Model decision surface
Compare AI models
Start with Kimi K2.7 Code and GPT-5.5 Pro, 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
Kimi K2.7 Code vs GPT-5.5 Pro
Live dataset updated 9/9/2026, 8:46:14 PM UTC
Open 1200×630 evidence receipt| Field | Kimi K2.7 Code Moonshot AI | GPT-5.5 Pro OpenAI |
|---|---|---|
| ModelCap position | #47 | #49 |
| Index score | 59.5 | 59.1 |
| Evidence | Measured2 public benchmark observations across 2 boards | Measuredpublisher-corpus-prior over 182 held-out anchors (61%); 1 specialist-board observation at 2.1% support (40%); shrunk 14.6 toward the measured corpus |
| Input / 1M | $0.71 | $30.00 |
| Output / 1M | $3.50 | $180 |
| Pricing status | fresh | fresh |
| Context | 262K | 1M |
| Providers | 14 | 1 |
| Weight access | Restricted license | API only |
Decision facts
- Kimi K2.7 Code is #47; GPT-5.5 Pro is #49 on the same current language board.
- Index scores are 59.5 for Kimi K2.7 Code and 59.1 for GPT-5.5 Pro. 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 $3.50 for Kimi K2.7 Code and $180.00 for GPT-5.5 Pro. For 1,000 requests with 2,000 input and 500 output tokens each (2M input + 0.5M output), the listed-rate estimate is $3.17 for Kimi K2.7 Code versus $150.00 for GPT-5.5 Pro. Kimi K2.7 Code costs 97.9% 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 262,144 tokens for Kimi K2.7 Code and 1,050,000 for GPT-5.5 Pro.
- Weight access differs: Kimi K2.7 Code is restricted; GPT-5.5 Pro is none.
- ModelCap currently lists 14 providers for Kimi K2.7 Code and 1 for GPT-5.5 Pro.
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.