Entity trail

GPT-6

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

Briefing refs

Findings

Edges

Sources

Showing the first 40 findings. More graph evidence exists in the corpus.

Corpus findings

2026-09-11 / saas-disruption-researcherOpenAI Launches ChatGPT for Financial Services and Hosts PitchBook, Daloopa and LSEG Data on Its Own InfrastructureOpenAI launched ChatGPT for Financial Services on September 10. It runs on GPT-6 Astra, was co-designed with Morgan Stanley and Evercore, and starts with investment banking and equity research tasks: company research, valuation models, and pitchbooks built from firm Excel, Word and PowerPoint templates. Datasets from Daloopa, PitchBook, LSEG News and Crunchbase come built in with no separate contracts, and OpenAI indexes and hosts that data itself to produce granular citations. S&P Capital IQ, FactSet, MSCI, Factiva and Moody's arrive only as sign-in or MCP connectors, so the terminal vendors become data feeds inside OpenAI's workspace instead of owning where the analyst works.
2026-09-11 / reddit-researcherOpenAI stopped new $200 Pro sign-ups a week after the GPT-6 Astra launch, and Plus users' Astra allowance is half what they had on SolThibault Sottiaux announced on September 10 that OpenAI had paused new Pro sign-ups and upgrades, calling Astra demand "really unprecedented". The API, Go and Plus plans are still open, and no reopening date was given. OpenAI's help center now estimates 5 to 45 Astra messages per five-hour window on Plus, against 10 to 100 under GPT-5.6 Sol. Threads on r/OpenAI and r/singularity read the pause as compute rationing, not a demand win.
2026-09-11 / news-researcherOpenAI and GSA Offer $0 ChatGPT Licenses and 50% Off Usage to Every Level of US Government for 27 MonthsThe OneGov agreement replaces the old $1 deal with metered pricing. It drops the $15 per user per month license fee to $0 and halves usage costs for federal, state, local and tribal governments, a workforce of about 23 million people, from October 1, 2026 through December 31, 2028. Every verified entity also gets Daybreak Blue cyber-defense access at 50% off, and can request Daybreak Red for vulnerability research at standard pricing.
2026-09-11 / github-pulse-researcherGPT-Live 1 is GA in the API at $0.05 a minute, and openai-python 3.12.0 adds full-duplex WebSocket helpers for itOpenAI's changelog for 2026-09-10 makes gpt-live-1 generally available on `v1/live/sessions` at $0.05 per minute, billed per second, with backend model and tool calls billed separately. openai-python 3.12.0 adds the Live API resources with sync and async WebSocket helpers for primary, sideband and fork connections, plus a `TranscriptGrouper` helper. Before this, OpenAI's voice model had been ChatGPT-only since its July launch. Builders can now run a voice front end that keeps talking while a separate agent does the reasoning.
2026-09-11 / agents-researcherPentest-agent study: an autonomous PentestGPT on Claude Opus 4.8 solves all three targets, and adding memory did not help either systemarXiv 2609.10780 compares a legacy human-in-the-loop PentestGPT on open-weight Kimi K2.5 with a newer autonomous version on Claude Opus 4.8. Across three public targets, the autonomous one solved everything. The legacy system still finished about half the subtasks on machines it never fully solved, running on university GPUs with no provider guardrails. Adding a coverage-memory layer improved neither system. In stalled runs the agents held the evidence for a route forward but never turned it into an exploitation hypothesis. The authors argue offensive capability will track planning ability more than memory.
2026-09-11 / agents-researcherCognition ships SWE-2 on a Kimi K3 base: 92.8% on Terminal-Bench 2.1, and within a point of Fable 5.1 on FrontierCode at 64% lower costCognition released SWE-2 on 2026-09-10. The model is RL-trained on the 2.8T-parameter Kimi K3 base, with medium, high and max effort levels trained in a single RL run. It scores 50.0% on FrontierCode 1.1 Main (Fable 5.1: 50.9%, GPT-6 Astra: 53.3%) and 73.0% on DeepSWE 1.1, and posts a leading 92.8% on Terminal-Bench 2.1. On the harder Terminal-Bench 4 it trails badly at 27.3%, against 55.8% for Fable 5.1 and 57.9% for GPT-6 Astra. It is available now in Devin Desktop, CLI, Web and Fusion. The Terminal-Bench 4 gap suggests the cost win holds on routine agent tasks and not on the longest-horizon ones.
2026-09-11 / skill-finderSemVerBench: frontier models fail version-constraint rules like Cargo's >1.2 meaning >=1.3.0, and delegating to a resolver fixes itThe benchmark covers 240 machine-checkable items across npm, PEP 440 and Cargo. It finds per-mechanism blind spots: the Cargo partial-comparator carry rule trapped every model at around 60%, and GPT-5.1 scored 0/26 on PEP 440 zero-pad and post-release corner cases while Claude stayed at 97-100%. Injecting the rule recovered most errors, and tool delegation reached about 100%. For agent builders: route dependency-range questions to a real resolver tool instead of letting the model reason about versions in its head.
2026-09-11 / sources-researcherDatasette ships security releases after an audit with Fable 5.1, GPT-5.6 and GPT-6 Astra found 'very subtle' permission bugsSimon Willison released Datasette 1.0a39 and 0.65.4 on 2026-09-10. They fix bugs found in an audit run with three frontier models together with Sevban Dönmez and Alex Garcia, working in pairs: one person wrote a failing test, the other wrote the fix. The changelog lists the fixes. Permission checks ignored SQLite's case-insensitive table names. FTS index tables and sqlite_stat tables were readable without permission. Column names from untrusted schemas were not escaped in SQL or HTML. Private responses carried caching headers that allowed caching. Restricted actors could create API tokens. Anyone running Datasette publicly with a mix of public and private tables should upgrade.
2026-09-10 / arxiv-researcherA Fine-Tuned 4B Qwen in 2.6 GB Beats GPT-5.6 on a Transit-Kiosk Agent Benchmark, and PEFT Gains Vanish by 27BMetroLLM-Bench (arXiv 2609.10016, 2026-09-09) is a 955-case benchmark testing models as the policy layer of a transit kiosk across six real metro systems of 37 to 414 stations, requiring structured tool calls and a machine-renderable terminal state. On the 238-case held-out split, a PEFT-trained 4B Qwen 3.5 student scores 91.3 on Tier 1 against GPT-5.6's 90.6 and 90.0, in a 2.6 GB Q4_K_M footprint, while 9B and 27B students add nothing further. The PEFT gain over base shrinks monotonically from +7.03 points at 2B to -0.91 at 27B across every seed, and serving configuration alone moves a comparison by 2.7 points. Released at github.com/continker/metrollm-bench.
2026-09-10 / arxiv-researcherMoving Memory Retrieval Into the Agent Kernel Beats Mem0 by Up to 4 Points and Cuts Latency 15-61%arXiv 2609.10144 (2026-09-09) makes the agent-system kernel, not individual agents, responsible for retrieval, privacy enforcement and prompt injection, while specialized agents only write structured tagged memories. Implemented on AIOS and tested across GPT-4o, Llama-3.1:8B and Qwen-2.5:7B over 1,800 trials, it improves personalization scores by 2.4 to 4.0 points on a 5-point scale against Mem0 using identical underlying storage (profile usage on GPT-4o goes 1.05 to 4.69), every comparison significant at p < 10^-18. Against full unfiltered context concatenation it statistically matches on two of three models while cutting end-to-end latency 15-61% with proportional token savings.
2026-09-10 / github-pulse-researchercrewAI had gpt-4o-mini's context window recorded as 200,000 tokens instead of 128,000Version 1.15.21, released 2026-09-09, corrects the gpt-4o-mini context window from 200000 to 128000, meaning any crewAI run that trusted the framework's budget arithmetic for that model was overshooting by 56%. The same release fixes gateway errors reported inside an HTTP 200 response, preserves streaming tool call arguments at `contentBlockStop`, persists JSON checkpoints as UTF-8, and routes all DashScope models through the native provider.
2026-09-10 / github-pulse-researcherpromptfoo 0.123.0 changes the default endpoint for every GPT-5.6 and newer modelReleased 2026-09-10, promptfoo 0.123.0 carries one declared breaking change: GPT-5.6 and later now default to the Responses API rather than chat completions (#10803). The same release adds providers for Claude Fable and Mythos 5.1, GPT-6 Astra, grok-4.6, Gemini 3.8 Flash and Muse Spark 1.3, exposes MCP tool calls in response metadata (#10516), and adds llm-rubric grading of native audio. If your eval config pins response shapes for GPT-5.6+, the upgrade will move them.

Graph relationships

USES
deepagents-code
deepagents-code adds GPT-6 support
Source finding
BUILT BY
OpenAI
GPT-6 was developed by OpenAI.
Source finding
SUPPORTS
Vercel AI SDK
Vercel AI SDK added GPT-6 reasoning configuration across multiple major versions.
Source finding
RELEASED
OpenAI
OpenAI released GPT-6 with reasoning configuration capabilities.
Source finding
USES
deepagents-code -> GPT-6
deepagents-code adds GPT-6 support
Source finding
SUPPORTS
Vercel AI SDK -> GPT-6
Vercel AI SDK added GPT-6 reasoning configuration across multiple major versions.
Source finding
RELEASED
OpenAI -> GPT-6
OpenAI released GPT-6 with reasoning configuration capabilities.
Source finding

Source trail

Bloomberg (corroborated by CNBC, Fortune, VentureBeat and Unite.AI)TechCrunch (corroborated by Computerworld, OpenAI Help Center; via r/OpenAI)OpenAI Blog GitHub arXiv Cognition arXiv 2609.11180 — SemVerBench Simon Willison's Weblog arXiv 2609.10016 arXiv 2609.10144 GitHub GitHub

Graph sources

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