Google Vertex AI vs Wafer

Google's full AI platform against a young startup whose agents tune open-model serving. Vertex offers breadth and governance; Wafer offers faster open models and flat-rate coding access.

By The Subconscious Team · Updated September 30, 2026

Google Vertex AI vs Wafer: key differences

Wafer takes an unusual route to speed. Its AI agents profile a workload, try configurations across batching, decoding, quantization, engines, kernels and hardware, deploy the winner, then keep re-tuning as load or models change, on NVIDIA or AMD. Wafer reports its tuned Qwen 3.5 397B running 2.8x faster than stock SGLang, and GLM 5.1 and DeepSeek V4 Pro each 2x faster than a vLLM baseline. Vertex AI is the established platform: Gemini 3.8, Claude and 200+ models on Google's infrastructure, with MLOps and agent tooling around them.

Scale and track record favor Vertex. Flexibility and price favor Wafer. Wafer is a very young company with a small hosted catalog, and its speedups are self-reported against stock baselines rather than tuned hosts. Its Wafer Pass, from $10 a week, covers every hosted model and drops into Claude Code, Cline and OpenHands, a cheap way for developers to run big open models at interactive speed. Teams with a strict latency target and no kernel engineers can buy a dedicated Wafer deployment. Enterprises that need closed models and governance use Vertex.

What Google Vertex AI and Wafer 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

Wafer

Wafer builds AI agents that act as GPU performance engineers, then sells inference on the stacks those agents tune. The company came out of Y Combinator's Summer 2025 batch as a "Cursor for CUDA" that turned slow PyTorch into custom kernels. Founders Emilio Andere and Steven Arellano are based in San Francisco. Its agents profile a workload, generate candidate configs across batching, decoding, quantization, engines, kernels and hardware, measure each one and deploy the winner.

Example models: Qwen 3.5 397B Turbo, GLM 5.1 Turbo

Full Wafer profile

Should you choose Google Vertex AI or Wafer?

Google Vertex AI

Choose Google Vertex AI for

Closed frontier models under enterprise controls
A mature platform with training and evaluation
Multimodal and media workloads

Wafer

Choose Wafer for

Flat-rate open-model access for coding agents
Dedicated endpoints tuned to a latency SLO
Hedging GPU supply across NVIDIA and AMD

Google Vertex AI vs Wafer at a glance

Attribute	Google Vertex AI	Wafer
Model access	Closed and open, 200+ models	Open weights
Flagship models	Gemini 3.8 Flash, Claude, Gemma	Qwen 3.5 397B Turbo, GLM 5.1 Turbo
Speed	Flash tier built for low latency	2–2.8x vs stock vLLM or SGLang
Price	Gemini 3.8 Flash $0.75 in, $3.75 out	Wafer Pass from $10 a week
Customization	Custom training on GPUs or TPUs	Agent-tuned dedicated deployments
Deployment	Managed on Google Cloud	Serverless pass, dedicated
Long context	1M on Gemini 3.8 Flash	Varies by model

Frequently asked questions

What is the difference between Google Vertex AI and Wafer?

Google's full AI platform against a young startup whose agents tune open-model serving. Vertex offers breadth and governance; Wafer offers faster open models and flat-rate coding access.

When should I choose Google Vertex AI over Wafer?

Closed frontier models under enterprise controls; A mature platform with training and evaluation; Multimodal and media workloads.

When should I choose Wafer over Google Vertex AI?

Flat-rate open-model access for coding agents; Dedicated endpoints tuned to a latency SLO; Hedging GPU supply across NVIDIA and AMD.

Is Google Vertex AI or Wafer cheaper?

Google Vertex AI: Gemini 3.8 Flash $0.75 in, $3.75 out. Wafer: Wafer Pass from $10 a week. The cheaper choice depends on the model and workload.

Which has more context, Google Vertex AI or Wafer?

Google Vertex AI: 1M on Gemini 3.8 Flash. Wafer: Varies by model.

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.

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