Google Vertex AI vs SambaNova

Vertex AI is a full enterprise AI platform on Google Cloud. SambaNova is a chip company selling fast decode on large open models, through SambaCloud and racks for other clouds.

By The Subconscious Team · Updated October 11, 2026

Google Vertex AI vs SambaNova: key differences

SambaNova competes on hardware. Its Reconfigurable Dataflow Unit maps the model graph onto the chip, a three-tier memory design lets one system hot swap between large models in milliseconds, and SambaCloud serves models like MiniMax M3, MiniMax M2.7, DeepSeek, Gemma 4 31B and GPT-OSS 120B. SemiAnalysis measured a SambaRack SN50 at about 800 tokens per second on MiniMax M2.7. Vertex AI competes on breadth and integration: 200+ models including closed Gemini 3.8 and Claude, custom training on GPUs or TPUs, and an agent runtime tied into BigQuery.

Buyers should weigh maturity against speed. Many of SambaNova's headline numbers are vendor benchmarks on SN50 hardware still ramping, and much of its business runs through hardware sales and partnerships rather than a big self-serve platform. Vertex has the opposite problem, a sprawling surface with names in flux and pricing that is hard to forecast. Interactive coding agents on big open models, or agents that switch between several models per task, suit SambaNova. Anything that needs a closed frontier model or enterprise data plumbing suits Vertex.

What Google Vertex AI and SambaNova 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

SambaNova

SambaNova designs its own inference chip, the Reconfigurable Dataflow Unit, and sells fast tokens on large open models through SambaCloud. The RDU maps the model graph onto the chip to cut trips to off-chip memory. A three-tier memory design of SRAM, HBM and bulk DRAM lets one system host very large models and hot swap between several of them in milliseconds. SambaCloud serves models like MiniMax M3 (in preview with a 1M context), MiniMax M2.7, DeepSeek, Gemma 4 31B and GPT-OSS 120B, with speeds reported by Artificial Analysis.

Example models: MiniMax M3, MiniMax M2.7, GPT-OSS 120B

Full SambaNova profile

Should you choose Google Vertex AI or SambaNova?

Google Vertex AI

Choose Google Vertex AI for

Closed frontier models with enterprise governance
Training, evaluation and serving in one place
Multimodal and media generation

SambaNova

Choose SambaNova for

Fast decode on large open models like MiniMax M2.7
Agents that hot swap between several models
Neoclouds adding a premium speed tier

Google Vertex AI vs SambaNova at a glance

Attribute	Google Vertex AI	SambaNova
Model access	Closed and open, 200+ models	Open weights
Flagship models	Gemini 3.8 Flash, Claude, Gemma	MiniMax M3, MiniMax M2.7, GPT-OSS 120B
Speed	Flash tier built for low latency	~800 tok/s on MiniMax M2.7 (SN50, SemiAnalysis)
Price	Gemini 3.8 Flash $0.75 in, $3.75 out until 2027, then $1.50/$7.50	$0.22 in, $0.59 out (GPT-OSS 120B)
Customization	Custom training on GPUs or TPUs	Unknown
Deployment	Managed on Google Cloud	SambaCloud, racks for neoclouds
Long context	1M on Gemini 3.8 Flash	Up to 1M (MiniMax M3, preview)

Frequently asked questions

What is the difference between Google Vertex AI and SambaNova?

Vertex AI is a full enterprise AI platform on Google Cloud. SambaNova is a chip company selling fast decode on large open models, through SambaCloud and racks for other clouds.

When should I choose Google Vertex AI over SambaNova?

Closed frontier models with enterprise governance; Training, evaluation and serving in one place; Multimodal and media generation.

When should I choose SambaNova over Google Vertex AI?

Fast decode on large open models like MiniMax M2.7; Agents that hot swap between several models; Neoclouds adding a premium speed tier.

Is Google Vertex AI or SambaNova cheaper?

Google Vertex AI: Gemini 3.8 Flash $0.75 in, $3.75 out until 2027, then $1.50/$7.50. SambaNova: $0.22 in, $0.59 out (GPT-OSS 120B). The cheaper choice depends on the model and workload.

Which has more context, Google Vertex AI or SambaNova?

Google Vertex AI: 1M on Gemini 3.8 Flash. SambaNova: Up to 1M (MiniMax M3, preview).

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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