LocalClaw/LLM/LLM-jp-4.1 8B Thinking
Open-weight local LLM

LLM-jp-4.1 8B Thinking

Use case: Coding assistant. Check the memory fit and choose a setup path below.

16 GB catalogue minimum16 GB RAMQ4_K_MCoding assistant
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LM StudioNot available for this model
UnslothNot available for this model
OllamaNot available for this model
Open on Hugging FaceFiles, licence and available downloads
llama.cppNot available for this model
Use with LocalClawOptional workspace after the model is installed
This model needs its official runtimeLLM-jp llama.cpp fork
Parameters
8B
Minimum RAM
16 GB
Model size
5.04 GB
Quantization
Q4_K_M

About LLM-jp-4.1 8B Thinking

Catalogue summary: Official Apache 2.0 LLM-jp 4.1 dense reasoning model from NII/LLM-jp with English/Japanese focus, 65K context, Harmony-style chat template and official Q4_K_M GGUF for local llama.cpp testing through the LLM-jp fork.

LLM-jp-4.1 8B Thinking has a catalogue minimum of 16 GB RAM with Q4_K_M. Actual memory use and speed vary by context length, runtime, backend and system headroom.

Use the official LLM-jp llama.cpp fork setup. The current low-bit files are not a stock LM Studio install.

Model sourcePublic GGUF repository (verified 2026-11-06): llm-jp/llm-jp-4.1-8b-thinking-ggufUpstream releasePaper or model cardLicence text
chatcodereasoninglong-contextmultilingualstandard

Install path

01
Check RAM fitMinimum 16 GB RAM. Start with the Q4_K_M quant.
02
Load the modelFollow the official LLM-jp llama.cpp fork instructions. Stock LM Studio support is not confirmed.
03
Try your workloadStart with a short prompt, check memory use and adjust context length before running longer tasks.

Catalogue record

  • Family: llm-jp
  • Parameters: 8B
  • Recommended quantization: Q4_K_M
  • Catalogue minimum RAM: 16 GB
  • Catalogue model size: 5.04 GB
  • Tags: chat, code, reasoning, long-context, multilingual, standard

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
7
quality
8
coding
8
reasoning
8

Technical notes

Developer
LLM-jp
License
Apache 2.0
Context window
65,536 tokens
Architecture
Dense 8.59B-parameter transformer language model from the LLM-jp-4.1 thinking series, with 32 layers, 4,096 hidden size, 32 attention heads, a 65,536-token context window and official BF16 plus Q4_K_M GGUF artifacts.

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.

Starter desktopMac mini M4 16GBPortable fitMacBook Air M4 16GBBest 16GB models16GB RAM guide

Related catalogue entries

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

LLM-jp-4.1 32B-A3B Thinking 32B (3.8B active, MoE)LLM-jp-4 33B Thinking 33BK2-Horizon-3.7B 3.7BK2-Horizon-7B 9BBonsai 2 27B 27.36B (ternary)Bonsai 27B 27.3B (ternary / 1-bit)OLMo 3 7B Instruct 7BOrnith-1.5-9B 9B

Where to go next