Model decision surface
Compare AI models
Start with Claude Opus 5 and LongCat 2.0, 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
Claude Opus 5 vs LongCat 2.0
Live dataset updated 9/9/2026, 8:46:14 PM UTC
Open 1200×630 evidence receipt| Field | Claude Opus 5 Anthropic | LongCat 2.0 Meituan |
|---|---|---|
| ModelCap position | #4 | #10 |
| Index score | 86.2 | 79.0 |
| Evidence | Measured6 public benchmark observations across 6 boards | Estimatedglobal-corpus-prior over 182 held-out anchors (7%); launch card against 4 resolved peers on 6 rows (93%); no cross-lab optimism probe available; shrunk 2 toward the measured corpus |
| Input / 1M | $5.00 | $0.30 |
| Output / 1M | $25.00 | $1.20 |
| Pricing status | fresh | fresh |
| Context | 1M | 1M |
| Providers | 5 | 1 |
| Weight access | API only | Open weights |
Decision facts
- Claude Opus 5 is #4; LongCat 2.0 is #10 on the same current language board.
- Index scores are 86.2 for Claude Opus 5 and 79.0 for LongCat 2.0. Their published uncertainty intervals overlap, so the rank difference alone does not establish a reliable capability advantage for your workload.
- Evidence differs: Claude Opus 5 is Measured; LongCat 2.0 is Estimated.
- Listed output price per 1M tokens is $25.00 for Claude Opus 5 and $1.20 for LongCat 2.0. For 1,000 requests with 2,000 input and 500 output tokens each (2M input + 0.5M output), the listed-rate estimate is $22.50 for Claude Opus 5 versus $1.20 for LongCat 2.0. LongCat 2.0 costs 94.7% 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 1,000,000 tokens for Claude Opus 5 and 1,048,756 for LongCat 2.0.
- Weight access differs: Claude Opus 5 is none; LongCat 2.0 is open.
- ModelCap currently lists 5 providers for Claude Opus 5 and 1 for LongCat 2.0.
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.