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 six NVIDIA-controlled public surfaces on October 22, 2026: the dated Agent Toolkit announcement, the live Agent Knowledge Foundation and Kumo catalogs, the Kumo Relational NIM page, the dated OpenShell Reference Architecture release and the NemoClaw optimization blueprint. We checked announcement timing, named components, current links and prototype paths, model and API identifiers, deployment routes, pricing disclosures, partner and performance claims, and operational boundaries. Availability visible on those surfaces is directly observable; adoption, accuracy, speed, capacity and security-performance figures remain vendor-reported. AccessAllGPT did not create an NVIDIA account, generate an API key, download weights, clone repositories, run a NIM, deploy OpenShell, inspect partner systems or reproduce any claim.
Reviewed: October 21 announcement date; toolkit components; Agent Knowledge Foundation description; named Kumo models; Auto-Ontology; OpenShell and NemoClaw roles; partner adoption statements; retrieval performance claims
Supports: NVIDIA announced the expanded Agent Toolkit on October 21, 2026, naming Agent Knowledge Foundation, Nemotron Retriever, Kumo, Auto-Ontology, OpenShell, NemoClaw, NeMo Relay and NeMo Compass. Adoption and performance statements are NVIDIA or partner claims.
Reviewed: Component catalog; compatibility statement; Nemotron Retriever, Kumo and Auto Ontology descriptions; CUDA-X library roles; workflow architecture; published performance claims
Supports: The live product page describes components as individually usable with existing data platforms, ontologies, vector databases and agent frameworks. It lists retrieval, structured prediction, ontology generation, data processing, graph, optimization and vector-search components.
Reviewed: Kumo family scope; Relational, Tabular, Forecast and Anomaly model descriptions; open-weight links; NIM API links; Structured Data Models and Kumo-TS runtimes; ethical considerations
Supports: NVIDIA exposes four named Kumo routes for relational, tabular, forecasting and anomaly workloads. The page links downloadable weights for all four, NIM API prototypes for Relational and Tabular, and public runtime repositories.
Reviewed: Prototype endpoint; request model identifier; task and schema contract; API-key requirement; self-hosted NIM path; NVIDIA AI Enterprise evaluation statement
Supports: The live page offers a free prototype endpoint using model identifier kumo-relational and documents a self-hosted NIM path. It does not display a production per-request price on the reviewed surface.
Reviewed: October 21 release date; software and hardware layers; supported operating environments; partner list; availability paragraph; throughput, performance, quarantine and capacity claims
Supports: NVIDIA announced a reference architecture spanning OpenShell software, Vera Rubin, Vera CPUs, BlueField-4 and Sentry, with Linux, Kubernetes, Windows and major-cloud environment statements. All performance and enforcement results are vendor claims.
Reviewed: Blueprint purpose; open status; NeMo Compass and Eval Author workflow; Hermes and LangChain examples; held-out evaluation and A/B comparison steps; Try Now and GitHub access
Supports: The live blueprint documents a trace-to-evaluation workflow for changing prompts, tool descriptions or routing logic, with two runnable examples and saved comparisons. It is an evaluation blueprint, not evidence that an agent improved on a buyer workload.
AccessAllGPT reviewed four IBM-authored or IBM-controlled public surfaces on October 22, 2026: the October 21 launch article and the live repositories and model cards for Granite Speech 5.0 2B, Granite Speech 5.0 470M TurboCTC and Granite Speech 4.1 2B Plus. Repository records were pinned to commits f4e68169fa2a5751acc4b5da9957855e5e8fc3f1, 1dd23f46f6d4e6eae2531982ba2e33220086dd97 and e69efe37f97b6283c61f5a8dadda2b3eb67765d6. We checked release timing, current artifact access, model identifiers, parameter metadata, licenses, languages, task boundaries, training summaries, runtime requirements, published evaluations, caveats and pricing disclosures. Repository availability is directly observable; accuracy, robustness, speed and comparison results remain vendor-reported. AccessAllGPT did not download the checkpoints, run inference, reproduce benchmarks, inspect every training example or measure quality, latency, memory, energy or cost.
Reviewed: October 21 publication date; three-model release table; 5.0 2B languages, translation and keyword claims; TurboCTC speed and accuracy claims; 4.1 2B Plus attribution, timestamp and long-form claims; selection guidance; license and runtime summary
Supports: IBM announced one new Granite Speech 5.0 2B model and two revised speech models on October 21, 2026. The article distinguishes the high-accuracy translation model, the high-throughput edge model and the multi-speaker model; all performance figures are IBM-reported.
Reviewed: Public and gated state; pinned revision; parameter metadata; release date; license; supported languages and translation directions; training summary; architecture; keyword limit; evaluation descriptions; runtime support; segment guidance; limitations
Supports: The public, ungated repository was reviewed at commit f4e68169fa2a5751acc4b5da9957855e5e8fc3f1. Its API record reports 2,313,207,132 BF16 safetensors parameters. The card lists an October 20 release, Apache 2.0, six ASR languages, bidirectional translation with English, 2,000-term keyword biasing, and Transformers, vLLM, llama.cpp and MLX usage paths.
Reviewed: Public and gated state; pinned revision; October 21 update and August predecessor; parameter metadata; seven languages; training summary; punctuation; English WER comparison; speed statement; Transformers and MLX requirements; license
Supports: The public, ungated repository was reviewed at commit 1dd23f46f6d4e6eae2531982ba2e33220086dd97. The API reports 472,993,792 safetensors parameters. IBM says the October 21 revision adds six languages and native punctuation while reporting 5.51% average English WER versus 5.78% for the earlier English-only checkpoint.
Reviewed: Public and gated state; pinned revision; April release and October 19 update; parameter metadata; supported languages; speaker-attributed ASR; timestamps; long-segment tables; keyword biasing; updated Open ASR comparison; Transformers and vLLM requirements; license
Supports: The public, ungated repository was reviewed at commit e69efe37f97b6283c61f5a8dadda2b3eb67765d6. The API reports about 2.11 billion BF16 parameters. The card documents an October 19 update for five-language transcription, speaker labels, word timestamps and keyword biasing, with mixed rather than uniformly improved vendor-run benchmark results.
AccessAllGPT reviewed five first-party public surfaces on October 21, 2026: OpenAI’s dated partnership announcement, Google Cloud’s launch article, and OpenAI’s live model references for GPT-6 Astra, GPT-6.1 Sol and GPT-6 Luna. We checked announcement timing, current versus promised access, named models, direct OpenAI model IDs and specifications, API and Codex claims, billing path, published prices, governance statements and coming-soon controls. Google Cloud’s structured metadata says datePublished 2026-10-21 while its rendered article displayed October 22 during this review; we preserve that inconsistency and use OpenAI’s October 21 announcement date. AccessAllGPT did not obtain preview access, submit the interest form, call a Google Cloud endpoint, connect Codex, inspect a contract or invoice, or test the models or controls.
Reviewed: October 21 announcement date; Model Garden and Codex partnership scope; Marketplace transaction path; GCP commitment drawdown; Google Antigravity and Gemini Agent roadmap; general-availability timing; Microsoft cloud-partner statement
Supports: OpenAI says its frontier models and Codex workflows are coming to Google Cloud Model Garden, purchases will transact through Google Cloud Marketplace and can draw down GCP commitments, general availability is planned in the coming weeks, and Microsoft remains OpenAI’s primary cloud partner.
Reviewed: Publication metadata and rendered dateline; three named models; private-preview availability; API and Codex connection statements; Marketplace billing and Flexible Savings Plans; data-perimeter, training-use, infrastructure, identity and audit claims; coming-soon ZDR and Confidential Compute
Supports: Google Cloud names GPT-6 Astra, GPT-6.1 Sol and GPT-6 Luna, says they are rolling out in private preview to select enterprise customers, and says selected customers can use APIs and connect local Codex CLI and Desktop workflows. Google also describes Marketplace billing, governance controls and two security features that remain forthcoming.
Reviewed: Direct OpenAI API model ID; model positioning; input and output modalities; context and output limits; reasoning levels; Standard token prices; long-context multiplier; endpoints, features and tools
Supports: OpenAI documents gpt-6-astra for text and image input and text output with a 1,050,000-token context window, 128,000-token maximum output, and direct-API Standard prices of $10 input and $50 output per million tokens. These are not published Google Cloud preview rates.
Reviewed: Direct OpenAI API model ID; positioning; modalities; context and output limits; reasoning levels; Standard token prices; long-context and processing-mode modifiers; Responses and Chat Completions support
Supports: OpenAI documents gpt-6.1-sol for text and image input and text output with a 1,050,000-token context window, 128,000-token maximum output, and direct-API Standard prices of $2 input and $10 output per million tokens. These are not published Google Cloud preview rates.
Reviewed: Direct OpenAI API model ID; positioning; modalities; context and output limits; reasoning levels; Standard token prices; long-context and processing-mode modifiers; Responses and Chat Completions support
Supports: OpenAI documents gpt-6-luna for text and image input and text output with a 1,050,000-token context window, 128,000-token maximum output, and direct-API Standard prices of $0.10 input and $0.50 output per million tokens. These are not published Google Cloud preview rates.
AccessAllGPT reviewed three Google-controlled public surfaces on October 21, 2026: the dated in-car launch announcement, the Personal Intelligence product page and Google’s Connected Apps personalization help article. We recorded announcement date, current and promised availability, connected sources, example requests, setup and age notices, pricing and API omissions, data-use statements, human-review language, and disconnect and deletion behavior. All capability, availability, security and privacy descriptions are Google statements. AccessAllGPT did not enter a vehicle, sign in, receive the rollout, connect an app, issue a voice request, inspect an answer or source reference, test distraction handling, measure accuracy or latency, or verify account, language, vehicle or regional eligibility.
Reviewed: October 20 publication date; global Gemini availability in cars; Personal Intelligence rollout timing; connected Google apps; example requests; opt-in controls; Android Auto and Google built-in sequencing
Supports: Google says Gemini is available globally on Android Auto and cars with Google built-in. Personal Intelligence began rolling out to Android Auto on October 20, 2026, while availability in cars with Google built-in is promised for the coming months. The announcement lists Workspace, Photos, Maps, YouTube and Search as connected sources and says setup is optional.
Reviewed: Connected-app description; chat-history preferences; opt-in app selection; activity and settings controls; source-reference behavior; compatibility, availability, setup and age notices
Supports: Google describes Personal Intelligence as an optional personalization layer that can connect Gmail, Photos, Search and YouTube with chat-history preferences. The page says users can select connected apps, manage past-chat use and review activity; it also warns that responses require checking, setup is required, compatibility and availability vary, and users must be 18 or older.
Reviewed: Eligible-user scope; connected-app list; data categories; sensitive-data notice; service improvement and model training; human review; cross-service sharing; app disconnection; activity deletion; personalization settings
Supports: Google says connected data can include email, files, events, photos, videos, contacts, Wallet information and location, including sensitive or confidential information. It says data may be used to improve services and train generative AI, may be human reviewed under the Gemini Apps Privacy Notice, and is not automatically removed from Gemini Apps Activity when an app is disconnected or source data is deleted.
AccessAllGPT reviewed four project-controlled public surfaces on October 21, 2026: the IBM-authored October 20 report hosted by Hugging Face, the ALTK-Evolve repository at commit 5f76fd190bb9ad427dbac8f95e22f17cd8fddcb8, and the live τ²-bench retail and airline submission pull requests. We separated held-out test results from base-split leaderboard submissions; recorded task counts, trials, model roles, Pass^4, reported conversation cost, prompt modifications, train-task overlap, verification state, package version and license; and treated every performance result as author-reported. AccessAllGPT did not install ALTK-Evolve, call either OpenAI model, rerun τ²-bench, inspect all trajectories, reproduce costs or independently validate the leaderboard ranking.
Reviewed: October 20 publication date; guideline-learning method; held-out retail and airline design; mean accuracy and Pass^4 tables; token-cost and turn-count tables; base-split leaderboard comparisons; links to code and submissions
Supports: The IBM-authored report says prompt-appended guidelines learned from training trajectories improved GPT-4.1 held-out retail Pass^4 from 57.5% to 67.5% and held-out airline Pass^4 from 35% to 45%; it also reports higher input cost, domain-dependent guideline dosage, and separate base-split leaderboard comparisons.
Reviewed: README overview and October 20 update; source and PyPI installation routes; Python requirement; model-provider configuration; package version; Apache 2.0 license; local dashboard and API warning; available memory tools
Supports: The public repository provides ALTK-Evolve under Apache 2.0, lists Python 3.12 or newer, documents source and PyPI installation, and identifies core package version 1.7.1 at the reviewed commit. The README warns that the default local dashboard API has no authentication.
Reviewed: Open pull-request state; retail base-split task and trial counts; Pass^1 through Pass^4; average conversation cost; model and simulator; modified-prompts disclosure; train-task overlap; trajectory link; expected Unverified status
Supports: The still-open submission reports 67.54% Pass^4 over 114 retail base-split tasks and four trials at $0.1084 average cost per conversation. It discloses modified prompts, says guidelines were learned from the train split included in the base evaluation, and expects an Unverified label.
Reviewed: Open pull-request state; airline base-split task and trial counts; Pass^1 through Pass^4; average conversation cost; model and simulator; modified-prompts disclosure; train-task overlap; trajectory link; expected Unverified status
Supports: The still-open submission reports 82.00% Pass^4 over 50 airline base-split tasks and four trials at $0.1690 average cost per conversation. It discloses modified prompts, says guidelines were learned from the train split included in the base evaluation, and expects an Unverified label.
AccessAllGPT reviewed three Google-controlled public surfaces on October 21, 2026: the dated small-business launch announcement, Google’s September Connected Apps announcement and the Gemini Apps Privacy Hub updated October 19. We checked what Google says is rolling out, intended users, named integrations, invocation paths, model reference, rollout timing, pricing omissions and documented data controls. Availability, speed, user-count and customer-outcome statements remain Google claims. AccessAllGPT did not sign in, receive the rollout, connect an account, upload a brand kit, generate an asset, analyze financial records, inspect permissions, observe retention, measure accuracy or latency, compare plans, or test Nano Banana 2.1.
Reviewed: October 20 publication date; business landing page; Google and third-party app connections; brand-style inputs and Nano Banana 2.1; finance analysis; named customer examples; global rollout timing and intended account scope
Supports: Google announced a Gemini business landing page, marketing and finance skills, brand-style retention, and additional connected apps on October 20, 2026. Google says the features are beginning to roll out globally in the coming days to all Gemini app users; the page does not publish a feature-specific price, fixed quota or developer API.
Reviewed: September 23 publication date; rollout wording; productivity, creativity and lifestyle app categories; named integrations; connection through Gemini settings; @-mention and direct-request invocation
Supports: Google previously documented a broader Gemini Connected Apps rollout, including Adobe, Zoho and other third-party services, and says users can connect apps in Gemini settings or invoke them through an @ mention or direct request. The announcement does not define one common permission or data contract for every provider.
Reviewed: October 19 update; information from Connected Apps; provider-specific data processing; Connected Apps controls; Keep Activity behavior; human review; temporary-chat retention; third-party service and custom-app warnings
Supports: Google says Gemini can exchange content with Connected Apps, third-party apps process shared data under their own policies, and users can connect or disconnect apps in settings. The notice says Keep Activity affects availability and improvement use, warns against entering confidential information users would not want reviewed, and describes separate retention behavior for temporary chats and reviewed data.
AccessAllGPT reviewed five first-party public surfaces on October 21, 2026: OpenAI’s dated Terminal X customer story, Terminal X’s live product page, OpenAI’s GPT-6.1 Sol model reference, current API pricing tables and original GPT-6.1 Sol launch article. We checked the publication date, evaluated task, 54-criterion rubric description, 500-judgment sample, agreement and mandate-drift figures, cost and speed comparison, platform availability, model ID, current limits and list prices. All performance, savings, usage and adoption figures are attributed to OpenAI’s customer story or Terminal X; they are not AccessAllGPT measurements. We did not receive the judgment set, rubric, predictions, reviewer labels, comparator identity, token logs, invoices, confidence intervals, error analysis or customer records; contact Terminal X, use its product, or call the OpenAI API.
Reviewed: October 20 publication date; product and deployment description; Capital Memory workflow; 54-criterion Eval Agent; 500-judgment agreement result; mandate-deviation detection; comparative cost and speed; customer savings; usage and adoption figures
Supports: OpenAI published a Terminal X customer story on October 20, 2026. It reports Terminal X-provided results for an investment-workflow Eval Agent using GPT-6.1 Sol, including 88.6% agreement with a senior reviewer across 500 scored judgments, 25% higher mandate-deviation detection and about 30% lower cost per query than an unnamed next-best model.
Reviewed: Current product positioning; Capital Memory; data, workflow, trace, editing, report, evaluation and delivery stages; on-premise deployment statement; booking-based access; real-time evaluation claims
Supports: Terminal X currently markets an investment-team AI platform that combines firm data, workflows and memory, exposes agent steps and sources, evaluates changes against answer keys from customer work, and is offered through a book-a-demo motion with on-premise deployment.
Reviewed: Current model identifier and positioning; text and image input; context and output limits; reasoning levels; Responses and Chat Completions support; tools; batch and residency availability; long-context and regional price qualifications
Supports: OpenAI currently documents gpt-6.1-sol as an available API model with a 1,050,000-token context window, 128,000 maximum output, five reasoning-effort levels, Responses API tools, Batch support, and US and EU data-residency options subject to documented constraints.
Reviewed: Standard GPT-6.1 Sol short- and long-context token tables; cache-write and cached-input rates; Batch, Flex and Fast processing; long-context threshold; regional-processing uplift
Supports: The current Standard short-context table lists GPT-6.1 Sol at $2 input, $0.10 cached input, $2.50 cache writes and $10 output per million tokens. Requests over 272,000 input tokens use higher rates for the full request, and processing modes and regional routing can change the price.
Reviewed: Model positioning; September 2026 launch; vendor capability claims; standard token prices; coding, professional-work and computer-use sections; pricing and availability
Supports: OpenAI introduced GPT-6.1 Sol in September 2026 for coding, computer use and professional work, positioning it between Astra and Luna. The launch article provides vendor-run model results and list-price context, not independent validation of Terminal X performance.
AccessAllGPT reviewed four Hugging Face-controlled public surfaces on October 20, 2026: the dated launch article, immutable AnyLanguageModel 1.0.0 GitHub release, tagged README, Package.swift and Apache-2.0 license, and the companion swift-huggingface and linked swift-xet 1.0 release notes. We checked the announcement and artifact chronology, installable version, platform requirements, provider and runtime list, shared features, package traits, license, credential guidance and breaking migrations. Capability and compatibility statements are project claims. AccessAllGPT did not install Xcode 26.4 or Swift 6.3, resolve the package, build an Apple or Linux application, download a model, invoke a hosted API, test tool calling or guided generation, measure binary size, latency, memory, energy, quality or cost, audit dependencies, or submit an app for Apple review.
Reviewed: October 20 publication date; 1.0 release announcement; drop-in API claim; local and hosted provider list; tool calling, guided generation and image support; Linux support; example local models; upgrade guidance; future-work statements
Supports: Hugging Face announced the AnyLanguageModel 1.0 milestone on October 20 and describes one Swift session API spanning Apple Foundation Models, local Core ML, MLX and llama.cpp backends, and multiple hosted model APIs. It also identifies swift-huggingface 1.0 and swift-xet 1.0 as companion releases.
Reviewed: Immutable 1.0.0 tag and commit; October 13 artifact date; breaking JSONValue and @Generable changes; swift-huggingface 1.0 requirement; JSON Lines streaming; prompt attachments; Linux cancellation; release comparison and source availability
Supports: The canonical repository exposes an immutable 1.0.0 release dated October 13, 2026. Its migration notes identify source and generated-content incompatibilities and require swift-huggingface 1.0, while the tagged code and release are publicly available.
Reviewed: Tagged installation and usage documentation; supported local and hosted providers; Swift and operating-system requirements; package traits and dependency-resolution workaround; credential guidance; tool-execution delegate; Apache-2.0 license; tagged Package.swift platform declarations
Supports: The tagged project requires Swift 6.3 and Xcode 26.4, supports iOS 17, macOS 14, visionOS 1 and Linux, and ships under Apache 2.0. Optional CoreML, MLX and Llama traits add their respective local runtimes; hosted providers retain their own credentials, usage prices and terms.
Reviewed: swift-huggingface October 9 release; swift-xet 1.0 dependency; public API changes; bucket downloading; provider and error-type migrations; linked swift-xet October 6 release; stable downloader API; error and configuration migrations; multipath default change
Supports: The companion download stack reached 1.0 before AnyLanguageModel: swift-xet on October 6 and swift-huggingface on October 9. Both releases stabilize public APIs but include breaking migrations that applications with direct dependencies must review.
AccessAllGPT reviewed three Google-controlled public surfaces on October 20, 2026: the October 19 co-creation announcement, the current Gemini Notebook plan comparison and Google’s August 28 compute-limit notice. We compared the exact creation sequence, review controls, optional fast path, rollout language, plan positioning and limit mechanics. Capability and availability statements remain vendor claims. AccessAllGPT did not sign in, receive the rollout, upload sources, generate or edit a deck or video, inspect citations or prompts, identify the underlying model, compare account tiers, exhaust a quota, measure rendering time, or test factual accuracy, source fidelity, visual quality, accessibility, export behavior or pricing.
Reviewed: October 19 publication date; source-based topic suggestions; Review toggle; outline and producer-note review; feedback loop; direct-to-review prompting; optional fast path; global rollout timing and intended user scope
Supports: Google says Gemini Notebook is adding a guided co-creation flow for Slide Decks and Video Overviews. Users can approve suggested topics, review outline or producer notes, request changes before rendering, or skip review. Google says the capabilities are rolling out globally to all users during the week following October 19.
Reviewed: Standard and paid plan comparison; Slides and artifact generation; usage-limit multipliers; model-access descriptions; feature-access labels; source limits; regional plan caveat; organization and education routes
Supports: Google’s current plan page includes Slide generation in the standard Gemini Notebook plan, lists higher limits and access levels for AI Plus, Pro and Ultra, and says paid plans are region-dependent. It does not assign a separate price or quota to the new co-creation controls.
Reviewed: Compute-specific limits; five-hour refresh; prompt, chat, source and feature factors; alternative-output suggestions; deferred Slide Deck and Video Overview generation; notification option; consumer web and mobile rollout
Supports: Google says consumer limits refresh every five hours and vary with prompt complexity, chat length, source count and feature choice. Slide Decks and Video Overviews can be deferred when an account reaches its current allowance, so the new review flow does not imply unlimited or immediate rendering.
AccessAllGPT reviewed four first-party or project-controlled public surfaces on October 20, 2026: the PyTorch launch post, Hugging Face integration post, live AWS Neuron 2.33 documentation and canonical AWS GitHub repository. We reconciled announcement and availability dates; release status; supported hardware and PyTorch line; execution, distribution and profiling surfaces; library integration; published coverage claims; known gaps; license and artifact availability. Vendor and project claims are labeled as such. AccessAllGPT did not provision a Trainium instance, install Neuron 2.33, run a model, reproduce the 100,000-model sweep, inspect its fixtures, measure fallback frequency, compile time, throughput, latency, numerical parity or cost, or compare Trainium with a GPU.
Reviewed: October 19 announcement and October 20 public-beta chronology; Trainium2 and Trainium3 support; eager, adaptive eager and torch.compile modes; distributed APIs; NKI and profiling; Hugging Face and TorchTitan integrations; model-coverage methodology; upstream-test skips; install and open-source availability
Supports: The launch post announces TorchNeuron as an Apache-2.0 native PyTorch backend for Trainium, scheduled for public beta on October 20. It documents eager and compiled execution, standard distributed APIs, profiling and NKI, while identifying unsupported operations and features in the first release.
Reviewed: October 19 publication and October 20 availability statement; migration from Optimum Neuron; Transformers inference and training; supported-library list; architecture-coverage claim; static-shape, async-loading and compilation constraints; Diffusers and Hub kernel examples
Supports: Hugging Face says Transformers, Diffusers, Accelerate, PEFT and TRL now use Trainium through the native backend. It reports out-of-box support for 89% of the top 100 text-generation architectures versus 46% with Optimum Neuron 0.4.5, and documents important static-shape and asynchronous-loading caveats.
Reviewed: Neuron 2.33 public-beta status; Trn2 and Trn3 scope; PyTorch 2.14 autoloading; execution modes; operator fallback and compile-failure behavior; supported data types; cache and recompilation behavior; inference, distributed training and NKI support; open-source and legacy-version guidance
Supports: The live AWS documentation confirms public beta in Neuron 2.33 on Trn2 and Trn3, identifies PyTorch 2.14 as the native-backend line, explains CPU fallback in eager mode versus default compile failure for unsupported lowering, and recommends TorchNeuron for new PyTorch 2.14 workloads.
Reviewed: Public repository status; main branch; 2.33.0 release commit and tag; repository description; source tree; Apache-2.0 license; README installation and platform scope
Supports: The canonical repository is publicly readable and exposes the TorchNeuron source, documentation, tests and 2.33.0 release under the Apache-2.0 license. This verifies that the promised open-source artifact is live rather than merely announced.