Google Vertex AI vs Inception

Vertex AI is Google Cloud's full AI platform with Gemini, Claude and 200+ models. Inception sells one family of fast diffusion LLMs.

By The Subconscious Team · Updated October 11, 2026

Google Vertex AI vs Inception: key differences

Vertex offers Gemini 3.8, Claude and open models next to training, pipelines, agent tooling and BigQuery integration. Gemini 3.8 Flash costs $0.75 in and $3.75 out at introductory rates through 2026 with 1M context, though pricing spreads across many services. Inception's Mercury 2.5 is a closed diffusion reasoning model with tool use and 260K context at $0.20 in and $0.75 out. Inception reports 1,100+ tokens per second; Artificial Analysis measures about 640.

Vertex fits enterprises on Google Cloud that want frontier models and governance in one place. Inception fits narrow, latency-critical tasks like code edits or voice where a cost-optimized model is enough. It is also sold through AWS Bedrock and Azure Foundry.

What Google Vertex AI and Inception do

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

Inception

Inception builds diffusion large language models (dLLMs). Every other LLM on this list generates text one token at a time; Inception's Mercury models start from a rough draft of a whole block and refine it over a few passes, producing many tokens in parallel. That ties speed less to output length and lets the models run fast on ordinary NVIDIA GPUs rather than custom chips. The company was founded by professors from Stanford, UCLA and Cornell behind core work on diffusion, Flash Attention and DPO, and is led by Stanford's Stefano Ermon. It raised a $50M seed in November 2025 led by Menlo Ventures, with Mayfield, M12, NVentures, Snowflake and Databricks, plus Andrew Ng and Andrej Karpathy as angels.

Example models: Mercury 2.5, Mercury 2

Full Inception profile

Should you choose Google Vertex AI or Inception?

Google Vertex AI

Choose Google Vertex AI for

Gemini and Claude on one cloud
Governed enterprise agents
1M-context multimodal work

Inception

Choose Inception for

Very fast output at low prices
Code autocomplete and edits
Voice agents

Google Vertex AI vs Inception at a glance

Attribute	Google Vertex AI	Inception
Model access	Closed and open, 200+ models	Closed weights (Mercury dLLMs)
Flagship models	Gemini 3.8 Flash, Claude, Gemma	Mercury 2.5, Mercury 2
Speed	Flash tier built for low latency	1,100+ tok/s (vendor); ~640 measured
Price	Gemini 3.8 Flash $0.75 in, $3.75 out until 2027, then $1.50/$7.50	$0.20 in, $0.75 out (Mercury 2.5)
Customization	Custom training on GPUs or TPUs	Fine-tuning on request
Deployment	Managed on Google Cloud	Serverless API, Bedrock, Azure, private
Long context	1M on Gemini 3.8 Flash	260K

Frequently asked questions

What is the difference between Google Vertex AI and Inception?

Vertex AI is Google Cloud's full AI platform with Gemini, Claude and 200+ models. Inception sells one family of fast diffusion LLMs.

When should I choose Google Vertex AI over Inception?

Gemini and Claude on one cloud; Governed enterprise agents; 1M-context multimodal work.

When should I choose Inception over Google Vertex AI?

Very fast output at low prices; Code autocomplete and edits; Voice agents.

Is Google Vertex AI or Inception cheaper?

Google Vertex AI: Gemini 3.8 Flash $0.75 in, $3.75 out until 2027, then $1.50/$7.50. Inception: $0.20 in, $0.75 out (Mercury 2.5). The cheaper choice depends on the model and workload.

Which has more context, Google Vertex AI or Inception?

Google Vertex AI: 1M on Gemini 3.8 Flash. Inception: 260K.

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 Google Vertex AI Subconscious vs Inception