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ModelCap

Model decision surface

Compare AI models

Start with Muse Spark Open 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

Muse Spark Open vs GLM 5.3

Live dataset updated 10/15/2026, 6:39:42 PM UTC

Open 1200×630 evidence receipt
Factual comparison of Muse Spark Open and GLM 5.3
Field
ModelCap position#15#20
Index score79.678.4
EvidenceEstimatedpublisher-corpus-prior over 213 held-out anchors (22%); launch card against 5 resolved peers on 11 rows (78%); exceeds every named peer on 3 of 11 rows; optimism haircut 0 from cross-lab-probe; shrunk 1 up toward the measured corpusMeasured3 public benchmark observations across 3 boards
Input / 1M$1.25$0.11
Output / 1M$4.25$4.80
Pricing statusfreshfresh
Context1M1M
Providers434
Weight accessGated accessRestricted license

Decision facts

  • Muse Spark Open is #15; GLM 5.3 is #20 on the same current language board.
  • Index scores are 79.6 for Muse Spark Open and 78.4 for GLM 5.3. Their published uncertainty intervals overlap, so the rank difference alone does not establish a reliable capability advantage for your workload.
  • Evidence differs: Muse Spark Open is Estimated; GLM 5.3 is Measured.
  • Listed output price per 1M tokens is $4.25 for Muse Spark Open and $4.80 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 $4.63 for Muse Spark Open versus $2.62 for GLM 5.3. GLM 5.3 costs 43.4% 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 1,048,576 tokens for Muse Spark Open and 1,048,576 for GLM 5.3.
  • Weight access differs: Muse Spark Open is gated; GLM 5.3 is restricted.
  • ModelCap currently lists 4 providers for Muse Spark Open and 34 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.