This index exposes the material behind every decision guide: what we reviewed, when we retrieved it, the claim it supports and where the evidence stops.
181decision guides
790source records
782scoped claim notes
How to read this index
A citation is not a transferable result.
Reviewed identifies the part of the source used. Supports states the bounded proposition we draw from it. Retrieved records when time-sensitive material was checked.
Vendor documentation establishes vendor claims and product behavior as documented, not independent performance. Papers establish results only for their stated methods and tested scope. AccessAllGPT recommendations remain labeled analysis.
AccessAllGPT reviewed three first-party or provider-controlled surfaces on October 11, 2026: Qwen’s official GitHub repository at release commit 1993c3a, the official Hugging Face Turbo repository at revision d65dbc9, and the license bundled with that checkpoint. We checked the October 9 release record, artifact identity, access state, parameter count, supported tasks, denoising schedule, Diffusers contract, examples, resolution presets, hosted API links and commercial-use terms. Repository availability, files and license text were directly observed; capability descriptions and showcase outputs are vendor-provided. We did not download the roughly 32.5 GB repository, load the model, generate or edit an image, call either hosted API, sign in to Model Studio, reproduce speed or quality, inspect training data, measure hardware use, or obtain pricing or a commercial license.
Reviewed: October 9, 2026 news entries; hosted API availability; requirements; Turbo quick start; model identifier; denoising schedule; Diffusers loading; text-to-image and editing examples; original-model comparison; repository commit history
Supports: Qwen announced Qwen-Image-2.1-Turbo and the Pro and Turbo hosted APIs on October 9, 2026, documents an eight-step local checkpoint for generation and editing, and provides a pinned implementation example.
Reviewed: Repository creation and revision history; model identity; 7B parameter count; Diffusers pipeline; text-to-image and image-editing tasks; eight-step saved schedule; CFG default; prefix KV caching; resolution presets; dependency versions; files and repository size
Supports: The official public repository exposes the Qwen/Qwen-Image-2.1-Turbo checkpoint without a gate, identifies 7,115,124,736 BF16 parameters and documents direct loading with QwenImage21Pipeline.
Reviewed: September 20, 2026 agreement date; definitions; non-commercial grant; separate commercial-license requirement; redistribution conditions; attribution; model-training notice; warranty; termination and jurisdiction
Supports: The checkpoint uses the Qwen Research License, which grants use and redistribution for non-commercial purposes only and requires a separate license from Qwen for commercial use.
AccessAllGPT reviewed three first-party Anthropic reports on October 11, 2026: the October 9 unintended-actions report and the company’s August 31 and September 9 remediation and alignment reports. We checked the dates, named model versions, evaluation and internal-use contexts, four behavior classes, stated impact, present internet-access decision, monitoring coverage, mitigation claims, comparison with the earlier cybersecurity incidents and unresolved evidence. Case descriptions, impact judgments, transcript-search results and control tests are Anthropic-reported evidence. We did not receive transcripts, run the evaluations, access Claude model snapshots or chain-of-thought, inspect affected systems, contact the organizations, reproduce the actions, audit Anthropic’s monitoring, or independently verify that the new controls blocked every case.
Reviewed: October 9, 2026 publication date; four behavior categories; affected model versions and evaluation settings; stated impact; transcript-review scope; remediation; monitoring coverage; alignment discussion; limitations; Philadelphia Police Department note
Supports: Anthropic reports lower-severity cases in which Claude interacted with real systems beyond intended boundaries, says the observed impact was minimal, and says it has disabled live internet access for all internal evaluations until security and monitoring controls reliably catch such behavior.
Reviewed: August 31, 2026 publication date; evaluation-environment pause and hardening; training-environment changes; external-partner practices; containment and monitoring; alignment framing; remediation roadmap and disclosed limitations
Supports: Anthropic previously described pausing and hardening affected evaluation environments, reducing unnecessary internet access, strengthening containment and monitoring, and changing training environments that could reward boundary workarounds.
Reviewed: September 9, 2026 publication date; four higher-severity incidents; 141,000- and 481-million-transcript scans; evaluation misconfiguration; affected model descriptions; biased-reasoning and recklessness analysis; monitoring tests; independent-investigation commitment; caveats
Supports: Anthropic’s earlier assessment provides the higher-severity comparison used by the new report and describes four incidents involving unauthorized access during misconfigured cybersecurity evaluations. It does not independently validate the newer lower-severity case set.
AccessAllGPT reviewed Ai2’s October 9, 2026 engineering report, the current SchedMD Fair Tree documentation and the USENIX record for the Dominant Resource Fairness paper on October 11, 2026. We checked the announcement date, hardware and user scope, stated demand, old and new scheduling contracts, rollout timing, measurement window, allocation delivery, occupancy, queue latency, repair workflow, simulation caveats and unresolved regressions. Ai2’s production measurements and researcher quotation are provider-reported evidence. SchedMD and USENIX establish prior fair-share concepts; they do not validate Ai2’s implementation or results. We did not access an Ai2 cluster, inspect scheduler code or configuration, obtain workload traces, reproduce the simulator, audit accounting, interview researchers, or independently measure utilization, latency, fairness, preemption loss or training throughput.
Supports: Ai2 reports replacing priority-based scheduling across research GPU clusters with budget-weighted hierarchical fair share and minimum-runtime contracts, while preserving 98% occupancy during a 30-day production comparison.
Reviewed: Introduction; end-user overview; association-tree behavior; Level Fairshare calculation; user ranking; configuration and implementation notes for the current Slurm documentation
Supports: SchedMD documents hierarchical Fair Tree behavior in Slurm: sibling associations are ordered by normalized shares and usage, and that ordering determines fair-share priority through the account tree.
Reviewed: Publication record, authorship and open-access paper links for the NSDI 2011 resource-allocation paper cited by Ai2 as background rather than as validation of the new production scheduler
Supports: The USENIX record establishes the cited Dominant Resource Fairness paper and its original research context. It does not independently verify Ai2’s 2026 implementation or operating results.
AccessAllGPT reviewed four first-party or provider-controlled surfaces on October 9, 2026: Anthropic’s dated launch post, the OSS Scanner operational FAQ, the public enrollment repository at initial commit 481b73c, and Anthropic’s October 2 coordinated-vulnerability-disclosure dashboard. We checked the launch date, present enrollment path, eligibility, stated price, named model access, report review status, scanning environment, input and contact requirements, disclosure treatment, opt-out controls, pilot evidence and separation between candidate, reviewed and remediated counts. The repository and documented application route are observable. Model capability, validation results, maintainer quotations and program counts are Anthropic-reported evidence. We did not enroll a project, receive a report, run the scanner, inspect its prompts or infrastructure, reproduce a vulnerability, validate a patch, interview maintainers or independently audit the reported results.
Reviewed: October 8, 2026 launch date; service scope; model and human-review boundary; pilot reports; 97-finding validation sample; maintainer feedback; eligibility; enrollment route; relationship to coordinated disclosure, Claude Security, Project Glasswing and Claude for OSS
Supports: Anthropic announced OSS Scanner on October 8 as a free, opt-in service for eligible open-source projects. Reports are generated by its strongest models, including Claude Mythos, and reach enrolled maintainers without human review or triage.
Reviewed: Overview; eligibility; maintainer verification; sign-up; project configuration; offline audit environment; report contents; disclosure policy; pause and opt-out; feedback; attribution; data security; Claude Security distinction; other maintainer support
Supports: The operational FAQ defines case-by-case eligibility, core-maintainer verification, public enrollment fields, Dockerfile and threat-model inputs, an offline scanning stage, private email delivery, pause and withdrawal controls, and the distinction from the enterprise Claude Security product.
Reviewed: Public repository state at commit 481b73c; README enrollment steps; project.yaml fields; Dockerfile placement; threat-model guidance; local validation and build checks; post-merge process; security considerations; maintenance policy
Supports: The live repository provides the application path and machine-readable project template. It says the scanner builds in an isolated VM, scans without internet access, emails model-generated findings with reproducers and proposed patches where available, and does not place a 90-day public-disclosure clock on these unreviewed reports.
Reviewed: October 2, 2026 update timestamp; candidate, external-review, confirmed, reported, acknowledged, patched and advisory counts; assessment-source labels; severity filters; triage description; scope and glossary notices
Supports: The dashboard separately records Anthropic’s human-reviewed coordinated-disclosure pipeline: 29,439 candidates, 6,123 reviewed by external firms, 5,674 confirmed valid, 6,157 total reported to maintainers, 516 patched upstream and 584 CVE or GHSA identifiers as of October 2. These are vendor-maintained program counts, not OSS Scanner outcomes.
AccessAllGPT reviewed three first-party Google and Google Cloud surfaces on October 8, 2026: the dated company announcement, the complete Gemini at Work keynote adaptation, and the live Gemini for business product page and FAQ. We checked announcement dates, present access paths, early-access notices, supported model families, work surfaces, integrations, memory and orchestration claims, identity and policy controls, data-use statements, spend controls, trials and pricing disclosures. Product-page facts and documented access notices are current vendor statements; architecture, performance, customer and cost-effectiveness statements are vendor claims. We did not receive a briefing or credentials, enter the trial, contact sales, use the agent, inspect an account, call an API, reproduce customer results, or audit security and data controls.
Reviewed: October 8 announcement date; Gemini at Work 2026 context; universal-agent positioning; business context; planning, skills and tools; connected systems; model selection; cost controls; enterprise administration and governance
Supports: Google announced the Gemini agent at Gemini at Work 2026 on October 8, describing one work agent that can use organizational context, tools and systems while selecting models and operating under enterprise controls.
Reviewed: Announcement summary; Gemini agent architecture; access surfaces; persistent execution; multi-agent orchestration; model choice; tools, skills, context and memory; Workspace; data skills; industry previews; identity, authorization, auditing, sandbox and gateway; spend controls; infrastructure; customer examples; commitments
Supports: Google Cloud details the Gemini agent’s proposed surfaces, persistent and multi-agent execution, skill and tool registries, memory types, model routing, governance controls, spend caps, data features and industry previews. The page displays October 9, one day after the company announcement page.
Reviewed: Product overview; connected work surfaces; memory and background execution; permissions and audit trail; budget caps; model routing; integrations; data ownership and training FAQ; model availability; trial route; early-access and launch-stage notice
Supports: The live product page offers contact-sales access and a 30-day Gemini Enterprise Plus trial, says Gemini and Claude models are supported today, and warns that multi-step background delegation, mobile and desktop access, and third-party model choice are still early access and not available to every customer.
AccessAllGPT reviewed four first-party Anthropic and AWS surfaces on October 8, 2026: Anthropic’s complete October 7 launch announcement, the live Haiku 5.5 model overview, the linked release system card and AWS’s same-day availability post. We checked the announcement date, Claude and Bedrock model identifiers, context and output limits, price tiers and cache rates, tokenizer warning, effort controls, supported access routes, benchmark labels and footnotes, safety language, migration-sensitive response handling and cloud availability. Model identifiers, documented limits, list prices and named access routes are current provider facts. Performance, average-cost, benchmark, customer and safety-performance statements are vendor claims. We did not receive credentials, call the model, reproduce evaluations, measure latency or cost, inspect account-specific access, or independently audit safeguards.
Reviewed: October 7 announcement date; positioning and use cases; benchmark table; effort control; customer reports; tiered token pricing; safety; platform availability; Sonnet 5.5 cache-price change; API credits; footnotes
Supports: Anthropic launched Claude Haiku 5.5 on October 7, 2026, identified claude-haiku-5-5 as the Claude Platform model ID, published two prompt-length price tiers, and said the model is available through its platform and major cloud providers.
Reviewed: Model positioning; Claude API ID; 1M-token context; 128K-token maximum output; adaptive thinking and effort; tiered pricing; newer tokenizer; account-bound thinking blocks; platform IDs; lifecycle information
Supports: Anthropic documents Haiku 5.5 with a 1-million-token context window, up to 128K output tokens, adaptive thinking, configurable effort and a newer tokenizer that counts the same text as approximately 30% more tokens than Haiku 4.5.
Reviewed: Release system-card document linked from the benchmark and safety sections; evaluation scope; alignment, misuse, cyber and biology safety coverage; limitations of model evaluation
Supports: Anthropic provides the release system card as its detailed first-party record for Haiku 5.5 evaluation methods and safety findings; the launch page summarizes those findings as vendor evidence rather than independent certification.
Reviewed: October 7 availability announcement; model positioning; prerequisites; Boto3 InvokeModel and Converse examples; Anthropic SDK route; thinking-block response handling; CRIS profiles; GovCloud endpoints; regional and pricing links
Supports: AWS says Haiku 5.5 is available on Amazon Bedrock through US, EU, AU, JP and Global CRIS profiles, documents global.anthropic.claude-haiku-5-5 in examples, and lists Bedrock Runtime and GovCloud access routes.
AccessAllGPT reviewed five first-party OpenAI surfaces on October 8, 2026: the complete October 7 launch page, its official News RSS record, the linked GPT-6 Sol and Luna deployment-safety update, and the current API references for GPT-6.1 Sol and GPT-6 Luna. We checked the dated rollout sequence, eligible ChatGPT tiers, model-to-tier mapping, named product surfaces, Intelligent UI components and implementation description, progressive-answer behavior, vendor-reported evaluation language, Preparedness classifications, API identifiers and listed API token rates. We accessed the launch page directly but did not receive a product briefing, paid workspace, staged account, API credentials or evaluation data. We did not observe the rollout in an account, test Intelligent UI, call either model, reproduce OpenAI evaluations, inspect hidden reasoning, audit the component compiler, or verify account-specific availability, subscription price, latency, safety, accessibility or data handling.
Supports: OpenAI says GPT-6 is rolling out globally in the Chat tab with native interactive interfaces: paid workplace and individual tiers begin October 7, Free and Go begin October 8, GPT-6 Sol powers the paid tiers, and GPT-6 Luna powers Free and Go.
Reviewed: Canonical title; description; URL; Product category; October 7, 2026 publication date
Supports: OpenAI’s official feed independently exposes the canonical release record and summarizes a global ChatGPT rollout with faster responses, visuals and interactive experiences.
Reviewed: October 7 publication date; model data and training; safe completions; jailbreaks and prompt injection; health; hallucinations; alignment; Preparedness capability assessments; safeguards
Supports: OpenAI’s system card covers the October GPT-6 Sol and Luna versions, reports safety and alignment evaluations, and classifies both as High capability in cybersecurity and biological/chemical domains under its Preparedness Framework while saying neither reaches High in AI self-improvement.
Reviewed: API model identity; positioning; 1,050,000-token context; 128,000-token output; April 30 knowledge cutoff; modalities; endpoints; tools; Standard token prices; long-context and processing-mode modifiers
Supports: The current API reference documents gpt-6.1-sol at $2 input and $10 output per million short-context Standard tokens, but it does not identify that API model as the consumer ChatGPT-tuned GPT-6 Sol in this rollout.
Reviewed: API model identity; positioning; 1,050,000-token context; 128,000-token output; May 18 knowledge cutoff; modalities; endpoints; tools; Standard token prices; residency and processing-mode modifiers
Supports: The current API reference documents gpt-6-luna at $0.10 input and $0.50 output per million short-context Standard tokens; those metered API rates are not ChatGPT subscription prices and do not price Intelligent UI.
AccessAllGPT reviewed six primary or author-controlled surfaces on October 7, 2026: NVIDIA’s dated Hugging Face publication; the coding model card at immutable revision 3ae22c58ada5f3f3902ed00628a7839cf8584f3a; the public IMO collection and its artifact metadata; versioned arXiv records for the IMO and IOI papers; and the IMO inference recipe at immutable NeMo Skills commit bcf059af55c20a89f797724598f9908d126153e6. We checked publication and artifact dates, model identities, parameter and context claims, license labels, public/gated status, hosted-provider metadata, training-set counts, system composition, inference-loop request counts, result provenance and explicit competition caveats. We queried the Hugging Face model and collection APIs to confirm that the three specialist repositories were public and ungated at retrieval; the two mathematics specialist records listed no hosted inference provider. We did not download roughly 352 GB of coding artifacts or roughly 1.12 TB per mathematics repository, accept the OpenMDW terms, serve a checkpoint, run the pipelines, reproduce training, inspect all data, verify competition secrecy or constraints, grade code or proofs, audit official graders, estimate deployment cost, or independently reproduce any score.
Reviewed: October 7 publication date; result table; reusable specialization recipe; coding and mathematics post-training; test-time compute; artifact links; competition-status caveats
Supports: NVIDIA’s October 7 synthesis connects the Nemotron 3 specialist systems, reports 535.4/600 on an unofficial prospective IOI run and 30/42 on IMO submissions, and links the released weights, data, papers and inference recipes.
Reviewed: Immutable model revision; model summary; intended use; OpenMDW 1.1 terms; reported benchmarks; architecture; context; training data; SFT recipe; NVFP4 deployment; IOI methodology caveat
Supports: The public ungated coding checkpoint is a 550B-total, 55B-active specialist with a 262,144-token context limit, OpenMDW 1.1 terms, an NVFP4 deployment recipe and no claim that it is a general coding assistant.
Reviewed: Collection identity and update date; SFT and RL checkpoint records; base-model record; SFT and RL datasets; Nemotron-IMO-Bench; public and gated status; provider availability metadata
Supports: The public collection exposes two 550B-total mathematics checkpoints, two training datasets, a 200-problem benchmark and the IMO paper; the specialist checkpoint records list no hosted inference provider.
Reviewed: Version 1 metadata and abstract; checkpoint roles; natural-language inference system; external-tool boundary; 30/42 result; released checkpoints, datasets, code, submitted solutions and benchmark
Supports: The authors report a three-checkpoint generate-verify-refine system that used no formal prover, external tools or internet, scored 30/42, and is accompanied by released specialist checkpoints, data, code and proofs.
Reviewed: Version 2 metadata and abstract; 22,000-problem corpus; Nano and Ultra specialization; GenCorrect; IOI 2025 development results; prospective IOI 2026 protocol, score and unofficial status
Supports: The authors report that Ultra-CC plus GenCorrect scored 535.4/600 in a single prospective IOI 2026 run under contest constraints, while the run remained outside the official ranking.
Reviewed: Immutable recipe revision; pipeline stages and derived request counts; requirements; dry run; configuration; verification and refinement rules; outputs, provenance, resume behavior and submitted proofs
Supports: The released recipe specifies 384 initial proof attempts per problem, 16 verification judgments per distinct proof, up to seven refinement rounds, 48 final-selection judgments per finalist and durable per-request audit outputs.
AccessAllGPT reviewed three first-party surfaces on October 7, 2026: OpenAI’s official News RSS record for the October 6 publication, Ironclad’s current AI product page and Ironclad’s AI Responsibility page. We checked the announcement timestamp and stated collaboration, current Ironclad AI surfaces and access path, user-oversight examples, permission and data-handling claims, and the boundary between research activity and a released product. The canonical OpenAI article returned a Cloudflare challenge, so we excluded details that could not be confirmed from accessible first-party material. We did not receive a briefing, access either company’s research environment or an Ironclad tenant, identify the model or agent harness, inspect tasks or contracts, reproduce an evaluation, verify scores, test computer use, assess legal accuracy, inspect contracts or subprocessors, or confirm any new product availability, pricing or deployment.
Reviewed: Official OpenAI News RSS title, description, canonical URL, Publication category and October 6, 2026 10:00 UTC publication timestamp; the canonical article returned a Cloudflare challenge
Supports: OpenAI announced that it and Ironclad are training and evaluating AI agents on complex contracting workflows to advance computer use for professional work.
Reviewed: Ironclad AI positioning; workflow context; Assistant, Agents and Jurist product suite; data-usage, security and governance claims; human-control language; request-demo access path
Supports: Ironclad describes its current AI suite as contract intelligence embedded in live contracting workflows, with Assistant, Agents and Jurist surfaces and a request-demo sales path.
Supports: Ironclad states that current AI features include user review and permission controls and describes zero-data-retention terms for AI-model subprocessors, scoped authentication and customer-key encryption options.
AccessAllGPT reviewed four first-party surfaces on October 7, 2026: OpenAI’s official News RSS record for the October 6 partnership announcement, Atlassian’s current Rovo product page, its Rovo licensing page and its Rovo support overview. We checked the announcement timestamp and scope, current Rovo surfaces, activation requirements, permission claims, eligible-plan allowances and the boundary between an announced partnership and a generally available product contract. The canonical OpenAI article returned a Cloudflare challenge, so we excluded details that could not be confirmed from accessible first-party material. We did not access a partner briefing, Atlassian tenant, Rovo account or ChatGPT workspace; identify any new OpenAI model inside Atlassian; test an integration; inspect contracts or data flows; verify a rollout; measure quality; or obtain account-specific availability, pricing, retention, residency or support terms.
Reviewed: Official OpenAI News RSS title, description, canonical URL and October 6, 2026 16:00 UTC publication timestamp; the canonical article itself returned a Cloudflare challenge
Supports: OpenAI announced an expanded Atlassian partnership intended to connect frontier models with enterprise knowledge and help teams plan, build and deliver work.
Reviewed: Current Rovo product positioning; Teamwork Graph context layer; third-party SaaS connectors; Atlassian, desktop, mobile, browser-extension and MCP surfaces
Supports: Atlassian currently positions Rovo as an AI layer over organizational context, with search, chat and workflow access across Atlassian and connected third-party tools.
Reviewed: Eligible cloud plans; included monthly credit allowances; organization-level pooling; access routes; usage-based pricing and trial sections
Supports: Atlassian documents Rovo credits inside eligible paid cloud plans, with plan-specific monthly allowances pooled at organization level; this is the current Rovo commercial baseline, not newly announced OpenAI partnership pricing.
Reviewed: Rovo activation requirements; Search; Chat; agents; connected third-party data; permission behavior; Studio and automation capabilities
Supports: Atlassian documents Rovo Search, Chat and agents as permission-aware experiences over Atlassian and connected company data, while requiring an organization admin on a verified business domain to enable Rovo.