| Signal | Qwen VL Max | Delta | R1 |
|---|---|---|---|
Capabilities | 67 | +17 | |
Pricing | 2 | 0 | |
Context window size | 81 | +5 | |
Recency | 57 | +2 | |
Output Capacity | 75 | +5 | |
Benchmarks | 0 | -77 | |
| Overall Result | 4 wins | of 6 | 2 wins |
10
days ranked higher
0
days
20
days ranked higher
Alibaba
DeepSeek
Qwen VL Max saves you $39.00/month
That's $468.00/year compared to R1 at your current usage level of 100K calls/month.
| Metric | Qwen VL Max | R1 | Winner |
|---|---|---|---|
| Overall Score | 68 | 68 | R1 |
| Rank | #167 | #166 | R1 |
| Quality Rank | #167 | #166 | R1 |
| Adoption Rank | #167 | #166 | R1 |
| Parameters | -- | -- | -- |
| Context Window | 131K | 64K | Qwen VL Max |
| Pricing | $0.52/$2.08/M | $0.70/$2.50/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 50 | Qwen VL Max |
| Pricing | 2 | 3 | R1 |
| Context window size | 81 | 76 | Qwen VL Max |
| Recency | 57 | 55 | Qwen VL Max |
| Output Capacity | 75 | 70 | Qwen VL Max |
| Benchmarks | -- | 77 | 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 68/100 (rank #167), placing it in the top 43% of all 290 models tracked.
Scores 68/100 (rank #166), placing it in the top 43% 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.
Qwen VL Max offers 19% better value per quality point. At 1M tokens/day, you'd spend $39.00/month with Qwen VL Max vs $48.00/month with R1 - a $9.00 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. Qwen VL Max also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (131K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($2.08/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (68/100) correlates with better nuance, coherence, and style in long-form content
Image understanding & OCR
Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly
Qwen VL Max and R1 are extremely close in overall performance (only 0.20000000000000284 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
Qwen VL Max
Marginally better benchmark scores; both are excellent
Best for Cost
Qwen VL Max
19% lower pricing; better value at scale
Best for Reliability
Qwen VL Max
Higher uptime and faster response speeds
Best for Prototyping
Qwen VL Max
Stronger community support and better developer experience
Best for Production
Qwen VL Max
Wider enterprise adoption and proven at scale
by Alibaba
| Capability | Qwen VL Max | R1 |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
Alibaba
DeepSeek
Qwen VL Max saves you $0.8280/month
That's 19% 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 | Qwen VL Max | R1 |
|---|---|---|
| Context Window | 131K | 64K |
| Max Output Tokens | 32,768 | 16,000 |
| Open Source | No | Yes |
| Created | Feb 1, 2025 | Jan 20, 2025 |
R1 scores 68/100 (rank #166) compared to Qwen VL Max's 68/100 (rank #167), giving it a 0-point advantage. R1 is the stronger overall choice, though Qwen VL Max may excel in specific areas like cost efficiency.
Qwen VL Max is ranked #167 and R1 is ranked #166 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.
Qwen VL Max is cheaper at $2.08/M output tokens vs R1's $2.50/M output tokens - 1.2x more expensive. Input token pricing: Qwen VL Max at $0.52/M vs R1 at $0.70/M.
Qwen VL Max has a larger context window of 131,072 tokens compared to R1's 64,000 tokens. A larger context window means the model can process longer documents and conversations.