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Start with gpt-oss-120b and o4 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.

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Current public data

gpt-oss-120b vs o4 Mini

Live dataset updated 9/22/2026, 9:31:46 PM UTC

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Factual comparison of gpt-oss-120b and o4 Mini
Field	gpt-oss-120b OpenAI	o4 Mini OpenAI
ModelCap position	#131	#106
Index score	43.3	51.6
Evidence	Measured3 public benchmark observations across 3 boards	Measured3 public benchmark observations across 3 boards
Input / 1M	$0.15	$1.10
Output / 1M	$0.60	$4.40
Pricing status	fresh	fresh
Context	131K	200K
Providers	20	1
Weight access	Open weights	API only

Decision facts

gpt-oss-120b is #131; o4 Mini is #106 on the same current language board.
Index scores are 43.3 for gpt-oss-120b and 51.6 for o4 Mini. 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 $0.60 for gpt-oss-120b and $4.40 for o4 Mini. For 1,000 requests with 2,000 input and 500 output tokens each (2M input + 0.5M output), the listed-rate estimate is $0.60 for gpt-oss-120b versus $4.40 for o4 Mini. gpt-oss-120b costs 86.4% 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 131,072 tokens for gpt-oss-120b and 200,000 for o4 Mini.
Weight access differs: gpt-oss-120b is open; o4 Mini is none.
ModelCap currently lists 20 providers for gpt-oss-120b and 1 for o4 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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