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GB10 for Coding Agents

Coding agents reward larger models and headroom for repo-scale context. A GB10-class appliance's unified memory can hold a strong coder plus context comfortably, keeping proprietary source on a box your team controls. Specs are provisional.

Bigger coders, more context

A 32B coder is a real step up for review and refactoring. GB10's memory holds it with room for long context, where a 24GB card is tighter.

Private by design

Source never leaves the box. Connect to GitHub and Jira through the Product & Engineering Ops pack.

Featured chips

Recommended models

  1. 1
    CodeLlama 34BCodeLlama · ~34B · 16K ctx · Llama Community License

    The largest CodeLlama, suitable for review and refactoring. Newer 32B-class open coders generally beat it now; included for completeness of the family.

  2. 2
    Qwen2.5-Coder 32BQwen · ~32B · 128K ctx · Apache-2.0

    A leading open coding model and a natural backbone for a serious local coding / product-engineering agent.

  3. 3
    DeepSeek-Coder V2 (class)DeepSeek · ~16B · 128K ctx · DeepSeek License

    Representative entry for the DeepSeek coding family. Sizes vary widely across releases — verify the exact variant and its footprint before deploying.

  4. 4
    StarCoder2 15BStarCoder · ~15B · 16K ctx · BigCode OpenRAIL-M

    The largest StarCoder2, trained on permissively-licensed code across many languages. Review the BigCode OpenRAIL-M license restrictions before commercial use.

  5. 5
    Qwen2.5-Coder 14BQwen · ~14B · 128K ctx · Apache-2.0

    The mid-size coder: noticeably stronger than 7B for review and refactoring while still fitting a single 16GB card. A great private coding-agent backbone.

Recommended hardware

Frequently asked questions

Is GB10 good for coding agents?+

Its unified memory holds a strong 32B coder plus repo-scale context on a compact box, which suits team coding agents — verify final specs before buying.

Related guides

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