Model Comparison
Qwen3 32B (Non-reasoning)
vs. Step 3.7 Flash
Comparing 2 AI models · 12 benchmarks · Alibaba, StepFun
Recommended Pick
StStep 3.7 Flash13 metric winsStrongest on: Value, Input price, Output price
Best Value
Step 3.7 Flash
100.0 value score
43.7 reasoning / $0.44/1M
Lowest Price
Step 3.7 Flash
$0.20/1M input price
Best Reasoning
Step 3.7 Flash
43.7 reasoning score
Blends available reasoning benchmarks
Best for Coding
Step 3.7 Flash
39.6 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
Step 3.7 Flash has the strongest quality-to-price mix at 100.0 out of 100 value points.
Price gap
Step 3.7 Flash is 3.5x cheaper on input tokens than Qwen3 32B (Non-reasoning).
Speed gap
Step 3.7 Flash generates about 4.1x as many tokens per second as Qwen3 32B (Non-reasoning).
Reasoning gap
Step 3.7 Flash leads Qwen3 32B (Non-reasoning) by 11.8 points on reasoning.
Top-pick rationale
Step 3.7 Flash wins 13 measurable categories, including Value, Input price, Output price, Blended price.
Response Face-Off
Run one prompt through the selected models and compare response quality with live speed and cost context.
Qwen3 32B (Non-reasoning)
Alibaba
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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Step 3.7 Flash
StepFun
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?
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Full Comparison
| Metric | Al Qwen3 32B (Non-reasoning) | Top Pick St Step 3.7 Flash |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $0.70/1M | $0.20/1M |
| Output Cost | $2.80/1M | $1.15/1M |
| Blended (3:1) | $1.22/1M | $0.44/1M |
| Specifications | ||
| Organization | Alibaba | StepFun |
| Release Date | Apr 28, 2025 | May 29, 2026 |
| Performance & Speed | ||
| Throughput | 99.1 tok/s | 407.7 tok/s |
| TTFT | 1076ms | 739ms |
| Latency | 1076ms | 5645ms |
| Composite Indices | ||
| Value Score | 26.0 | 100.0 |
| Reasoning Score | 31.9 | 43.7 |
| Intelligence | 8.6 | 30.3 |
| Coding | — | 39.6 |
| Math | 19.7 | — |
| Standard Benchmarks | ||
| GPQA | 53.5% | 80.9% |
| MMLU Pro | 72.7% | — |
| HLE | 4.3% | 19.9% |
| LiveCodeBench | 28.8% | — |
| MATH 500 | 86.9% | — |
| AIME 2025 | 19.7% | — |
| AIME (Original) | 30.3% | — |
| SciCode | 28.0% | 40.0% |
| LCR | 0.0% | 63.7% |
| IFBench | 31.5% | 67.3% |
| TAU-bench v2 | — | 98.5% |
| TerminalBench Hard | — | 35.6% |
Key Takeaways
Step 3.7 Flash offers the best value at $0.20/1M,making it ideal for high-volume applications and cost-conscious projects.
Step 3.7 Flash has the strongest reasoning profile with a 43.7 reasoning score,combining the available reasoning-heavy benchmarks.
Step 3.7 Flash reaches a 39.6 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
Qwen3 32B (Non-reasoning)
- General-purpose AI
- Versatile applications
Step 3.7 Flash
- Cost-sensitive applications
- High-volume processing
- Complex reasoning tasks
- Research & analysis
- Code generation
- Software development
