| Signal | Qwen3 30B A3B Thinking 2507 | Delta | R1 |
|---|---|---|---|
Capabilities | 67 | +17 | |
Pricing | 0 | -2 | |
Context window size | 72 | -5 | |
Recency | 97 | +40 | |
Output Capacity | 20 | -50 | |
Benchmarks | 0 | -80 | |
| Overall Result | 2 wins | of 6 | 4 wins |
13
days ranked higher
1
days
16
days ranked higher
Alibaba
DeepSeek
Qwen3 30B A3B Thinking 2507 saves you $172.90/month
That's $2074.80/year compared to R1 at your current usage level of 100K calls/month.
| Metric | Qwen3 30B A3B Thinking 2507 | R1 | Winner |
|---|---|---|---|
| Overall Score | 67 | 66 | Qwen3 30B A3B Thinking 2507 |
| Rank | #157 | #159 | Qwen3 30B A3B Thinking 2507 |
| Quality Rank | #157 | #159 | Qwen3 30B A3B Thinking 2507 |
| Adoption Rank | #157 | #159 | Qwen3 30B A3B Thinking 2507 |
| Parameters | 30B | -- | -- |
| Context Window | 33K | 64K | R1 |
| Pricing | $0.05/$0.34/M | $0.70/$2.50/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 50 | Qwen3 30B A3B Thinking 2507 |
| Pricing | 0 | 3 | R1 |
| Context window size | 72 | 76 | R1 |
| Recency | 97 | 57 | Qwen3 30B A3B Thinking 2507 |
| Output Capacity | 20 | 70 | R1 |
| Benchmarks | -- | 80 | R1 |
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 67/100 (rank #157), placing it in the top 46% of all 290 models tracked.
Scores 66/100 (rank #159), placing it in the top 46% of all 290 models tracked.
With only a 0-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.
Qwen3 30B A3B Thinking 2507 offers 88% better value per quality point. At 1M tokens/day, you'd spend $5.86/month with Qwen3 30B A3B Thinking 2507 vs $48.00/month with R1 — a $42.13 monthly difference.
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 Thinking 2507 also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (64K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.34/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (67/100) correlates with better nuance, coherence, and style in long-form content
Qwen3 30B A3B Thinking 2507 and R1 are extremely close in overall performance (only 0.3999999999999915 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
Qwen3 30B A3B Thinking 2507
Marginally better benchmark scores; both are excellent
Best for Cost
Qwen3 30B A3B Thinking 2507
88% lower pricing; better value at scale
Best for Reliability
Qwen3 30B A3B Thinking 2507
Higher uptime and faster response speeds
Best for Prototyping
Qwen3 30B A3B Thinking 2507
Stronger community support and better developer experience
Best for Production
Qwen3 30B A3B Thinking 2507
Wider enterprise adoption and proven at scale
by Alibaba
| Capability | Qwen3 30B A3B Thinking 2507 | R1 |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Alibaba
DeepSeek
Qwen3 30B A3B Thinking 2507 saves you $3.76/month
That's 88% cheaper than R1 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 Thinking 2507 | R1 |
|---|---|---|
| Context Window | 33K | 64K |
| Max Output Tokens | -- | 16,000 |
| Open Source | Yes | Yes |
| Created | Aug 28, 2025 | Jan 20, 2025 |
Qwen3 30B A3B Thinking 2507 scores 67/100 (rank #157) compared to R1's 66/100 (rank #159), giving it a 0-point advantage. Qwen3 30B A3B Thinking 2507 is the stronger overall choice, though R1 may excel in specific areas like certain benchmarks.
Qwen3 30B A3B Thinking 2507 is ranked #157 and R1 is ranked #159 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 Thinking 2507 is cheaper at $0.34/M output tokens vs R1's $2.50/M output tokens — 7.4x more expensive. Input token pricing: Qwen3 30B A3B Thinking 2507 at $0.05/M vs R1 at $0.70/M.
R1 has a larger context window of 64,000 tokens compared to Qwen3 30B A3B Thinking 2507's 32,768 tokens. A larger context window means the model can process longer documents and conversations.