Model Comparison
Phi-4
vs. Step3 VL 10B
Comparing 2 AI models · 12 benchmarks · Microsoft, StepFun
Recommended Pick
Strongest on: Input price, Output price, TTFT
Lowest Price
Step3 VL 10B
$0.00/1M input price
Best Reasoning
Step3 VL 10B
29.6 reasoning score
Blends available reasoning benchmarks
Composite Indices
Higher is better; speed and price are normalized
Standard Benchmarks
Only benchmarks with data are shown
Differences That Matter
Price gap
Step3 VL 10B is ∞x cheaper on input tokens than Phi-4.
Reasoning gap
Step3 VL 10B leads Phi-4 by 1.3 points on reasoning.
Top-pick rationale
Step3 VL 10B wins 12 measurable categories, including Input price, Output price, TTFT, Latency.
Response Face-Off
Run one prompt through the selected models and compare response quality with live speed and cost context.
Phi-4
Microsoft
TTFT
—
Time
—
tok/s
—
Tokens
—
Cost
—
Step3 VL 10B
StepFun
TTFT
—
Time
—
tok/s
—
Tokens
—
Cost
—
Which answer was more useful?
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Full Comparison
| Metric | Mi Phi-4 | Top Pick St Step3 VL 10B |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $0.13/1M | $0.00/1M |
| Output Cost | $0.50/1M | $0.00/1M |
| Blended (3:1) | $0.22/1M | — |
| Specifications | ||
| Organization | Microsoft | StepFun |
| Release Date | Dec 12, 2024 | Jan 20, 2026 |
| Performance & Speed | ||
| Throughput | 31.8 tok/s | — |
| TTFT | 504ms | — |
| Latency | 504ms | — |
| Composite Indices | ||
| Value Score | 100.0 | — |
| Reasoning Score | 28.3 | 29.6 |
| Intelligence | 4.9 | 9.5 |
| Math | 18.0 | — |
| Standard Benchmarks | ||
| GPQA | 57.5% | 69.0% |
| MMLU Pro | 71.4% | — |
| HLE | 4.1% | 10.2% |
| LiveCodeBench | 23.1% | — |
| MATH 500 | 81.0% | — |
| AIME 2025 | 18.0% | — |
| AIME (Original) | 14.3% | — |
| SciCode | 26.0% | 31.1% |
| LCR | 0.0% | 0.0% |
| IFBench | 23.5% | 50.2% |
| TAU-bench v2 | 0.0% | 16.1% |
| TerminalBench Hard | 3.8% | 5.3% |
Key Takeaways
Step3 VL 10B offers the best value at $0.00/1M,making it ideal for high-volume applications and cost-conscious projects.
Step3 VL 10B has the strongest reasoning profile with a 29.6 reasoning score,combining the available reasoning-heavy benchmarks.
All models support context windows of ∞+ tokens,suitable for processing lengthy documents and maintaining extended conversations.
When to Choose Each Model
Phi-4
- General-purpose AI
- Versatile applications
Step3 VL 10B
- Cost-sensitive applications
- High-volume processing
- Complex reasoning tasks
- Research & analysis