| Signal | Qwen3 30B A3B Instruct 2507 | Delta | Step 3.5 Flash |
|---|---|---|---|
Capabilities | 50 | -17 | |
Pricing | 0 | -- | |
Context window size | 86 | -- | |
Recency | 88 | -12 | |
Output Capacity | 90 | +10 | |
Benchmarks | 0 | -66 | |
| Overall Result | 1 wins | of 6 | 3 wins |
6
days higher
3
days
21
days higher
Alibaba
StepFun
Qwen3 30B A3B Instruct 2507 saves you $1.00/month
That's $12.00/year compared to Step 3.5 Flash at your current usage level of 100K calls/month.
| Metric | Qwen3 30B A3B Instruct 2507 | Step 3.5 Flash | Winner |
|---|---|---|---|
| Overall Score | 75 | 75 | Step 3.5 Flash |
| Rank | #115 | #110 | Step 3.5 Flash |
| Quality Rank | #115 | #110 | Step 3.5 Flash |
| Adoption Rank | #115 | #110 | Step 3.5 Flash |
| Parameters | 30B | -- | -- |
| Context Window | 262K | 262K | -- |
| Pricing | $0.09/$0.30/M | $0.10/$0.30/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 67 | Step 3.5 Flash |
| Pricing | 0 | 0 | Qwen3 30B A3B Instruct 2507 |
| Context window size | 86 | 86 | Qwen3 30B A3B Instruct 2507 |
| Recency | 88 | 100 | Step 3.5 Flash |
| Output Capacity | 90 | 80 | Qwen3 30B A3B Instruct 2507 |
| Benchmarks | -- | 66 | Step 3.5 Flash |
Our composite score (0–100) combines six weighted signals: benchmark performance (25%), pricing efficiency (25%), context window size (15%), model recency (15%), output capacity (10%), and capability versatility (10%). Here's what the scores mean for these two models:
Scores 75/100 (rank #115), placing it in the top 61% of all 290 models tracked.
Scores 75/100 (rank #110), placing it in the top 62% of all 290 models tracked.
With only a 1-point gap, these models are in the same performance tier. The practical difference in output quality is minimal - your choice should depend on pricing, latency requirements, and specific feature needs.
Both models are priced similarly, so the decision comes down to quality and features rather than cost.
Both models have comparable response speeds. For most applications, the latency difference is negligible.
When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.
Code generation & review
Higher benchmark score (0/100) indicates stronger performance on coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Faster response time (speed score 0/100) is critical for user-facing chat. Qwen3 30B A3B Instruct 2507 also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (262K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.30/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (75/100) correlates with better nuance, coherence, and style in long-form content
Qwen3 30B A3B Instruct 2507 and Step 3.5 Flash are extremely close in overall performance (only 0.8000000000000114 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
Qwen3 30B A3B Instruct 2507
Marginally better benchmark scores; both are excellent
Best for Cost
Qwen3 30B A3B Instruct 2507
2% lower pricing; better value at scale
Best for Reliability
Qwen3 30B A3B Instruct 2507
Higher uptime and faster response speeds
Best for Prototyping
Qwen3 30B A3B Instruct 2507
Stronger community support and better developer experience
Best for Production
Qwen3 30B A3B Instruct 2507
Wider enterprise adoption and proven at scale
by Alibaba
| Capability | Qwen3 30B A3B Instruct 2507 | Step 3.5 Flash |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
Alibaba
StepFun
Qwen3 30B A3B Instruct 2507 saves you $0.0180/month
That's 3% cheaper than Step 3.5 Flash at 1,000 tokens/request and 100 requests/day.
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | Qwen3 30B A3B Instruct 2507 | Step 3.5 Flash |
|---|---|---|
| Context Window | 262K | 262K |
| Max Output Tokens | 262,144 | 65,536 |
| Open Source | Yes | Yes |
| Created | Jul 29, 2025 | Jan 29, 2026 |
Step 3.5 Flash scores 75/100 (rank #110) compared to Qwen3 30B A3B Instruct 2507's 75/100 (rank #115), giving it a 1-point advantage. Step 3.5 Flash is the stronger overall choice, though Qwen3 30B A3B Instruct 2507 may excel in specific areas like certain benchmarks.
Qwen3 30B A3B Instruct 2507 is ranked #115 and Step 3.5 Flash is ranked #110 out of 290+ AI models. Rankings use a composite score combining benchmark performance (25%), pricing (25%), context window (15%), recency (15%), output capacity (10%), and versatility (10%). Scores update hourly.
Qwen3 30B A3B Instruct 2507 is cheaper at $0.30/M output tokens vs Step 3.5 Flash's $0.30/M output tokens - 1.0x more expensive. Input token pricing: Qwen3 30B A3B Instruct 2507 at $0.09/M vs Step 3.5 Flash at $0.10/M.
Qwen3 30B A3B Instruct 2507 has a larger context window of 262,144 tokens compared to Step 3.5 Flash's 262,144 tokens. A larger context window means the model can process longer documents and conversations.