| Signal | Nemotron Nano 9B V2 | Delta | o3 Deep Research |
|---|---|---|---|
Capabilities | 67 | -33 | |
Pricing | 0 | -40 | |
Context window size | 81 | -3 | |
Recency | 97 | -3 | |
Output Capacity | 20 | -63 | |
Benchmarks | 0 | -88 | |
| Overall Result | 0 wins | of 6 | 6 wins |
0
days ranked higher
0
days
30
days ranked higher
NVIDIA
OpenAI
Nemotron Nano 9B V2 saves you $2988.00/month
That's $35856.00/year compared to o3 Deep Research at your current usage level of 100K calls/month.
| Metric | Nemotron Nano 9B V2 | o3 Deep Research | Winner |
|---|---|---|---|
| Overall Score | 72 | 92 | o3 Deep Research |
| Rank | #144 | #8 | o3 Deep Research |
| Quality Rank | #144 | #8 | o3 Deep Research |
| Adoption Rank | #144 | #8 | o3 Deep Research |
| Parameters | 9B | -- | -- |
| Context Window | 131K | 200K | o3 Deep Research |
| Pricing | $0.04/$0.16/M | $10.00/$40.00/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 100 | o3 Deep Research |
| Pricing | 0 | 40 | o3 Deep Research |
| Context window size | 81 | 84 | o3 Deep Research |
| Recency | 97 | 100 | o3 Deep Research |
| Output Capacity | 20 | 83 | o3 Deep Research |
| Benchmarks | -- | 88 | o3 Deep Research |
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 72/100 (rank #144), placing it in the top 51% of all 290 models tracked.
Scores 92/100 (rank #8), placing it in the top 98% of all 290 models tracked.
o3 Deep Research has a 20-point advantage, which typically translates to noticeably stronger performance on complex reasoning, code generation, and multi-step tasks.
Nemotron Nano 9B V2 offers 100% better value per quality point. At 1M tokens/day, you'd spend $3.00/month with Nemotron Nano 9B V2 vs $750.00/month with o3 Deep Research - a $747.00 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. Nemotron Nano 9B V2 also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (200K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.16/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (92/100) 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
o3 Deep Research clearly outperforms Nemotron Nano 9B V2 with a significant 19.900000000000006-point lead. For most general use cases, o3 Deep Research is the stronger choice. However, Nemotron Nano 9B V2 may still excel in niche scenarios.
Best for Quality
Nemotron Nano 9B V2
Marginally better benchmark scores; both are excellent
Best for Cost
Nemotron Nano 9B V2
100% lower pricing; better value at scale
Best for Reliability
Nemotron Nano 9B V2
Higher uptime and faster response speeds
Best for Prototyping
Nemotron Nano 9B V2
Stronger community support and better developer experience
Best for Production
Nemotron Nano 9B V2
Wider enterprise adoption and proven at scale
by NVIDIA
| Capability | Nemotron Nano 9B V2 | o3 Deep Research |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Searchdiffers | ||
| Image Output |
NVIDIA
OpenAI
Nemotron Nano 9B V2 saves you $65.74/month
That's 100% cheaper than o3 Deep Research 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 | Nemotron Nano 9B V2 | o3 Deep Research |
|---|---|---|
| Context Window | 131K | 200K |
| Max Output Tokens | -- | 100,000 |
| Open Source | Yes | No |
| Created | Sep 5, 2025 | Oct 10, 2025 |
o3 Deep Research scores 92/100 (rank #8) compared to Nemotron Nano 9B V2's 72/100 (rank #144), giving it a 20-point advantage. o3 Deep Research is the stronger overall choice, though Nemotron Nano 9B V2 may excel in specific areas like cost efficiency.
Nemotron Nano 9B V2 is ranked #144 and o3 Deep Research is ranked #8 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.
Nemotron Nano 9B V2 is cheaper at $0.16/M output tokens vs o3 Deep Research's $40.00/M output tokens - 250.0x more expensive. Input token pricing: Nemotron Nano 9B V2 at $0.04/M vs o3 Deep Research at $10.00/M.
o3 Deep Research has a larger context window of 200,000 tokens compared to Nemotron Nano 9B V2's 131,072 tokens. A larger context window means the model can process longer documents and conversations.