| Created | Dec 1, 2025 | Dec 5, 2024 |
DeepSeek V3.2 scores 74/100 (rank #113) compared to Nova Pro 1.0's 58/100 (rank #232), giving it a 16-point advantage. DeepSeek V3.2 is the stronger overall choice, though Nova Pro 1.0 may excel in specific areas like certain benchmarks.
DeepSeek V3.2 is ranked #113 and Nova Pro 1.0 is ranked #232 out of 290+ AI models. Rankings use a composite score combining benchmark performance (25%), pricing (25%), context window (15%), recency (15%), output capacity (10%), and versatility (10%). Scores update hourly.
DeepSeek V3.2 is cheaper at $0.38/M output tokens vs Nova Pro 1.0's $3.20/M output tokens - 8.4x more expensive. Input token pricing: DeepSeek V3.2 at $0.26/M vs Nova Pro 1.0 at $0.80/M.
Nova Pro 1.0 has a larger context window of 300,000 tokens compared to DeepSeek V3.2's 163,840 tokens. A larger context window means the model can process longer documents and conversations.