tools
SambaNova DataScale
SambaNova DataScale è un sistema di IA installato in sede o ospitato, per addestrare ed eseguire modelli di grandi dimensioni con processori a flusso di dati.
In inglese
SambaNova DataScale is an integrated hardware and software system for AI training and inference. The DataScale SN40L uses Reconfigurable Dataflow Units, a dataflow architecture, and three-tier memory to run multiple models and switch between them quickly.
It is aimed at enterprises, government agencies, and research organizations. Deployments can be on-premises or in hosted data centers. Hardware pricing is not published on the reviewed pricing page; that page lists SambaNova Cloud token usage instead.
Features
- Runs AI model training and inference
- Uses SN40L Reconfigurable Dataflow Units
- Supports on-premises and hosted data-center deployment
- Runs multiple models on one system
- Switches between models in microseconds
- Uses three-tier memory with SRAM, HBM, and DDR
- Supports custom and chained models
- Runs Red Hat Enterprise Linux
Use cases
- Train and deploy large language models
- Run generative and agentic AI workloads
- Analyze high-resolution computer-vision images
- Support scientific research and AI-for-science workloads
- Deploy private AI infrastructure for enterprises
- Run multiple models from a shared system
Pros
Cons
Latest updates
- Supermicro Will Build and Sell SambaNova-Powered Inference Systems (SN50)
Supermicro will deliver and support inference systems pairing NVIDIA GPUs with SambaNova SN50 RDUs, rolling out in phases.
- MiniMax M3.1 Flash Now Available on SambaCloud (MiniMax M3.1 Flash)
MiniMax M3.1 Flash is now available on SambaCloud.
- MiniMax M3 Prompt Caching on SambaCloud: How It Works (MiniMax M3)
Prompt caching is now available for MiniMax M3 on SambaCloud for shared prefixes of at least 4,096 tokens.
- MiniMax M3 Running Fastest on SambaCloud (MiniMax M3)
MiniMax M3 is available on SambaCloud for developers building long-horizon, long-context agents.
- Prompt Caching on SambaCloud: Faster, Cheaper Inference (MiniMax M2.7)
Prompt caching is now live on SambaCloud, starting with support for MiniMax M2.7.
Capabilities
- Choice of models — “SambaStack switches between multiple frontier-scale models, enabling complex agentic AI workflows to execute end-to-end on one node.” source
- Self-hosted — “SambaRack™ is a state-of-the-art hardware platform that can be set up easily in data centers to run Al inference workloads.” source
- API — “SambaNova provides simple-to-integrate APIs for Al inference, making it easy to onboard applications.” source
- Runs models for you — “SambaNova provides simple-to-integrate APIs for Al inference, making it easy to onboard applications.” source
- Builds agents and workflows — “Build or use pre-built AI agents — all with business-aware intelligence.” source
Get it
Pricing
- Prices checked
- 2026-10-24
MiniMax-M3.1-Flash
- 0.03 USD — Cached Input Tokens
- 0.30 USD — Input (per 1M tokens)
- 1.20 USD — Output (per 1M tokens)
DeepSeek-V3.1
- 3 USD — Input (per 1M tokens)
- 4.50 USD — Output (per 1M tokens)
DeepSeek-V3.2
- 3 USD — Input (per 1M tokens)
- 4.50 USD — Output (per 1M tokens)
gemma-4-31B-it
- 0.38 USD — Input (per 1M tokens)
- 1.15 USD — Output (per 1M tokens)
gpt-oss-120b
- 0.22 USD — Input (per 1M tokens)
- 0.59 USD — Output (per 1M tokens)
Meta-Llama-3.3-70B-Instruct
- 0.60 USD — Input (per 1M tokens)
- 1.20 USD — Output (per 1M tokens)