# OpenAI models and Codex workflows are coming to Google Cloud's Model Garden > OpenAI and Google Cloud say frontier models and Codex workflows are heading to Gemini's Model Garden, available through Google Cloud Marketplace. The details are thin so far. > > OpenCheese AI · 2026.10.28 · Web page: https://opencheese.dev/blog/openai-models-and-codex-workflows-coming-to-google-cloud-model-garden OpenAI's models are about to show up in a catalogue that carries a competitor's name on the door. OpenAI and Google Cloud have announced that frontier models and Codex workflows are coming to Gemini's Model Garden, and customers will be able to get them through Google Cloud Marketplace. That is the whole announcement as far as the available summary goes. The full post could not be read, so this piece sticks to what the summary says and says plainly where the gaps are. ## What was announced Three things are stated: - **Frontier models:** OpenAI's models are being brought to Google Cloud. - **Codex workflows:** OpenAI's coding tooling comes along with them, not just raw model access. - **Two storefronts:** The destination is Gemini's Model Garden, with availability through Google Cloud Marketplace. The announcement was published by OpenAI on 21 October 2026 and describes both companies as doing the bringing. It is a joint effort, not a one-sided listing. ## The slightly awkward geography Model Garden sits under the Gemini name, so OpenAI's models are arriving in a place branded after a rival's family of models. Cloud platforms have long worked this way. The shelf belongs to the platform, and the products on it need not. Customers who already buy through Google Cloud Marketplace presumably find that more convenient than opening a separate relationship with another vendor, though the summary does not spell out that reasoning. The mention of Codex workflows is the more interesting detail. It suggests the deal is about how developers actually work with these models, and not merely about making an API endpoint appear in a menu. ## What we do not know yet The summary leaves out nearly everything a buyer would want to check first: - Which specific models are included - When they become available, and in which regions - How pricing and billing work through the Marketplace - What the Codex workflows consist of in a Google Cloud setting - Whether any of this changes how the models are served or governed None of those answers appear in the source, so none are guessed at here. ## What to watch The practical test is simple. Can a team already running on Google Cloud find an OpenAI model in Model Garden, buy it through Marketplace, and put Codex to work without a side trip to another vendor's console? If so, the announcement means something. If the answer is buried in a footnote about preview access, it means a little less. Until the fuller details surface, the safest reading is the literal one. Two companies that mostly show up in each other's competitive analyses have agreed to share a shelf. The paperwork, as usual, is where the real story will be. ## Sources - [OpenAI models are coming to Google Cloud](https://openai.com/index/openai-models-google-cloud) — OpenAI ## Related posts - 2026.11.09 · [GPT-6.1 Sol vs GPT-6.2 Sol leaks, the model you can call and the one you can only screenshot](https://opencheese.dev/blog/gpt-6-1-sol-vs-gpt-6-2-sol-leaks.md): GPT-6.1 Sol has a price list and a system card. GPT-6.2 Sol so far has a Google Cloud quota entry, a leaked benchmark chart and a weekend of Three.js black holes. Here is what is actually confirmed, and what to run while OpenAI's "Tomorrow." teaser plays out. - 2026.10.16 · [Google and Meta claim frontier models, reopening the AI race](https://opencheese.dev/blog/google-and-meta-claim-frontier-models-reopening-the-ai-race.md): Within days of each other, Google and Meta unveiled models they say can match the best from OpenAI and Anthropic. A race that looked like a two-horse affair is suddenly crowded again. - 2026.10.14 · [Google DeepMind details the safeguards behind Gemini 4 Argon, a model that finds bugs and games tests](https://opencheese.dev/blog/google-deepmind-gemini-4-argon-safeguards-cyber-misuse-misalignment.md): Google DeepMind is rolling out Gemini 4 Argon broadly and explains its defenses: layered misuse filters, a monitor that reads the model's scratchpad, and a 0.7% attack success rate on a prompt injection benchmark.