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
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 M2.7, DeepSeek, Gemma 4 31B and GPT-OSS 120B. SambaNova says a SambaRack SN50 runs MiniMax M2.7 near 820 tokens per second in its fastest configuration. 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 profileSambaNova
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 M2.7, DeepSeek, Gemma 4 31B and GPT-OSS 120B, with speeds reported by Artificial Analysis.
Example models: MiniMax M2.7, GPT-OSS 120B
Full SambaNova profileShould 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 | ||
|---|---|---|
| Model access | Closed and open, 200+ models | Open weights |
| Flagship models | Gemini 3.8 Flash, Claude, Gemma | MiniMax M2.7, GPT-OSS 120B, DeepSeek |
| Speed | Flash tier built for low latency | ~820 tok/s on MiniMax M2.7 (SN50) |
| Price | Gemini 3.8 Flash $0.75 in, $3.75 out | $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 192K (MiniMax M2.7) |
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. 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 192K (MiniMax M2.7).
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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.