Model decision surface
Compare AI models
Start with GPT-5.5 and Qwen3.8 Max (0902), or choose any two current ranked language models. Compare capability evidence, price, context, provider availability, and weight access without pretending one field decides every use case.
Current public data
GPT-5.5 vs Qwen3.8 Max (0902)
Live dataset updated 9/15/2026, 9:19:37 PM UTC
Open 1200×630 evidence receipt| Field | GPT-5.5 OpenAI | |
|---|---|---|
| ModelCap position | #10 | #5 |
| Index score | 79.3 | 83.2 |
| Evidence | Measured7 public benchmark observations across 7 boards | Measured1 public benchmark observation across 1 board |
| Input / 1M | $5.00 | $2.00 |
| Output / 1M | $30.00 | $6.00 |
| Pricing status | fresh | fresh |
| Context | 1M | 1M |
| Providers | 3 | 1 |
| Weight access | API only | API only |
Decision facts
- GPT-5.5 is #10; Qwen3.8 Max (0902) is #5 on the same current language board.
- Index scores are 79.3 for GPT-5.5 and 83.2 for Qwen3.8 Max (0902). Their published uncertainty intervals overlap, so the rank difference alone does not establish a reliable capability advantage for your workload.
- Both positions use Measured evidence.
- Listed output price per 1M tokens is $30.00 for GPT-5.5 and $6.00 for Qwen3.8 Max (0902). For 1,000 requests with 2,000 input and 500 output tokens each (2M input + 0.5M output), the listed-rate estimate is $25.00 for GPT-5.5 versus $7.00 for Qwen3.8 Max (0902). Qwen3.8 Max (0902) costs 72.0% less in this scenario. This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the selected endpoint before budgeting.
- Published context is 1,050,000 tokens for GPT-5.5 and 1,000,000 for Qwen3.8 Max (0902).
- ModelCap currently lists 3 providers for GPT-5.5 and 1 for Qwen3.8 Max (0902).
These are separate published fields, not a synthetic winner. ModelCap does not collapse price, access, context, and capability evidence into a hidden recommendation score.
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Each comparison page is a permanent, shareable URL with the same live figures as this tool: ModelCap Index position, API pricing, context window, provider count, weight access and every shared benchmark board.