Individual skill

sambanova-guide

Run open models on SambaNova's reconfigurable hardware — fast inference with enterprise deployment options.

skills/sambanova-guide/SKILL.md

Read pinned source

Source commit faf37c0859ebf627bfcb5225e8057d088691e0ae

What was checked

Matches the observed repository HEAD
Yes
Scanner rules are current
Yes
Repository scan complete
No
Skill scan complete
Yes
Observed behavior
Instructions only
Last checked
Nov 11, 2026

These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.

Install this skill

Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.

An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.

Repository context

Repository stars (not skill ratings)
56
Repository last updated
Oct 10, 2026
License
MIT

Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.

Files and excerpt

File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.

Browse files
Read excerpt

## Overview

SambaNova builds reconfigurable dataflow hardware (RDUs) for AI and offers
inference services running open models on it — combining competitive inference
speed with enterprise-oriented deployment options (including on-premises and
sovereign deployments for regulated industries). The positioning blends
performance with enterprise requirements: data control, compliance, and
deployment flexibility alongside fast tokens.

For most builders, SambaNova enters consideration in two scenarios: as another
fast-inference API for open models (benchmark it with the other speed
specialists), and — more distinctively — when enterprise constraints (data
residency, on-prem, regulated industries) rule out pure public-API approaches.
The reconfigurable hardware story matters less to API users than the deployment
Back to top