Model Comparison
Nemotron Nano 9B V2 (Reasoning)
vs. Phi-4 Multimodal Instruct
Comparing 2 AI models · 12 benchmarks · NVIDIA, Microsoft
Recommended Pick
NV Nemotron Nano 9B V2 (Reasoning) 9 metric wins Strongest on: Throughput, TTFT, Reasoning
Lowest Price
Phi-4 Multimodal Instruct
$0.00/1M input price
Best Reasoning
Nemotron Nano 9B V2 (Reasoning)
43.2 reasoning score
Blends available reasoning benchmarks
Best for Coding
Nemotron Nano 9B V2 (Reasoning)
8.3 coding index
Composite Indices
Higher is better; speed and price are normalized
Standard Benchmarks
Only benchmarks with data are shown
Differences That Matter
Price gap
Phi-4 Multimodal Instruct is ∞x cheaper on input tokens than Nemotron Nano 9B V2 (Reasoning).
Speed gap
Nemotron Nano 9B V2 (Reasoning) generates about 7.0x as many tokens per second as Phi-4 Multimodal Instruct.
Reasoning gap
Nemotron Nano 9B V2 (Reasoning) leads Phi-4 Multimodal Instruct by 18.3 points on reasoning.
Top-pick rationale
Nemotron Nano 9B V2 (Reasoning) wins 9 measurable categories, including Throughput, TTFT, Reasoning, Intelligence.
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 Multimodal Instruct
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 Multimodal Instruct |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $0.04/1M | $0.00/1M |
| Output Cost | $0.16/1M | $0.00/1M |
| Blended (3:1) | $0.07/1M | — |
| Specifications | ||
| Organization | NVIDIA | Microsoft |
| Release Date | Aug 18, 2025 | Feb 26, 2025 |
| Performance & Speed | ||
| Throughput | 116.7 tok/s | 16.8 tok/s |
| TTFT | 252ms | 1330ms |
| Latency | 17391ms | 1330ms |
| Composite Indices | ||
| Value Score | 100.0 | — |
| Reasoning Score | 43.2 | 24.9 |
| Intelligence | 14.8 | 10.0 |
| Coding | 8.3 | — |
| Math | 69.7 | — |
| Standard Benchmarks | ||
| GPQA | 57.0% | 31.5% |
| MMLU Pro | 74.2% | 48.5% |
| HLE | 4.6% | 4.4% |
| LiveCodeBench | 72.4% | 13.1% |
| MATH 500 | — | 69.3% |
| AIME 2025 | 69.7% | — |
| AIME (Original) | — | 9.3% |
| SciCode | 22.0% | 11.0% |
| LCR | 21.0% | — |
| IFBench | 27.6% | — |
| TAU-bench v2 | 21.9% | — |
| TerminalBench Hard | 1.5% | — |
Key Takeaways
Phi-4 Multimodal Instruct offers the best value at $0.00/1M, 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.
Nemotron Nano 9B V2 (Reasoning) reaches a 8.3 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)
- Complex reasoning tasks
- Research & analysis
- Code generation
- Software development
Phi-4 Multimodal Instruct
- Cost-sensitive applications
- High-volume processing
