AI Coding Agent
The coding agent provides in-editor completion, pull-request review and explanation, test generation and refactoring using strong open coding models — all on a machine the team controls.
Engineering teams want AI assistance without shipping proprietary source to a third party. Coding rewards larger models and prompt-processing compute, so this sits in the upper-mid hardware tier: a 24GB+ GPU, a high-memory Mac, or a multi-GPU workstation for a whole team.
What it does
- ▸Code completion, review and refactoring on private repos
- ▸Pull-request explanation and test generation
- ▸Issue triage and release-note drafting
- ▸Engineering ops assistants for a team
Connects to
Fit is driven by each machine’s coding capability score.
Models that power it
All models →Open models in the library that suit this role: 25. A few, smallest first:
DeepSeek-R1 Distill 1.5B
tiny reasoning · edge
Qwen2.5-Coder 1.5B
code · fill-in-the-middle
StarCoder2 3B
code · fill-in-the-middle
Qwen2.5 7B
multilingual · coding
Qwen2.5-Coder 7B
coding · in-editor completion
CodeLlama 7B
code · fill-in-the-middle
Hardware it runs on
All hardware →Machines that can host this agent today, scored for real local-AI workloads — cheapest strong fit first.
Coding Agent Workstation (reference profile)
A workstation tuned for local coding agents: ~48GB across two 24GB cards runs strong 32B coder models and serves a small engineering team privately.
- Memory
- 48 GB
- Architecture
- Ada Lovelace
Apple Mac Studio (M4 Max)
Up to 128GB of unified memory in a compact desktop — large enough to hold 70B-class models entirely on-device.
- Memory
- 128 GB unified
- Architecture
- Apple M4 Max
NVIDIA A100 80GB
The datacenter workhorse of the LLM boom: 80GB HBM2e with strong tensor throughput, now widely available used and in the cloud.
- Memory
- 80 GB
- Architecture
- Ampere
Run it private, in your cloud, or hybrid
Keep this agent on hardware you own for privacy and predictable cost, run it on cloud GPUs in your own account for bursts and the largest models, or do both.
Frequently asked questions
What is the Coding & Engineering agent?+
The coding agent provides in-editor completion, pull-request review and explanation, test generation and refactoring using strong open coding models — all on a machine the team controls.
Can the Coding & Engineering agent run privately on my own hardware?+
Yes. It runs on open-weight models you self-host on a private box, on-prem server or your own cloud account, so data stays on infrastructure you control. You can also run hybrid — local by default, bursting to the cloud for the largest models.
Which models power the Coding & Engineering agent?+
It works with open models such as DeepSeek-R1 Distill 1.5B, Qwen2.5-Coder 1.5B, StarCoder2 3B. The right size depends on quality needs and the hardware you run it on — see the model library for VRAM by quantization.
What hardware does the Coding & Engineering agent need?+
It typically maps to the Pro tier. A machine like the Coding Agent Workstation (reference profile) strongly fits this role; lighter or heavier hardware shifts how many concurrent requests and how large a model you can run.
What does the Coding & Engineering agent connect to?+
It connects to the systems this function already runs on — for example GitHub, Jira, Slack, CI / build systems — so it does real work instead of only answering questions.
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