Models & Pricing

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Choose two or three models, including exact thinking and fast versions. Copy the URL to share your selection.

ComparisonGPT-5.2 Fast
openai/gpt-5.2-low
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TypeChat—
Best forFast, low-cost replies and high-volume everyday tasks—
TokenRex price$1.75 in / $14.00 out per 1M tokens—
Cached input / 1M tokens$0.175 per 1M tokens—
Cache write / 1M tokensNo extra fee—
Cached outputNot offered · standard output rate applies—
Market price$1.75 in / $14.00 out per 1M tokens—
Context window (provider)400,000 tokens—
Input token limit (provider)Within the context window—
Maximum output128,000 tokens—
Knowledge cutoffAug 31, 2025—
Vendor input modalitiesNot verified—
Vendor output modalitiesNot verified—
TokenRex endpointsPOST /v1/chat/completions—
TokenRex inputText, Image/PDF content through the chat bridge—
TokenRex outputText—
Benchmark evidence1 source-linked results—
lineage-bench (overall, avg of lineage-8/16/32/64/128)
0.66accuracy (0-1)

gpt-5.2, reasoning.effort=low, lineage-bench (graph relationship reasoning), via OpenAI API (author states repeated directly, not only via OpenRouter). Community-reproduced micro-benchmark, not an OpenAI-published table; single independent tester, small forum post, not peer reviewed. Publisher excerpt: gpt-5.2 (low) | 0.660 | 1.000 | 0.975 | 0.800 | 0.400 | 0.125

OpenAI Developer Community forum · independent lineage-bench results by user sszymczy
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No overall score, winner or cost-versus-score frontier is calculated without comparable, attributable benchmark evidence. Different test configurations appear separately. Vendor capabilities are distinct from TokenRex API support.

— means no published value or no matching capability. Provider token limits are not tested gateway guarantees; TokenRex media controls and response formats are listed separately.

GPT-5.2 Fast

Sources and verification

Provider specifications describe the upstream model, not a guarantee of every feature through TokenRex. Prices come from the enabled catalog; benchmark results belong to the exact tested model.

Research notes (1)
  • Published provider limits; maximum-capacity requests have not been independently exercised through TokenRex. Thinking-level variants use the same provider model; reasoning and answer tokens share the output budget.