Model decision surface
Compare AI models
Start with LongCat 2.0 and Grok 4.20 Multi-Agent, 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
LongCat 2.0 vs Grok 4.20 Multi-Agent
Live dataset updated 9/9/2026, 8:46:14 PM UTC
Open 1200×630 evidence receipt| Field | LongCat 2.0 Meituan | |
|---|---|---|
| ModelCap position | #10 | #14 |
| Index score | 79.0 | 77.5 |
| Evidence | 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 | Measured2 public benchmark observations across 2 boards |
| Input / 1M | $0.30 | $1.25 |
| Output / 1M | $1.20 | $2.50 |
| Pricing status | fresh | fresh |
| Context | 1M | 2M |
| Providers | 1 | 1 |
| Weight access | Open weights | API only |
Decision facts
- LongCat 2.0 is #10; Grok 4.20 Multi-Agent is #14 on the same current language board.
- Index scores are 79.0 for LongCat 2.0 and 77.5 for Grok 4.20 Multi-Agent. Their published uncertainty intervals overlap, so the rank difference alone does not establish a reliable capability advantage for your workload.
- Evidence differs: LongCat 2.0 is Estimated; Grok 4.20 Multi-Agent is Measured.
- Listed output price per 1M tokens is $1.20 for LongCat 2.0 and $2.50 for Grok 4.20 Multi-Agent. For 1,000 requests with 2,000 input and 500 output tokens each (2M input + 0.5M output), the listed-rate estimate is $1.20 for LongCat 2.0 versus $3.75 for Grok 4.20 Multi-Agent. LongCat 2.0 costs 68.0% 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 1,048,756 tokens for LongCat 2.0 and 2,000,000 for Grok 4.20 Multi-Agent.
- Weight access differs: LongCat 2.0 is open; Grok 4.20 Multi-Agent is none.
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.