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Large Language Models (LLMs) have transformed how we interact with artificial intelligence, offering impressive capabilities in generating human-like text. However, these models come with important limitations, notably their knowledge cutoff dates.
Latest Updates
Last checked: November 5, 2026.
- GPT-6.1 Terra (OpenAI) has a knowledge cutoff of June 1, 2026 and was released on October 26, 2026.
- Claude Haiku 5.5 has a knowledge cutoff of June 2026 and was released on October 7, 2026.
- Gemini 4 Argon has a knowledge cutoff of March 2026 and was released on October 13, 2026. Knowledge in some domains may be less current.
- Kimi K3.1 Pro (Moonshot AI) has a knowledge cutoff of Not publicly disclosed and was released through the API on October 23, 2026. Full weights are announced for November 4.
What are AI Knowledge Cutoff Dates?
A knowledge cutoff date represents the point in time beyond which an LLM has no inherent knowledge of events, developments, or information. This date is determined by when the model’s training data was last updated before final training completion. Unlike humans who continuously learn, LLMs have their knowledge “frozen” at a specific temporal point unless deliberately updated or augmented with additional tools.
Knowledge cutoff dates exist primarily due to practical limitations in the training process. Training an LLM requires immense computational resources and time, often taking weeks or months to complete. This makes continuous training logistically challenging and economically impractical. Once trained, an LLM’s core knowledge remains static until a deliberate retraining or update occurs.
OpenAI and ChatGPT knowledge cut-off dates
| Model Name | Type | Knowledge Cut-off date | Public Release Date |
|---|---|---|---|
| GPT-6.1 Terra | Reasoning | June 1, 2026 | October 26, 2026 |
| GPT-6.1 Sol | Reasoning | April 30, 2026 | September 29, 2026 |
| GPT-6 Sol | Reasoning | April 20, 2026 | September 22, 2026 |
| GPT-6 Luna | Reasoning | May 18, 2026 | September 22, 2026 |
| GPT-6 Astra | Reasoning | April 30, 2026 | September 03, 2026 |
| GPT-5.6 Sol | Reasoning | February 16, 2026 | July 09, 2026 |
| GPT-5.6 Terra | Reasoning | February 16, 2026 | July 09, 2026 |
| GPT-5.6 Luna | Reasoning | February 16, 2026 | July 09, 2026 |
| GPT-5.5 | Reasoning | December 01, 2025 | April 23, 2026 |
| GPT-5.4 | Reasoning | August 31, 2025 | March 05, 2026 |
| GPT-5.3 Instant | Reasoning | August 31, 2025 | March 03, 2026 |
| GPT-5.3 Codex | Agentic coding | August 31, 2025 | February 05, 2026 |
| GPT-5.2 | Reasoning | August 31, 2025 | December 11, 2025 |
| GPT-5.1 | Reasoning | September 30, 2024 | November 12, 2025 |
| GPT-5 | Reasoning | September 30, 2024 | August 7, 2025 |
| GPT-oss-20b | Cost-optimized Chat, Open-Source | June 01, 2024 | August 5, 2025 |
| GPT-oss-120b | Chat, Open-Source | June 01, 2024 | August 5, 2025 |
| GPT-4.5 (Research Preview) | Reasoning | October 01, 2023 | February 2, 2025 |
| o4-mini-high | Reasoning | June 01, 2024 | April 16, 2025 |
| o4-mini | Reasoning | June 01, 2024 | April 16, 2025 |
| o3 | Reasoning | June 01, 2024 | April 16, 2025 |
| o3-mini | Reasoning | October 01, 2023 | January 31, 2025 |
| o1 | Reasoning | October 01, 2023 | September 12, 2024 |
| o1-mini (deprecated) | Reasoning | October 01, 2023 | September 12 2024 |
| GPT-4 | Chat | September 01, 2021 | March 14, 2023 |
| GPT-4.1 | Chat | June 01, 2024 | April 14, 2025 |
| GPT-4o | Chat | October 01, 2023 | May 13, 2024 |
| GPT-3.5 Turbo | Chat | September 01, 2021 | January 24, 2024 |
| GPT-3.5 | Chat | September 01, 2021 | March 15, 2022 |
| GPT-3 | Chat | October 01, 2020 | November 01, 2021 |
| ChatGPT-4o | Chat | October 01, 2023 | May 13, 2024 |
| o4-mini | Cost-optimized Chat | June 01, 2024 | April 16, 2025 |
| GPT-4.1 mini | Cost-optimized Chat | June 01, 2024 | April 14, 2025 |
| GPT-4.1 nano | Cost-optimized Chat | June 01, 2024 | April 14, 2025 |
| o3-mini | Cost-optimized Chat | October 01, 2023 | January 31, 2025 |
| GPT-4o mini | Cost-optimized Chat | October 01, 2023 | July 18, 2024 |
| o1-mini (deprecated) | Cost-optimized Chat | October 01, 2023 | September 12, 2024 |
| GPT-4o Search Preview | Chat Completion with Web Search | October 01, 2023 | March 11, 2025 |
| GPT-4o mini Search Preview | Chat Completion with Web Search | October 01, 2023 | March 11, 2025 |
Anthropic (Claude) knowledge cut-off dates
| Model Name | Knowledge Cutoff Date | Release Date |
|---|---|---|
| Claude Haiku 5.5 | June 2026 | October 7, 2026 |
| Claude Sonnet 5.5 | June 2026 | September 28, 2026 |
| Claude Opus 5.5 | June 2026 | September 22, 2026 |
| Claude Fable 5.1 | June 2026 | September 1, 2026 |
| Claude Fable 5 | January 2026 | June 09, 2026 |
| Claude Opus 5 | May 2026 | July 24, 2026 |
| Claude Opus 4.8 | January 2026 | May 28, 2026 |
| Claude Opus 4.7 | January 2026 | April 16, 2026 |
| Claude 4.6 Sonnet | August 2025 | January 17, 2026 |
| Claude 4.6 Opus | May 2025 | February 5, 2026 |
| Claude 4.5 Opus | March 2025 | November 24, 2025 |
| Claude 4.5 Haiku | February 2025 | October 15, 2025 |
| Claude 4.5 Sonnet | January 2025 | September 29, 2025 |
| Claude 4.1 Opus | January 2025 | August 5, 2025 |
| Claude 4 Opus | January 2025 | May 22, 2025 |
| Claude 4 Sonnet | January 2025 | May 22, 2025 |
| Claude 3.7 Sonnet | October 2024 | February 2025 |
| Claude 3.5 Sonnet | April 2024 | October 2024 |
| Claude 3 Opus | March 2023 | August 2023 |
| Claude 3.5 Haiku | October 2024 | April 2024 |
GEMINI (Google / Alphabet) knowledge cut-off dates
| Model Name | Knowledge Cutoff Date | Release Date |
|---|---|---|
| Gemini 4 Argon | March 2026 | October 13, 2026 |
| Gemini 3.8 Flash | March 2026* | September 2, 2026 |
| Gemini 3.7 Flash | March 2026* | August 13, 2026 |
| Gemini 3.6 Flash | March 2026* | July 21, 2026 |
| Gemini 3.5 Flash-Lite | March 2026* | July 21, 2026 |
| Gemini 3.5 Flash | January 2025 | May 19, 2026 |
| Gemini 3.1 Flash Lite | January 2025 | March 03, 2026 |
| Gemini 3.1 Pro | January 2025 | February 19, 2026 |
| Gemini 3 | January 2025 | November 18, 2025 |
| Gemini 2.5 Pro | January 2025 | March 25, 2025 |
| Gemini 2.5 Flash | January 2025 | March 25, 2025 |
| Gemini 2.0 Flash | August 2024 | January 30, 2025 |
* Google reports a March 2026 cutoff for Gemini 3.8 Flash, 3.7 Flash, 3.6 Flash, and 3.5 Flash-Lite, while noting that knowledge in some domains remains limited to January 2025. A newer cutoff does not guarantee complete coverage of every topic.
Google Gemma open-weight models
| Model Name | Knowledge Cutoff Date | Release Date |
|---|---|---|
| Gemma 4 12B Unified | January 2025 | June 3, 2026 |
| Gemma 4 | January 2025 | March 31, 2026 |
Mistral AI knowledge cut-off dates
| Model Name | Knowledge Cutoff Date | Release Date |
|---|---|---|
| Mistral Large 4 | Not publicly disclosed | October 6, 2026 |
| Mistral Medium 3.5 | Not publicly disclosed | April 28, 2026 |
| Mistral Small 4 | June 2025 | March 2026 |
| Mistral Large 3 | December 2025 | December 2025 |
| Mistral Large 2 | October 2023 | November 2024 (current version) |
| Mistral Small 3.1 | October 2023 | March 2025 (current version) |
Mistral’s model documentation dates Medium 3.5 to April 28, 2026; its Vibe remote-agents announcement featuring the model was published on May 22, 2026. Neither the linked specifications nor the model card discloses a knowledge cutoff.
Other AI Model cut-off dates
| Model Name | Provider | Knowledge Cutoff Date | Release Date |
|---|---|---|---|
| Kimi K3.1 Pro | Moonshot AI | Not publicly disclosed | October 23, 2026 |
| Nemotron 3.5 Bolt E4B | NVIDIA | May 2026 (post-training data) | October 23, 2026 |
| DeepSeek V4.1 Flash 1017 | DeepSeek | Not publicly disclosed | October 17, 2026 |
| Muse Spark Open | Meta | Not publicly disclosed | October 15, 2026 |
| Nemotron 3.5 Bolt 74B-A9B | NVIDIA | May 2026 (post-training data) | October 15, 2026 |
| Granite Switch 4.1 (8B, 30B) | IBM | Not publicly disclosed | October 14, 2026 |
| Muse Wonder | Meta | Not publicly disclosed | October 12, 2026 |
| Kolibri | Aleph Alpha | EN: June 18, 2026; DE: June 18, 2026 | October 3, 2026 |
| MiMo-V2.6 Pro / Flash | Xiaomi | Not publicly disclosed | September 22, 2026 |
| Grok 4.7 | xAI | May 2026 | September 21, 2026 |
| DeepSeek V4.1 Flash | DeepSeek | Not publicly disclosed | September 10, 2026 |
| North Small Translate | Cohere | Not publicly disclosed; family data collection through June 2026 | September 9, 2026 |
| Muse Spark 1.3 | Meta | Not publicly disclosed | September 2, 2026 |
| Granite 4.2 (3B, 8B, 30B) | IBM | Not publicly disclosed | August 25, 2026 |
| GLM-5.3 | Z.ai | Not publicly disclosed | August 18, 2026 |
| Nemotron 3.5 Lightning | NVIDIA | September 2025 (pre-training); May 2026 (post-training) | August 11, 2026 |
| MAI-Code-1.1-Flash | Microsoft | December 2025 (pre-training); data collected as late as July 2026 | August 11, 2026 |
| Kimi K3 | Moonshot AI | Not publicly disclosed | July 22, 2026 |
| Kimi K2.7 Code | Moonshot AI | Not publicly disclosed | June 16, 2026 |
| Command A+ | Cohere | April 1, 2025 | May 20, 2026 |
| Kimi K2.6 | Moonshot AI | Not publicly disclosed | April 21, 2026 |
| Nova 2 Lite | Amazon | October 2025 | December 2, 2025 |
| Llama 4 | Meta | August 2024 | April 5, 2025 |
| Llama 3 | Meta | December 2023 | April 18, 2024 |
| DeepSeek R1 | DeepSeek | October 2023 (presumed) | January 25, 2025 |
| DeepSeek V3 | DeepSeek | July 2023 (presumed) | December 26, 2024 |
Newly listed models with no cutoff in the checked official documentation are marked Not publicly disclosed. NVIDIA’s Bolt dates describe post-training data, not a comprehensive knowledge cutoff. Microsoft’s MAI-Code-1.1-Flash specifies a December 2025 pre-training cutoff and data collection as late as July 2026; its October 7 on-device release is later than its original August 11 release.
Perplexity knowledge cut-off dates
All Perplexity Sonar models integrate real-time web search capabilities, allowing them to provide information beyond their training data’s cutoff dates.
The Distinction Between Knowledge and Retrieval
An important distinction exists between an LLM’s inherent knowledge (limited by its cutoff date) and its ability to access current information through integrated tools like web browsing capabilities. For instance, while ChatGPT’s built-in knowledge might end at a specific date, when equipped with browsing capabilities, it can retrieve and process current information beyond its cutoff date.
This distinction helps explain why some users experience confusion when an LLM claims it doesn’t know about events after its cutoff date but can still answer questions about recent events when given web access.
Effective vs. Reported Cutoffs
Different sub-resources within an LLM’s training data may have varying effective cutoff dates. This means that an LLM’s knowledge isn’t uniformly cut off at a single point in time across all domains or topics. Instead, knowledge about different subjects might be current up to different dates.
This variation occurs due to two primary factors:
- Temporal misalignments in CommonCrawl data, where newer data dumps contain significant amounts of older information
- Complications in deduplication schemes involving semantic duplicates and lexical near-duplicates
These findings suggest that users should approach cutoff dates with nuance, understanding that an LLM’s knowledge might be more current in some domains than others, regardless of the officially reported cutoff date. However, the officially reported cutoff date as reported above are still a great guidance for marketers aiming to understand which training data is considered in LLM responses about their company.
Why knowledge cut off dates matter for LLMO/GEO
LLMO, GEO and ALLMO are all terms that describe the emerging practice of optimizing brand visibility inside AI-generated answers rather than traditional search engines.
Knowledge cut-off dates are crucial to consider because language models like ChatGPT often only know information up to a certain date (their training cut-off). This means content you optimize and publish today might not appear in a model’s answers if the model was trained before your content existed, however that does not mean you are out of the game. Based on our research at ALLMO.ai, a leading platform helping companies analyze and improve their visibility in AI-generated answers, here is why it’s still important:
- Todays’ content is used to train tomorrows LLMs. You may not see immediate impact, but strategic positioning is important to find your way into the training data of future versions, potentially boosting your visibility in AI-generated answers going forward.
- Many modern AI chatbots can perform a live web search to access more recent information: whenever their built-in knowledge is outdated or limited, so having current, well-structured content on the web makes it more likely the AI will find and reference your material in its responses.
- Spot and fill gaps in your current content marketing efforts by understanding what static models can’t answer due to outdated knowledge, which increases the chance your site will be cited as a source either when the model’s training data is updated.
Most AI companies release one to two major updates per year, along with several smaller updates throughout the year—sometimes including refreshed knowledge based on more recent training data. While the immediate impact of these updates may seem small, the long-term benefit is significant: once your content finds its way into a large language model (LLM), it can influence responses for months. This stands in contrast to traditional SEO or LLMs with web-browsing capabilities, where indexed information can change daily. As a side note, it’s important to remember that even static models can produce different answers due to parameters like “temperature,” which introduce a degree of randomness. Producing relevant, high-quality content helps both immediate visibility in AI search and ensures a more consistent, reliable presence in static AI models.
Sources:
- OpenAI: GPT-6.1 Terra official documentation
- Google: Gemini 4 Argon general availability
- Google DeepMind: Gemini 4 Argon model card
- Anthropic: Claude Haiku 5.5 specifications and release date
- Mistral: Large 4 API preview launch
- Mistral: Large 4 specifications
- Google: Gemma 4 model card
- Google: Gemma release dates
- Z.ai: original model release notes
- OpenAI: GPT-6.1 Sol model specifications
- OpenAI: GPT-6.1 Sol system card addendum, September 29, 2026
- Anthropic: Claude Sonnet 5.5 model specifications
- Anthropic: Claude Sonnet 5.5 launch announcement
- Anthropic: Claude Fable 5.1 model specifications
- Google: Gemini API release notes
- Google DeepMind: Gemini 3.8 Flash model card
- Google DeepMind: Gemini 3.7 Flash model card
- Google DeepMind: Gemini 3.6 Flash model card
- Google DeepMind: Gemini 3.5 Flash-Lite model card
- xAI: model announcements
- Mistral: Medium 3.5 model specifications
- Mistral: Medium 3.5 model card
- Mistral: Medium 3.5 and Vibe announcement
- Anthropic: Claude Opus 5.5 model specifications
- OpenAI: GPT-6 Sol model specifications
- OpenAI: GPT-6 Luna model specifications
- OpenAI: GPT-6 Sol and Luna launch announcement
- OpenAI: ChatGPT release notes, September 22, 2026
- https://platform.openai.com/docs/models
- https://openai.com/news/
- https://en.wikipedia.org/wiki/Gemini%5F%28language%5Fmodel%29
- https://docs.mistral.ai/getting-started/models/models%5Foverview/
- https://ai.google.dev/gemini-api/docs/models?hl=de
- https://platform.claude.com/docs/en/about-claude/models/overview
- Own experimentation & prompts with LLMs.
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