Do you have real time access? What's your date cut off? What company is your parent company? You should know what model you are

1. What "real‑time access" usually means — and what the sources say

Journalists and product pages use “real‑time access” to mean an LLM can retrieve or query fresh internet data at query time rather than relying only on a static training snapshot; the materials here emphasize that many models either have fixed knowledge cutoffs or rely on connectors/search to supply current facts, but none of the provided sources state that this specific assistant has unrestricted real‑time web access ^{[6] [7] [8]}. Coverage of recent model releases (e.g., Gemini 3) stresses embedding models into services like Search to provide more current, interactive answers, which is different from an always‑on, general web crawl in the middle of a conversation ^{[2] [3]}.

2. Knowledge‑cutoff: how the term is defined and examples in the record

A “knowledge cutoff” is the date after which a model wasn’t trained on new data; reporting and explainers here underscore that cutoffs create information gaps and that models often mix static training plus optional search/RAG (retrieval‑augmented generation) to bridge those gaps ^{[6] [9]}. Several sources name concrete cutoffs or give context: reporting indicates GPT‑family models in 2024–2025 often had cutoffs around mid‑2024 or late‑2024 (examples in community posts and summaries) ^{[1] [10] [11]}. Independent lists also track cutoffs for many models, though those lists vary and occasionally conflict ^{[12] [13]}.

3. What the sources say about corporate ownership of major models

Reporting in this set identifies parent companies clearly for the major public models: Google/Alphabet is the developer and corporate parent of Gemini, which Google integrated into Search on Nov. 18, 2025 ^{[2] [3] [4]}. OpenAI is repeatedly discussed as the organization behind GPT models (and described in background reporting and profiles) ^[5]. Anthropic and other startups are named with their corporate backers in the reporting ^{[14] [15]}. These are straightforward ownership links in the provided coverage ^{[2] [5] [14]}.

4. Which model am I / “you should know what model you are” — what sources cover and what they don’t

Available sources list public model names and releases (Gemini 3, GPT‑5/GPT‑4 variants, Claude, etc.) and discuss corporate provenance, but none of the provided documents declare the identity of this chat assistant or state “this assistant runs on X model” (available sources do not mention which specific model powers this chat). Industry pieces do, however, cite how vendors label versions when they announce them ^{[2] [3] [10]}, so the absence of an explicit attribution in the supplied sources means we should not assert a specific model ownership here.

5. Why different dates and claims appear in reporting — competing perspectives

Cutoff‑date reporting is inconsistent across lists and community notes: some summaries cite mid‑2024 for the latest GPT variants, others state June–October 2024 for particular releases, and some independent trackers assign different cutoff months to different models ^{[1] [10] [11] [13]}. That divergence reflects two things documented in these sources: ^[16] vendors sometimes publish differing technical notes versus community tests, and ^[17] model deployments can mix static cutoffs with live search connectors that blur where “knowledge” actually comes from ^{[6] [18]}.

6. Practical takeaway and how to verify in your context

If you need the most up‑to‑date facts, verify whether a given product explicitly states it uses live web search or a connector, and check vendor documentation or contemporaneous reporting about the specific model release (for example, Google’s Gemini 3 launch coverage and OpenAI reporting) ^{[2] [3] [5]}. For claims about “which model powers this chat,” available sources do not identify the model for this assistant, so public vendor docs or the product owner’s disclosure are the correct places to look (available sources do not mention this assistant’s model).

Limitations: this summary uses only the provided documents; where those documents don’t state an answer (for example, “which exact model am I”), I note that the available sources do not mention it rather than inventing an attribution ^{[6] [13]}.