OpenAI vs Google Vertex AI

A closed model lab against Google Cloud's full AI platform. OpenAI sells GPT models and agent tooling; Vertex sells Gemini, Claude and 200+ models inside an MLOps stack.

By The Subconscious Team · Updated September 30, 2026

OpenAI vs Google Vertex AI: key differences

OpenAI sells models. Vertex AI sells a platform. OpenAI's API gives direct access to GPT-6 Astra and the GPT-5.6 family with clear price tiers, a 1.05M window and cache and Batch discounts that stack. Vertex, recently rebranded the Gemini Enterprise Agent Platform, puts Gemini 3.8, Claude and open models like Gemma in Model Garden next to custom training on GPUs or TPUs, pipelines, a feature store, a model registry, vector search and BigQuery integration. The practical question is whether a team wants a model API or a place to build, train and govern everything on Google Cloud.

For pure inference, OpenAI is simpler to budget. Its tiers are published per model, while Vertex pricing is usage-based and split across every service, which reviewers call hard to forecast. Vertex wins when the data already lives in BigQuery, when a team wants Gemini's multimodal and video work, or when choosing among several labs matters more than any one model. The cost of that choice is lock-in, since pipelines, features and registries on Vertex are Vertex-native. OpenAI's lock-in sits at the model level, through closed weights and behavior changes between versions.

What OpenAI and Google Vertex AI do

OpenAI

OpenAI runs the most widely adopted closed-model API. Its September 2026 lineup has GPT-6 Astra at the top for computer use, coding and long agentic runs, priced at $10 in and $50 out per million tokens. Below it sits the GPT-5.6 family: Sol for hard professional work, Terra as the balanced default, and Luna for high-volume jobs at $0.20 in and $1.20 out. All of them carry a 1.05M token context window with up to 128K output.

Example models: GPT-6 Astra, GPT-5.6 Terra

Full OpenAI profile

Google Vertex AI

Vertex AI is Google Cloud's enterprise AI platform. At Google Cloud Next on April 22, 2026, Google rebranded it the Gemini Enterprise Agent Platform with an agent-first structure, though the API endpoint and most docs still say Vertex. Model Garden offers 200+ models, including Google's Gemini 3.8 family, Anthropic's Claude models and open models like Gemma, alongside Imagen, Veo and Chirp for media and speech. Google's own TPUs sit underneath much of its first-party serving.

Example models: Gemini 3.8, Claude

Full Google Vertex AI profile

Should you choose OpenAI or Google Vertex AI?

OpenAI

Choose OpenAI for

Teams that want one model API with published per-tier pricing
Computer use and coding agents on GPT-6 Astra
Hosted tools like web search and MCP without building a platform

Google Vertex AI

Choose Google Vertex AI for

Google Cloud shops keeping models close to BigQuery data
Running Gemini and Claude side by side under one governance layer
Custom training on TPUs next to inference

OpenAI vs Google Vertex AI at a glance

Attribute	OpenAI	Google Vertex AI
Model access	Closed, plus open gpt-oss	Closed and open, 200+ models
Flagship models	GPT-6 Astra, GPT-5.6 Sol, Terra, Luna	Gemini 3.8 Flash, Claude, Gemma
Speed	Fast mode: up to 2.5x at 2x price	Flash tier built for low latency
Price	$0.20–$10 in, $1.20–$50 out per 1M	Gemini 3.8 Flash $0.75 in, $3.75 out
Customization	N/A	Custom training on GPUs or TPUs
Deployment	API, Azure OpenAI, Bedrock	Managed on Google Cloud
Long context	1.05M; 2x input past 272K	1M on Gemini 3.8 Flash

Frequently asked questions

What is the difference between OpenAI and Google Vertex AI?

A closed model lab against Google Cloud's full AI platform. OpenAI sells GPT models and agent tooling; Vertex sells Gemini, Claude and 200+ models inside an MLOps stack.

When should I choose OpenAI over Google Vertex AI?

Teams that want one model API with published per-tier pricing; Computer use and coding agents on GPT-6 Astra; Hosted tools like web search and MCP without building a platform.

When should I choose Google Vertex AI over OpenAI?

Google Cloud shops keeping models close to BigQuery data; Running Gemini and Claude side by side under one governance layer; Custom training on TPUs next to inference.

Is OpenAI or Google Vertex AI cheaper?

OpenAI: $0.20–$10 in, $1.20–$50 out per 1M. Google Vertex AI: Gemini 3.8 Flash $0.75 in, $3.75 out. The cheaper choice depends on the model and workload.

Which has more context, OpenAI or Google Vertex AI?

OpenAI: 1.05M; 2x input past 272K. Google Vertex AI: 1M on Gemini 3.8 Flash.

Related comparisons

Running long-horizon agents?

If your agents run past 200K tokens, compare both against Subconscious. Our inference stack treats a long-horizon trace as the primary workload, so speed, cost, and accuracy hold up deep into the trace.

Subconscious vs OpenAI Subconscious vs Google Vertex AI