Model decision surface
Compare AI models
Start with Mercury 2.5 and GPT-4o-mini, 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
Mercury 2.5 vs GPT-4o-mini
Live dataset updated 9/15/2026, 8:34:26 PM UTC
Open 1200×630 evidence receipt| Field | Mercury 2.5 Inception Labs | GPT-4o-mini OpenAI |
|---|---|---|
| ModelCap position | #128 | #131 |
| Index score | 37.3 | 35.9 |
| Evidence | Estimatedglobal-corpus-prior over 193 held-out anchors (23%); opens from measured predecessor inception/mercury-2 (77%); shrunk 4.4 up toward the measured corpus | Measuredpublisher-corpus-prior over 193 held-out anchors (61%); 1 specialist-board observation at 2.1% support (39%); shrunk 22.3 up toward the measured corpus |
| Input / 1M | $0.04 | $0.15 |
| Output / 1M | $0.15 | $0.60 |
| Pricing status | fresh | fresh |
| Context | 260K | 128K |
| Providers | 1 | 2 |
| Weight access | API only | API only |
Decision facts
- Mercury 2.5 is #128; GPT-4o-mini is #131 on the same current language board.
- Index scores are 37.3 for Mercury 2.5 and 35.9 for GPT-4o-mini. Their published uncertainty intervals overlap, so the rank difference alone does not establish a reliable capability advantage for your workload.
- Evidence differs: Mercury 2.5 is Estimated; GPT-4o-mini is Measured.
- Listed output price per 1M tokens is $0.15 for Mercury 2.5 and $0.60 for GPT-4o-mini. For 1,000 requests with 2,000 input and 500 output tokens each (2M input + 0.5M output), the listed-rate estimate is $0.15 for Mercury 2.5 versus $0.60 for GPT-4o-mini. Mercury 2.5 costs 74.2% 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 260,000 tokens for Mercury 2.5 and 128,000 for GPT-4o-mini.
- ModelCap currently lists 1 providers for Mercury 2.5 and 2 for GPT-4o-mini.
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.