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ModelCap

Model decision surface

Compare AI models

Start with MiMo-V2.5-Pro and GLM 5.3, 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

MiMo-V2.5-Pro vs GLM 5.3

Live dataset updated 9/9/2026, 8:46:14 PM UTC

Open 1200×630 evidence receipt
Factual comparison of MiMo-V2.5-Pro and GLM 5.3
Field
ModelCap position#21#8
Index score72.882.1
EvidenceMeasured5 public benchmark observations across 5 boardsMeasured4 public benchmark observations across 4 boards
Input / 1M$0.435$1.40
Output / 1M$0.87$4.40
Pricing statusfreshfresh
Context1M1.3M
Providers727
Weight accessOpen weightsRestricted license

Decision facts

  • MiMo-V2.5-Pro is #21; GLM 5.3 is #8 on the same current language board.
  • Index scores are 72.8 for MiMo-V2.5-Pro and 82.1 for GLM 5.3. 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 $0.87 for MiMo-V2.5-Pro and $4.40 for GLM 5.3. For 1,000 requests with 2,000 input and 500 output tokens each (2M input + 0.5M output), the listed-rate estimate is $1.30 for MiMo-V2.5-Pro versus $5.00 for GLM 5.3. MiMo-V2.5-Pro costs 73.9% 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 1,050,000 tokens for MiMo-V2.5-Pro and 1,310,720 for GLM 5.3.
  • Weight access differs: MiMo-V2.5-Pro is open; GLM 5.3 is restricted.
  • ModelCap currently lists 7 providers for MiMo-V2.5-Pro and 27 for GLM 5.3.

These are separate published fields, not a synthetic winner. ModelCap does not collapse price, access, context, and capability evidence into a hidden recommendation score.

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.