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Start with Gemini 4 Argon 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.

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Current public data

Gemini 4 Argon vs GLM 5.3

Live dataset updated 10/13/2026, 6:04:47 PM UTC

Open 1200×630 evidence receipt

Factual comparison of Gemini 4 Argon and GLM 5.3
Field	Gemini 4 Argon Google	GLM 5.3 Z.ai
ModelCap position	#33	#18
Index score	73.0	79.7
Evidence	Estimated1 reported rows against measured corpus ladders (72%); publisher-corpus-prior over 211 held-out anchors (28%); shrunk 3.7 toward the measured corpus	Measured3 public benchmark observations across 3 boards
Input / 1M	$2.00	$0.079
Output / 1M	$10.00	$4.80
Pricing status	fresh	fresh
Context	1M	1M
Providers	2	33
Weight access	No linked weights	Restricted license

Decision facts

Gemini 4 Argon is #33; GLM 5.3 is #18 on the same current language board.
Index scores are 73.0 for Gemini 4 Argon and 79.7 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: Gemini 4 Argon is Estimated; GLM 5.3 is Measured.
Listed output price per 1M tokens is $10.00 for Gemini 4 Argon 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 $9.00 for Gemini 4 Argon versus $2.56 for GLM 5.3. GLM 5.3 costs 71.6% 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 Gemini 4 Argon and 1,048,576 for GLM 5.3.
Weight access differs: Gemini 4 Argon is none; GLM 5.3 is restricted.
ModelCap currently lists 2 providers for Gemini 4 Argon and 33 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.

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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.