Family gpt-oss · 117B parameters

gpt-oss 120B

OpenAI's first open model. 117B/5.1B active MoE. Matches o4-mini. Fits on an 80 GB GPU.

🇺🇸 OpenAI·License Apache 2.0·Context 125k tokens·Output April 2025·Tested on the GIGABYTE AI TOP ATOM · our measurements← Catalog

01What it can do

Strengths
  • MIT License
  • Open-weight OpenAI quality
  • 128k context
  • Strong at reasoning and code
Limitations to know
  • —70 GB VRAM Q4 — multi-GPU required
  • —MoE that's complex to deploy
Architecture
MoE · ~117B total / ~20B active · OpenAI open-source · 128k ctx
Training
OpenAI — OpenAI's first open-weight model released under the MIT license.
Ideal for
ReasoningPro chatAgents

04Install

Install Ollama for your OS. Check the model and its quantization before downloading. Start with 4096 tokens of context, then check placement with ollama ps. A command below is not proof that a test was run on your machine.

$ollama run openai/gpt-oss:120b
⚠
First download: between 2 and 40 GB depending on the selected quantization. Plan for sufficient disk space; a stable connection is recommended. Subsequent launches are instant.

02Required memory

Approximate GPU VRAM required to run this model, including 4k tokens of context overhead. For a longer context, add ~1 GB per 8k-token increment.

Q4_K_M
The lightest, ~5% loss
70 GB
Q5_K_M
Good quality/size compromise
85 GB
Q8_0
Nearly indistinguishable from FP16
125 GB
FP16
Full precision — server use
234 GB
Fallback CPU · If you don't have a GPU, allow 100 GB of RAM minimum to run this model at reduced speed.

What hardware do you need for gpt-oss 120B?

To run gpt-oss 120B locally with Q4 quantization, you need about 70 GB of VRAM. An option to compare: BOSGAME M5 128GB / 2TB (Ryzen AI Max+ 395) — leave some headroom for the system and context; check engine compatibility with the GPU.

Current offer: BOSGAME M5 128GB / 2TB (Ryzen AI Max+ 395)
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Why this choice? Our complete guide on BOSGAME M5 128GB / 2TB (Ryzen AI Max+ 395) →

Affiliate links — commission possible at no extra cost to you; independent recommendations. As an Amazon Associate, BestLLMfor earns from qualifying purchases.

This model in your private ChatGPT, without the cloud

Too large for your machine? The kit gives you the model that fits in your VRAM

  • Lifetime online access
  • PDF + files
  • Lifetime updates

03Expected speed

Tokens generated per second in Q4_K_M, 4k context. Beyond 20 t/s, reading is comfortable. Below 10 t/s, that's just for testing.

Entry-level
~12t/s
GTX 1650, RX 6600, MBA M2 8GB
Mid-range
~35t/s
RTX 4060, 4070, MBP M3 Pro
High-end
~90t/s
RTX 4090, M4 Max, Radeon 7900