| Signal | Qwen-Max | Delta | Qwen2.5 VL 72B Instruct |
|---|---|---|---|
Capabilities | 50 | -- | |
Pricing | 4 | +3 | |
Context window size | 72 | -- | |
Recency | 55 | -- | |
Output Capacity | 65 | -10 | |
| Overall Result | 1 wins | of 5 | 1 wins |
10
days higher
1
days
19
days higher
Alibaba
Alibaba
Qwen2.5 VL 72B Instruct saves you $192.00/month
That's $2304.00/year compared to Qwen-Max at your current usage level of 100K calls/month.
| Metric | Qwen-Max | Qwen2.5 VL 72B Instruct | Winner |
|---|---|---|---|
| Overall Score | 40 | 40 | -- |
| Rank | #273 | #271 | Qwen2.5 VL 72B Instruct |
| Quality Rank | #273 | #271 | Qwen2.5 VL 72B Instruct |
| Adoption Rank | #273 | #271 | Qwen2.5 VL 72B Instruct |
| Parameters | -- | 72B | -- |
| Context Window | 33K | 33K | -- |
| Pricing | $1.04/$4.16/M | $0.80/$0.80/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 50 | Qwen-Max |
| Pricing | 4 | 1 | Qwen-Max |
| Context window size | 72 | 72 | Qwen-Max |
| Recency | 55 | 55 | Qwen-Max |
| Output Capacity | 65 | 75 | Qwen2.5 VL 72B Instruct |
Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Here's what the scores mean for these two models:
Scores 40/100 (rank #273), placing it in the top 6% of all 290 models tracked.
Scores 40/100 (rank #271), placing it in the top 7% 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.
Qwen2.5 VL 72B Instruct offers 69% better value per quality point. At 1M tokens/day, you'd spend $24.00/month with Qwen2.5 VL 72B Instruct vs $78.00/month with Qwen-Max - a $54.00 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. Qwen2.5 VL 72B Instruct also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (33K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.80/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (40/100) 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-Max and Qwen2.5 VL 72B Instruct are extremely close in overall performance (only 0 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
Qwen-Max
Marginally better benchmark scores; both are excellent
Best for Cost
Qwen2.5 VL 72B Instruct
69% lower pricing; better value at scale
Best for Reliability
Qwen-Max
Higher uptime and faster response speeds
Best for Prototyping
Qwen-Max
Stronger community support and better developer experience
Best for Production
Qwen-Max
Wider enterprise adoption and proven at scale
by Alibaba
| Capability | Qwen-Max | Qwen2.5 VL 72B Instruct |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Alibaba
Alibaba
Qwen2.5 VL 72B Instruct saves you $4.46/month
That's 65% cheaper than Qwen-Max 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-Max | Qwen2.5 VL 72B Instruct |
|---|---|---|
| Context Window | 33K | 33K |
| Max Output Tokens | 8,192 | 32,768 |
| Open Source | No | Yes |
| Created | Feb 1, 2025 | Feb 1, 2025 |
Both Qwen-Max and Qwen2.5 VL 72B Instruct score 40/100, making them extremely close competitors. Choose based on pricing, provider ecosystem, or specific capability requirements.
Qwen-Max is ranked #273 and Qwen2.5 VL 72B Instruct is ranked #271 out of 290+ AI models. Rankings use a composite score combining benchmark performance (90%) from MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations, with capabilities and context window as tiebreakers (10%). Scores update hourly.
Qwen2.5 VL 72B Instruct is cheaper at $0.80/M output tokens vs Qwen-Max 's $4.16/M output tokens - 5.2x more expensive. Input token pricing: Qwen-Max at $1.04/M vs Qwen2.5 VL 72B Instruct at $0.80/M.
Qwen-Max has a larger context window of 32,768 tokens compared to Qwen2.5 VL 72B Instruct's 32,768 tokens. A larger context window means the model can process longer documents and conversations.