arcflare_
Reasoning117B-A5B official

gpt-oss-120b

by OpenAI

OpenAI open-weight MoE reasoning model, 117B parameters with 5.1B active, configurable reasoning effort, MXFP4-trained MoE weights.

#reasoning#moe#large
arcflare pull unsloth/gpt-oss-120b-GGUF:Q4_K_M

[ 01 ] // quickstart

┌─ arcflare — zsh // tty1
$ 

[ 02 ] // readme

gpt-oss-120b

OpenAI open-weight MoE reasoning model, 117B parameters with 5.1B active, configurable reasoning effort, MXFP4-trained MoE weights.

Get it

arcflare pull unsloth/gpt-oss-120b-GGUF:Q4_K_M
arcflare run gpt-oss-120b

ArcFlare reads the GGUF header and loads it at the largest context your free VRAM can actually hold. Use arcflare fit to see that before downloading anything else, or arcflare use opencode to code with it.

Highlights

  • Downloads the Q4_K_M file by default: 62.8 GB. Also published: Q8_0 (63.4 GB), Q5_K_M (62.9 GB), Q3_K_M (62.6 GB)
  • Trained for a 128K context
  • Licence: Apache-2.0. Read it before commercial use

Sizes

  • 117b-a5b · 62.8GB

Other sizes live in sibling repos: swap the size in the repo name when pulling.

[ 03 ] // relatedmore →

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Alibaba Qwen

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Qwen3-30B-A3B thinking-only update: 30.5B MoE with 3.3B active, deeper reasoning and 256K native context.

size
30B-A3B
vram
~20 GB
license
Apache-2.0

83% of a 24 GB card

#reasoning #moe #large

gpt-oss

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Reasoning

gpt-oss: OpenAI's open-weight reasoning models. 20B runs in ~16 GB, 120B on one 80 GB card. Apache-2.0, adjustable reasoning effort.

size
20B
vram
~14 GB
license
Apache-2.0

58% of a 24 GB card

#reasoning #tools #moe

glm4.5-air

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GLM-4.5-Air: a 106B MoE with 12B active, hybrid reasoning and strong agent and coding scores, under MIT. Workstation-class.

size
106B-A12B
vram
~64 GB
license
MIT

2.7× a 24 GB card

#moe #agentic #reasoning