Model Comparison
Nemotron Nano 9B V2 (Reasoning)
vs. Phi-4
Comparing 2 AI models · 12 benchmarks · NVIDIA, Microsoft
Recommended Pick
NV Nemotron Nano 9B V2 (Reasoning) 16 metric wins Strongest on: Value, Input price, Output price
Best Value
Nemotron Nano 9B V2 (Reasoning)
100.0 value score
43.2 reasoning / $0.07/1M
Lowest Price
Nemotron Nano 9B V2 (Reasoning)
$0.04/1M input price
Best Reasoning
Nemotron Nano 9B V2 (Reasoning)
43.2 reasoning score
Blends available reasoning benchmarks
Best for Coding
Phi-4
11.2 coding index
Composite Indices
Higher is better; speed and price are normalized
Standard Benchmarks
Only benchmarks with data are shown
Differences That Matter
Best value
Nemotron Nano 9B V2 (Reasoning) has the strongest quality-to-price mix at 100.0 out of 100 value points.
Price gap
Nemotron Nano 9B V2 (Reasoning) is 3.1x cheaper on input tokens than Phi-4.
Speed gap
Nemotron Nano 9B V2 (Reasoning) generates about 3.1x as many tokens per second as Phi-4.
Reasoning gap
Nemotron Nano 9B V2 (Reasoning) leads Phi-4 by 14.1 points on reasoning.
Coding gap
Phi-4 leads Nemotron Nano 9B V2 (Reasoning) by 2.9 points on coding.
Response Face-Off
Run one prompt through the selected models and compare response quality with live speed and cost context.
Nemotron Nano 9B V2 (Reasoning)
NVIDIA
TTFT
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Time
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tok/s
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Tokens
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Cost
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Phi-4
Microsoft
TTFT
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Time
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tok/s
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Tokens
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Cost
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Which answer was more useful?
Full Comparison
| Metric | Top Pick NV Nemotron Nano 9B V2 (Reasoning) | Mi Phi-4 |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $0.04/1M | $0.13/1M |
| Output Cost | $0.16/1M | $0.50/1M |
| Blended (3:1) | $0.07/1M | $0.22/1M |
| Specifications | ||
| Organization | NVIDIA | Microsoft |
| Release Date | Aug 18, 2025 | Dec 12, 2024 |
| Performance & Speed | ||
| Throughput | 116.7 tok/s | 38.1 tok/s |
| TTFT | 252ms | 526ms |
| Latency | 17391ms | 526ms |
| Composite Indices | ||
| Value Score | 100.0 | 21.5 |
| Reasoning Score | 43.2 | 29.0 |
| Intelligence | 14.8 | 10.4 |
| Coding | 8.3 | 11.2 |
| Math | 69.7 | 18.0 |
| Standard Benchmarks | ||
| GPQA | 57.0% | 57.5% |
| MMLU Pro | 74.2% | 71.4% |
| HLE | 4.6% | 4.1% |
| LiveCodeBench | 72.4% | 23.1% |
| MATH 500 | — | 81.0% |
| AIME 2025 | 69.7% | 18.0% |
| AIME (Original) | — | 14.3% |
| SciCode | 22.0% | 26.0% |
| LCR | 21.0% | 0.0% |
| IFBench | 27.6% | 23.5% |
| TAU-bench v2 | 21.9% | 0.0% |
| TerminalBench Hard | 1.5% | 3.8% |
Key Takeaways
Nemotron Nano 9B V2 (Reasoning) offers the best value at $0.04/1M, making it ideal for high-volume applications and cost-conscious projects.
Nemotron Nano 9B V2 (Reasoning) has the strongest reasoning profile with a 43.2 reasoning score, combining the available reasoning-heavy benchmarks.
Phi-4 reaches a 11.2 coding index, making it the top choice for software development and code generation tasks.
All models support context windows of ∞+ tokens, suitable for processing lengthy documents and maintaining extended conversations.
When to Choose Each Model
Nemotron Nano 9B V2 (Reasoning)
- Cost-sensitive applications
- High-volume processing
- Complex reasoning tasks
- Research & analysis
Phi-4
- Code generation
- Software development
