Generative AI Knowledge Cutoff Dates Compared: ChatGPT, Claude, Gemini & More

1. What Is a Knowledge Cutoff Date?

Have you ever asked an AI about recent news only to get a reply like "my training data only goes up to [date]"? That date is the knowledge cutoff.

AI models are built by training on massive text datasets, but those datasets have a hard deadline. For any events or information published after the cutoff, the model on its own cannot give an accurate answer.

That said, many modern AI tools now include web search, which lets them fetch up-to-date information beyond the cutoff. The key is understanding the difference between what the model "knows" natively and what it can look up in real time.

2. Cutoff Date Comparison Table

Here is a side-by-side look at cutoff dates for the major AI tools as of September 29, 2026.

As of September 29, 2026, the most recent are Claude's Claude Opus 5.5 (released September 22, 2026) and the higher-tier Claude Fable 5.1 (released September 1), both at June 2026. Claude Sonnet 5.5, released on September 28, also has a June 2026 cutoff. Next come Grok 4.7 at May 2026 and OpenAI's low-cost GPT-6 Luna at May 18, 2026. ChatGPT's flagship GPT-6 Astra follows at April 30, 2026, and Gemini 3.8 Flash at March 2026 (Gemini 4 Argon, generally available since October 13, is also March 2026). Meta does not publish a cutoff for Muse Spark or for the preview Muse Wonder (released October 12), and Mistral does not publish one for its models. Among the open-weight models in this list that publish a cutoff, Meta's Muse Glimmer (January 4, 2026) is the most recent (Muse Spark Open, released October 15, does not state one in its developer documentation), while Llama 4 stops at August 2024. In September, Anthropic, Google and OpenAI shipped new models between the 1st and the 3rd, and xAI, Anthropic and OpenAI did so again on the 21st and 22nd, so this ranking changed between the start and the end of the month.

3. ChatGPT (OpenAI)

This OpenAI section was updated on September 30, 2026. The eight-tool overview above is as of September 29; the GPT-6.1 Sol addition is reflected only here.

OpenAI's highest-tier model is GPT-6 Astra, with a knowledge cutoff of April 30, 2026 (OpenAI API documentation). GPT-6.1 Sol joined Codex and ChatGPT Work on September 29, 2026. Its cutoff is also April 30, 2026, while the earlier GPT-6 Sol has an April 20, 2026 cutoff and the low-cost GPT-6 Luna has a May 18, 2026 cutoff. A newer model name does not necessarily mean newer knowledge (see the GPT-6.1 Sol specifications and GPT-6 Sol and Luna details). GPT-5.6 Sol, Terra and Luna remain available, with a shared cutoff of February 16, 2026.

Here is a quick rundown of cutoff dates for the current and past major models:

All ChatGPT models have access to Bing-powered web search, so they can retrieve information past the cutoff. Search results include source links, making it easy to verify claims.

4. Claude (Anthropic)

Anthropic's Claude takes a unique approach with a two-tier cutoff system:

• Reliable knowledge cutoff — Information up to this date is answered with high confidence.
• Training data cutoff — Data is included but accuracy may be slightly lower.

Claude does not have built-in web search, but it can access external information through the Agent SDK and tool integrations. In Claude Code, the WebSearch tool is available for real-time lookups.

5. Gemini (Google)

Google's Gemini stands out thanks to its deep integration with Google Search. The top model, Gemini 4 Argon (announced September 30, generally available October 13), has a knowledge cutoff of March 2026 (model card), and the workhorse Gemini 3.8 Flash (released September 2, 2026) shares the same March 2026 cutoff. Both can fill in the gaps with real-time data from Google Search (as of October 14, 2026). Gemini 3.1 Pro, billed as the most capable model until Argon arrived, is still offered as a preview.

Older generations deserve a note too. On September 18, 2026, Google limited access to the Gemini 2.5 models to users who had actively used them before. They are not deprecated and are still served through the API, but Google advises new projects to use 3.8 Flash or 3.5 Flash-Lite. On October 8, Gemini 3.5 Flash and 3.7 Flash were deprecated, and API requests to them are now automatically routed to 3.6 Flash and 3.8 Flash respectively (Gemini API release notes). Anything new you build is now expected to run on Gemini 3 or later (4 Argon, 3.8 Flash and so on).

Gemini's biggest advantage is its tight integration with the Google ecosystem — Gmail, Google Docs, Sheets, and more — making it especially useful for business workflows.

6. Grok (xAI)

Elon Musk's xAI built Grok with real-time access to X (formerly Twitter) data. The model's own knowledge has a cutoff, but it compensates with web search and live X post data.

The current Grok 4.7 was released on September 21, 2026, and xAI positions it as its frontier model for coding, agentic tasks and knowledge work (as of September 2026). Its knowledge cutoff is May 2026 (xAI API documentation). xAI's documentation also states that Grok has no knowledge of real-time events unless search tools are enabled. The generations just before it were Grok 4.6 (August 12, 2026) and Grok 4.5 (July 8, 2026). The earlier Grok 4.20 entered beta in February 2026 and launched its API in March, using a 3-trillion-parameter Mixture of Experts (MoE) architecture. Grok is also known for its distinctive, often humorous response style.

7. Microsoft Copilot / GitHub Copilot

Microsoft Copilot (Microsoft 365 Copilot, the work version) is not tied to one fixed model: you choose between OpenAI's GPT and Anthropic's Claude. From September 22, 2026, Claude Opus 5.5 and GPT-6 Sol began rolling out across Word, Excel, PowerPoint, Chat, Cowork and Copilot Studio (Microsoft Copilot Blog; availability varies by license and region). So the knowledge cutoff depends on the model you pick, with the same values as in the ChatGPT and Claude sections above. When web search is enabled, Copilot turns your prompt into a short query, sends it to Bing and uses the results to ground its answer (Microsoft Learn). Administrators can switch web search off, though, so a work account may not be able to pull in recent information.

GitHub Copilot focuses on code and lets you choose from more than 30 models from OpenAI, Anthropic, Google, xAI, Microsoft and Moonshot AI (GitHub Docs supported models list, as of September 26, 2026). For Business and Enterprise, GPT-5.3-Codex has been the designated base and long-term support (LTS) model since March 18, 2026, used when no other model is enabled. Here too, the cutoff is set by the model you choose.

8. Perplexity AI

Perplexity AI takes a different approach from other AI tools. It runs a web search for every question and builds the answer from several cited sources. The model that writes the answer still has a cutoff, but because the material is gathered fresh each time, how well it handles recent events depends on what the search turns up.

You can choose the model behind the answer. Alongside Perplexity's own Sonar, the list includes OpenAI's GPT, Anthropic's Claude, Google's Gemini, xAI's Grok and Moonshot AI's Kimi: eight models on the Pro plan, and ten on the higher Max plan, which adds two top-tier models (Perplexity Help Center, list as of September 4, 2026). Perplexity itself says the list changes and that your own model selector is the source of truth. On Max you can also use "Model Council," which sends the same question to several models and combines their answers.

9. Open-Weight Models (Meta, Llama & Mistral)

Open-weight models can be downloaded and run on your own hardware, which is their biggest advantage. However, they do not include web search out of the box. Both Meta and Mistral now release some models with open weights and keep others for their own apps and APIs.

Meta (Muse Glimmer and Llama 4)

In April 2026 Meta launched a new family of models called Muse. The latest is Muse Spark 1.3 (September 2, 2026), but it is a closed model whose weights are not released, and Meta's developer model list (Meta Model API docs) does not state a knowledge cutoff for it (as of September 26, 2026). On October 12, 2026, Meta released Muse Wonder, which it calls its "most capable" model, but the developer model list treats it as a preview and gives no knowledge cutoff. For new projects, Muse Spark 1.3 is still the recommended choice (confirmed October 18, 2026).

The newest open-weight model is Muse Spark Open (released October 15, 2026). It has 816B total parameters, with 42B active in a mixture-of-experts (MoE) design, and a context window of about 1 million tokens. It uses Meta's own Muse Model License: commercial use is allowed, but the work must carry the notice "Built with Muse Spark Open" (large-scale API provision is subject to conditions). Even the 4-bit version of the weights is about 537 GB and is aimed at data-center-class GPUs. Meta's materials do not state a knowledge cutoff (checked October 18, 2026).

A small open model you can run on your own PC is Muse Glimmer (released August 2026). It is a roughly 30-billion-parameter (30B) model trained from Muse Spark's outputs and licensed under Apache 2.0. Its model card gives a knowledge cutoff of January 4, 2026, more than a year later than Llama 4. According to the model card, 4-bit quantization shrinks the language model to under 20 GB so that it fits in 24 to 32 GB of memory.

The previous generation, Llama 4 (released April 5, 2025), comes in two variants, Scout (109B total parameters) and Maverick (400B), with a knowledge cutoff of August 2024 (Llama 4 model card). Scout has a 10-million-token context window.

Mistral (Mistral Medium 3.5, Large 3 and Large 4)

France-based Mistral now calls Mistral Medium 3.5 (April 28, 2026) its frontier-class model. It is a dense 128B model, and its weights are also released under a modified MIT license. In Mistral's model list it is the replacement for Mistral Medium 3.1, the Magistral Medium reasoning model and the Devstral 2 coding model, among others. The earlier large model, Mistral Large 3 (December 2, 2025), is a MoE with 675B total parameters (41B active) and remains available under Apache 2.0. On October 6, 2026, the next one, Mistral Large 4, arrived as a Public Preview. It is a MoE with 1.05T total parameters (52B active) and a 1M-token context window. The weights were released on October 29, 2026, as an improved version of the preview model, on Hugging Face (Mistral's announcement). The license is the Mistral Ecosystem Open-Weight License, a modified MIT license. Commercial use is allowed, but offering the model to others through an API or similar service (Model as a Service) requires a separate agreement with Mistral. Mistral's API still lists Large 4 as a Public Preview (as of November 1, 2026). Under Mistral's model lifecycle policy, preview models can be updated silently and have no guaranteed path to general availability.

Mistral does not list training-data cutoffs in its model list. The closest clue is the recommended system prompt (SYSTEM_PROMPT.txt) it ships on Hugging Face, which gives the "knowledge base last updated" date as November 1, 2024 for Medium 3.5 and October 1, 2023 for Large 3. That is text for the model to tell users, not a formally published training cutoff. The chat app "Le Chat" has been renamed Vibe, and its Work mode can search the web (Mistral docs).

10. How Web Search Changes the Game

Whether a knowledge cutoff matters in practice depends heavily on whether the tool supports web search.

Tools with web search can fetch information well past their cutoff dates. That said, the quality of search results varies by tool. In practice, Perplexity excels with thorough source citations, and ChatGPT's Bing integration is consistently reliable.

On the other hand, tools like Claude that excel in raw reasoning shine in tasks that don't require the latest information — code generation, data analysis, and complex problem solving. An older cutoff doesn't make a tool inferior; choosing the right tool for the task is what matters.

11. Best AI Tool for Each Use Case

There is no single "best AI." If you need the latest information, go with Perplexity or ChatGPT. For deep reasoning, choose Claude. For Google Workspace integration, pick Gemini. For privacy, run Llama or Muse Glimmer locally. Each tool has a distinct sweet spot.

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