Model Comparison
Nemotron Nano 12B v2 VL (Reasoning)
vs. Phi-4 Mini Instruct
Comparing 2 AI models · 12 benchmarks · NVIDIA, Microsoft
Recommended Pick
NV Nemotron Nano 12B v2 VL (Reasoning) 16 metric wins Strongest on: Throughput, TTFT, Reasoning
Lowest Price
Phi-4 Mini Instruct
$0.00/1M input price
Best Reasoning
Nemotron Nano 12B v2 VL (Reasoning)
45.5 reasoning score
Blends available reasoning benchmarks
Best for Coding
Nemotron Nano 12B v2 VL (Reasoning)
11.7 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 Mini Instruct is ∞x cheaper on input tokens than Nemotron Nano 12B v2 VL (Reasoning).
Speed gap
Nemotron Nano 12B v2 VL (Reasoning) generates about 12.3x as many tokens per second as Phi-4 Mini Instruct.
Reasoning gap
Nemotron Nano 12B v2 VL (Reasoning) leads Phi-4 Mini Instruct by 26.7 points on reasoning.
Coding gap
Nemotron Nano 12B v2 VL (Reasoning) leads Phi-4 Mini Instruct by 8.1 points on coding.
Top-pick rationale
Nemotron Nano 12B v2 VL (Reasoning) wins 16 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 12B v2 VL (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 Mini Instruct
Microsoft
TTFT
—
Time
—
tok/s
—
Tokens
—
Cost
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Which answer was more useful?
Full Comparison
| Metric | Top Pick NV Nemotron Nano 12B v2 VL (Reasoning) | Mi Phi-4 Mini Instruct |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $0.20/1M | $0.00/1M |
| Output Cost | $0.60/1M | $0.00/1M |
| Blended (3:1) | $0.30/1M | — |
| Specifications | ||
| Organization | NVIDIA | Microsoft |
| Release Date | Oct 28, 2025 | Feb 26, 2024 |
| Performance & Speed | ||
| Throughput | 290.2 tok/s | 23.6 tok/s |
| TTFT | 257ms | 1393ms |
| Latency | 7150ms | 1393ms |
| Composite Indices | ||
| Value Score | 100.0 | — |
| Reasoning Score | 45.5 | 18.8 |
| Intelligence | 14.9 | 8.4 |
| Coding | 11.7 | 3.6 |
| Math | 75.0 | 6.7 |
| Standard Benchmarks | ||
| GPQA | 57.2% | 33.1% |
| MMLU Pro | 75.9% | 46.5% |
| HLE | 5.3% | 4.2% |
| LiveCodeBench | 69.4% | 12.6% |
| MATH 500 | — | 69.6% |
| AIME 2025 | 75.0% | 6.7% |
| AIME (Original) | — | 3.0% |
| SciCode | 26.2% | 10.8% |
| LCR | 40.0% | 13.7% |
| IFBench | 31.9% | 21.1% |
| TAU-bench v2 | 21.3% | 8.2% |
| TerminalBench Hard | 4.5% | 0.0% |
Key Takeaways
Phi-4 Mini Instruct offers the best value at $0.00/1M, making it ideal for high-volume applications and cost-conscious projects.
Nemotron Nano 12B v2 VL (Reasoning) has the strongest reasoning profile with a 45.5 reasoning score, combining the available reasoning-heavy benchmarks.
Nemotron Nano 12B v2 VL (Reasoning) reaches a 11.7 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 12B v2 VL (Reasoning)
- Complex reasoning tasks
- Research & analysis
- Code generation
- Software development
Phi-4 Mini Instruct
- Cost-sensitive applications
- High-volume processing
