GPT-5.6 is an OpenAI model version reported in customer and industry accounts to power production agents and workflow automation: companies report using it to run multilingual voice and chat agents, to turn scattered company files into context for agents, and to shorten trade-validation workflows. Independent analysis cites a GPT-5.6 family model reaching 75% on the GPQA Diamond benchmark at an estimated cost of $0.0004 per question.
CURRENT SNAPSHOT4/5 DIMENSIONS WITH DATA
The dimensions that change the decision.
PRICING
Reported cost relative to GPT-4.1Ringg reported that using GPT-5.6 for agents costs about 90% less compared with GPT-4.1.
GPQA Diamond performance and per‑question cost (reported by Epoch AI)Epoch AI's analysis reports a GPT-5.6‑family model matched a prior 75% score on the GPQA Diamond (a PhD‑level science test) at about four hundredths of a cent per question.
CONTEXT WINDOW
Context / institutional memory capability (reported)V7 reports using GPT-5.6 to turn scattered company files into context that agents can use to complete complex, source‑linked work.
MODALITIES
Reported modalities / deployment contextsRingg reported using GPT-5.6 to power multilingual agents across voice, chat, WhatsApp, and web.
BENCHMARKS
Benchmark performance and estimated cost (reported example)Epoch AI reported that a GPT-5.6 family model scored 75% on the GPQA Diamond benchmark at an estimated cost of $0.0004 (four hundredths of a cent) per question.
V7 reports using GPT-5.6 to turn scattered company files into context that agents can use to complete complex, source‑linked work.
PRICING · GPQA Diamond performance and per‑question cost (reported by Epoch AI)DEVELOPER CLAIM
Epoch AI's analysis reports a GPT-5.6‑family model matched a prior 75% score on the GPQA Diamond (a PhD‑level science test) at about four hundredths of a cent per question.
Chatham Financial used GPT-5.6 to build technology and redesign workflows, reducing trade validation time from 30 minutes to under 4 minutes.
CAPABILITIES · Use for context-aware agents / institutional memoryDEVELOPER CLAIM
V7 used GPT-5.6 to convert scattered company files into context that agents can use to complete complex, source‑linked work.
BENCHMARKS · Benchmark performance and estimated cost (reported example)DEVELOPER CLAIM
Epoch AI reported that a GPT-5.6 family model scored 75% on the GPQA Diamond benchmark at an estimated cost of $0.0004 (four hundredths of a cent) per question.
WHAT CHANGED
Stored passport versions, without reconstructed history.
Passport updated7 facts
CONTEXT WINDOW · Context / institutional memory capability (reported)V7 reports using GPT-5.6 to turn scattered company files into context that agents can use to complete complex, source‑linked work.→V7 reports using GPT-5.6 to turn scattered company files into context that agents can use to complete complex, source‑linked work.
CAPABILITIES · Use for context-aware agents / institutional memory+ V7 used GPT-5.6 to convert scattered company files into context that agents can use to complete complex, source‑linked work.
PRICING · Reported cost comparison vs. GPT-4.1− Ringg reports GPT-5.6 gives about 90% lower cost versus GPT-4.1 for their agents.
PRICING · Reported cost relative to GPT-4.1+ Ringg reported that using GPT-5.6 for agents costs about 90% less compared with GPT-4.1.
BENCHMARKS · Benchmark performance and estimated cost (reported example)+ Epoch AI reported that a GPT-5.6 family model scored 75% on the GPQA Diamond benchmark at an estimated cost of $0.0004 (four hundredths of a cent) per question.
PRICING · GPQA Diamond performance and per‑question cost (reported by Epoch AI)Epoch AI's analysis reports a GPT-5.6‑family model matched a prior 75% score on the GPQA Diamond (a PhD‑level science test) at about four hundredths of a cent per question.→Epoch AI's analysis reports a GPT-5.6‑family model matched a prior 75% score on the GPQA Diamond (a PhD‑level science test) at about four hundredths of a cent per question.
MODALITIES · Supported modalities / interfaces (reported)− Ringg reports using GPT-5.6 to power multilingual agents across voice, chat, WhatsApp, and web.
MODALITIES · Reported modalities / deployment contexts+ Ringg reported using GPT-5.6 to power multilingual agents across voice, chat, WhatsApp, and web.
CAPABILITIES · Workflow speed / trade validation+ Chatham Financial used GPT-5.6 to build technology and redesign workflows, reducing trade validation time from 30 minutes to under 4 minutes.
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