| Signal | GPT-5.2 Chat | Delta | Qwen Plus 0728 (thinking) |
|---|---|---|---|
Capabilities | 83 | +17 | |
Benchmarks | 78 | +78 | |
Pricing | 14 | +13 | |
Context window size | 81 | -14 | |
Recency | 100 | +4 | |
Output Capacity | 70 | -5 | |
| Overall Result | 4 wins | of 6 | 2 wins |
12
days higher
3
days
15
days higher
OpenAI
Alibaba
Qwen Plus 0728 (thinking) saves you $810.00/month
That's $9720.00/year compared to GPT-5.2 Chat at your current usage level of 100K calls/month.
| Metric | GPT-5.2 Chat | Qwen Plus 0728 (thinking) | Winner |
|---|---|---|---|
| Overall Score | 83 | 82 | GPT-5.2 Chat |
| Rank | #59 | #62 | GPT-5.2 Chat |
| Quality Rank | #59 | #62 | GPT-5.2 Chat |
| Adoption Rank | #59 | #62 | GPT-5.2 Chat |
| Parameters | -- | -- | -- |
| Context Window | 128K | 1000K | Qwen Plus 0728 (thinking) |
| Pricing | $1.75/$14.00/M | $0.26/$0.78/M | -- |
| Signal Scores | |||
| Capabilities | 83 | 67 | GPT-5.2 Chat |
| Benchmarks | 78 | -- | GPT-5.2 Chat |
| Pricing | 14 | 1 | GPT-5.2 Chat |
| Context window size | 81 | 95 | Qwen Plus 0728 (thinking) |
| Recency | 100 | 96 | GPT-5.2 Chat |
| Output Capacity | 70 | 75 | Qwen Plus 0728 (thinking) |
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 83/100 (rank #59), placing it in the top 80% of all 290 models tracked.
Scores 82/100 (rank #62), placing it in the top 79% 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.
Qwen Plus 0728 (thinking) offers 93% better value per quality point. At 1M tokens/day, you'd spend $15.60/month with Qwen Plus 0728 (thinking) vs $236.25/month with GPT-5.2 Chat - a $220.65 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 Plus 0728 (thinking) also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (1000K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.78/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (83/100) 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
GPT-5.2 Chat and Qwen Plus 0728 (thinking) are extremely close in overall performance (only 0.5 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
GPT-5.2 Chat
Marginally better benchmark scores; both are excellent
Best for Cost
Qwen Plus 0728 (thinking)
93% lower pricing; better value at scale
Best for Reliability
GPT-5.2 Chat
Higher uptime and faster response speeds
Best for Prototyping
GPT-5.2 Chat
Stronger community support and better developer experience
Best for Production
GPT-5.2 Chat
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-5.2 Chat | Qwen Plus 0728 (thinking) |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Searchdiffers | ||
| Image Output |
OpenAI
Alibaba
Qwen Plus 0728 (thinking) saves you $18.55/month
That's 93% cheaper than GPT-5.2 Chat 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 | GPT-5.2 Chat | Qwen Plus 0728 (thinking) |
|---|---|---|
| Context Window | 128K | 1M |
| Max Output Tokens | 16,384 | 32,768 |
| Open Source | No | No |
| Created | Dec 10, 2025 | Sep 8, 2025 |
GPT-5.2 Chat scores 83/100 (rank #59) compared to Qwen Plus 0728 (thinking)'s 82/100 (rank #62), giving it a 1-point advantage. GPT-5.2 Chat is the stronger overall choice, though Qwen Plus 0728 (thinking) may excel in specific areas like cost efficiency.
GPT-5.2 Chat is ranked #59 and Qwen Plus 0728 (thinking) is ranked #62 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 Plus 0728 (thinking) is cheaper at $0.78/M output tokens vs GPT-5.2 Chat's $14.00/M output tokens - 17.9x more expensive. Input token pricing: GPT-5.2 Chat at $1.75/M vs Qwen Plus 0728 (thinking) at $0.26/M.
Qwen Plus 0728 (thinking) has a larger context window of 1,000,000 tokens compared to GPT-5.2 Chat's 128,000 tokens. A larger context window means the model can process longer documents and conversations.