Model Comparison
Phi-4 Multimodal Instruct
vs. Step3 VL 10B
Comparing 2 AI models · 11 benchmarks · Microsoft, StepFun
Recommended Pick
StStep3 VL 10B7 metric winsStrongest on: TTFT, Latency, Reasoning
Lowest Price
Phi-4 Multimodal Instruct
$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
Reasoning gap
Step3 VL 10B leads Phi-4 Multimodal Instruct by 5.8 points on reasoning.
Top-pick rationale
Step3 VL 10B wins 7 measurable categories, including TTFT, Latency, Reasoning, Intelligence.
Response Face-Off
Run one prompt through the selected models and compare response quality with live speed and cost context.
Phi-4 Multimodal Instruct
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 Multimodal Instruct | Top Pick St Step3 VL 10B |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $0.00/1M | $0.00/1M |
| Output Cost | $0.00/1M | $0.00/1M |
| Specifications | ||
| Organization | Microsoft | StepFun |
| Release Date | Feb 26, 2025 | Jan 20, 2026 |
| Performance & Speed | ||
| Throughput | 16.9 tok/s | — |
| TTFT | 363ms | — |
| Latency | 363ms | — |
| Composite Indices | ||
| Reasoning Score | 23.8 | 29.6 |
| Intelligence | 4.5 | 9.5 |
| Standard Benchmarks | ||
| GPQA | 31.5% | 69.0% |
| MMLU Pro | 48.5% | — |
| HLE | 4.4% | 10.2% |
| LiveCodeBench | 13.1% | — |
| MATH 500 | 69.3% | — |
| AIME (Original) | 9.3% | — |
| SciCode | 11.0% | 31.1% |
| LCR | — | 0.0% |
| IFBench | — | 50.2% |
| TAU-bench v2 | — | 16.1% |
| TerminalBench Hard | — | 5.3% |
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.
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 Multimodal Instruct
- Cost-sensitive applications
- High-volume processing
Step3 VL 10B
- Complex reasoning tasks
- Research & analysis
