Open-weight local LLM

Nemotron Mini (4B)

Use case: Fast chat. Check the memory fit and choose a setup path below.

6 GB catalogue minimum6 GB RAMQ5_K_MFast chat
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Parameters
4B
Minimum RAM
6 GB
Model size
2.5 GB
Quantization
Q5_K_M

About Nemotron Mini (4B)

Catalogue summary: NVIDIA small model for RAG + roleplay + function calling. Compact and versatile. 107K downloads.

Nemotron Mini (4B) has a catalogue minimum of 6 GB RAM with Q5_K_M. Actual memory use and speed vary by context length, runtime, backend and system headroom.

Use nemotron-mini-4b-instruct as the catalogue search term in a compatible runtime, and confirm the available format on the upstream repository before download.

chatlightspeed

Install path

01
Check RAM fitMinimum 6 GB RAM. Start with the Q5_K_M quant.
02
Load the modelSearch nemotron-mini-4b-instruct in LM Studio.
03
Try your workloadStart with a short prompt, check memory use and adjust context length before running longer tasks.

Catalogue record

  • Family: nemotron
  • Parameters: 4B
  • Recommended quantization: Q5_K_M
  • Catalogue minimum RAM: 6 GB
  • Catalogue model size: 2.5 GB
  • Tags: chat, light, speed

Practical limits

  • Catalogue RAM is a minimum estimate, not a guarantee for every context length or runtime.
  • Speed and memory use vary by quantization, backend, context length and system headroom.
  • Verify architecture, licence and usage restrictions in the linked upstream material before deployment.

Reading the scores

LocalClaw /10 is an editorial catalogue rating. Community /5 comes from member reviews. Your machine fit is a separate memory and runtime assessment.

Capability profile

Repository catalogue ratings used by LocalClaw's editorial rubric. They are not a standardized third-party benchmark.

speed
9
quality
6
coding
5
reasoning
5

Technical notes

Developer
See upstream repository
License
See upstream repository
Context window
See upstream repository
Architecture
See upstream repository

This model fits these next steps

Hardware fit is based on LocalClaw's RAM tier, model size and quantization metadata. Always leave memory headroom for your OS and runtime.

Related catalogue entries

Linked mechanically by family, shared tags and nearby RAM tier; this is not a quality ranking.

Where to go next