FitMyLLM
OpenAI/Mixture of Experts

OpenAIGPT-OSS 120B

OpenAI's flagship open-weight model. 117B MoE with 5.1B active params. Strong reasoning and tool use under Apache 2.0.

chatcodingreasoningtool_use
117B
Parameters (5.1B active)
128K
Context length
16
Benchmarks
17
Quantizations
Architecture
MoE
Released
2026-02-14
Layers
64
KV Heads
8
Head Dim
128
Family
gpt-oss

Quantization Options

QuantBitsVRAMQuality
IQ2_XXS2.3835.3 GBlow
IQ2_M2.9343.3 GBlow
Q2_K3.1646.7 GBlow
IQ3_XXS3.2548.0 GBlow
IQ3_XS3.551.7 GBlow
Q3_K_S3.6453.7 GBlow
IQ3_M3.7655.5 GBlow
Q3_K_M459.0 GBlow
Q3_K_L4.363.4 GBmoderate
IQ4_XS4.4665.7 GBmoderate
Q4_K_S4.6768.8 GBmoderate
Q4_K_M4.8972.0 GBgood
Q5_K_S5.5781.9 GBgood
Q5_K_M5.783.9 GBgood
Q6_K6.5696.4 GBexcellent
Q8_08.5124.8 GBlossless
FP1616234.5 GBlossless

Select your GPU above to see speed estimates and compatibility for each quantization.

▸ READY TO RUN THIS?RENT BY THE HOUR

RENT A GPU AND RUN GPT-OSS 120B NOW

Rent on RunPod →Or Vast.ai →

Spin up an A100 / H100 / 4090 in ~60s. Pay by the second. Cancel anytime.

Community Ratings

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Benchmarks (16)

AIME97.9
MMLU-PRO90.0
HumanEval88.3
GPQA Diamond80.1
LiveCodeBench70.7
MATH-50066.7
AA Math66.7
SWE-bench62.4
IFBench58.3
τ²-Bench45.0
AA Long Context43.7
SciCode36.0
AA Intelligence24.5
AA Coding15.5
HLE14.9
Terminal-Bench5.3

Run this model

▸Easiest way to get started·Beginners
DOCS ↗
curl -fsSL https://ollama.com/install.sh | sh
$ollama run gpt-oss:120b-q4_K_M

Downloads and runs automatically. Add --verbose for speed stats.

▸ SETUP GUIDE
>_

Auto-setup with fitmyllm CLI

Detects your GPU, recommends the best model, downloads it, and starts chatting — zero config. Benchmarks your speed and contributes anonymous data to improve predictions.

pip install fitmyllmthen run fitmyllmLearn more
Auto-detect GPULive tok/s in chatSpeed benchmarks9 inference engines
HuggingFaceOllama LibraryGGUF DownloadsBuild Hardware

GPUs that can run this model

At Q4_K_M quantization. Sorted by minimum VRAM.

NVIDIA H100 SXM5 80GB
80 GB VRAM • 3350 GB/s
NVIDIA
$25000
NVIDIA H100 PCIe 80GB
80 GB VRAM • 2000 GB/s
NVIDIA
$25000
NVIDIA A100 SXM 80GB
80 GB VRAM • 2039 GB/s
NVIDIA
$10000
NVIDIA A100 PCIe 80GB
80 GB VRAM • 1935 GB/s
NVIDIA
$10000
NVIDIA A100 SXM4 80 GB
80 GB VRAM • 2040 GB/s
NVIDIA
$15000
NVIDIA A100 PCIe 80 GB
80 GB VRAM • 1940 GB/s
NVIDIA
$10000
NVIDIA A100X
80 GB VRAM • 2040 GB/s
NVIDIA
NVIDIA H100 PCIe 80 GB
80 GB VRAM • 2040 GB/s
NVIDIA
$25000
NVIDIA H100 SXM5 80 GB
80 GB VRAM • 3360 GB/s
NVIDIA
$25000
NVIDIA H100 CNX
80 GB VRAM • 2040 GB/s
NVIDIA
$25000
NVIDIA A800 PCIe 80 GB
80 GB VRAM • 1940 GB/s
NVIDIA
NVIDIA A800 SXM4 80 GB
80 GB VRAM • 2040 GB/s
NVIDIA
NVIDIA H800 PCIe 80 GB
80 GB VRAM • 2040 GB/s
NVIDIA
NVIDIA H800 SXM5
80 GB VRAM • 3360 GB/s
NVIDIA
NVIDIA RTX 6000D
84 GB VRAM • 1570 GB/s
NVIDIA
$7500
NVIDIA B200
90 GB VRAM • 4100 GB/s
NVIDIA
$30000
NVIDIA H100 NVL 94 GB
94 GB VRAM • 3940 GB/s
NVIDIA
$30000
NVIDIA H100 SXM5 94 GB
94 GB VRAM • 3360 GB/s
NVIDIA
$25000
RTX Pro 6000
96 GB VRAM • 1792 GB/s
NVIDIA
$8565
NVIDIA H100 PCIe 96 GB
96 GB VRAM • 3360 GB/s
NVIDIA
$25000
NVIDIA H100 SXM5 96 GB
96 GB VRAM • 3360 GB/s
NVIDIA
$25000
Intel Data Center GPU Max 1350
96 GB VRAM • 2460 GB/s
INTEL
NVIDIA RTX PRO 6000 Blackwell Server
96 GB VRAM • 1790 GB/s
NVIDIA
$9999
NVIDIA RTX PRO 6000 Blackwell
96 GB VRAM • 1790 GB/s
NVIDIA
$9999
AMD Instinct MI300A
120 GB VRAM • 5300 GB/s
AMD
$12000
Apple M4 Max (128GB)
128 GB VRAM • 546 GB/s
APPLE
$3999
AMD Instinct MI250X
128 GB VRAM • 3277 GB/s
AMD
$10000
Apple M1 Ultra (128GB)
128 GB VRAM • 800 GB/s
APPLE
$4999
Apple M2 Ultra (128GB)
128 GB VRAM • 800 GB/s
APPLE
$3999
AMD Radeon Instinct MI250
128 GB VRAM • 3280 GB/s
AMD
$12000

Find the best GPU for GPT-OSS 120B

Build Hardware for GPT-OSS 120B
▸ SPEC SHEET

GPT-OSS 120B — 117B MoE.

▸ SPECIFICATIONS
PARAMETERS
117B (5.1B active)
ARCHITECTURE
Mixture of Experts
CONTEXT LENGTH
128K tokens
CAPABILITIES
chat, coding, reasoning, tool_use
RELEASE DATE
2026-02-14
PROVIDER
OpenAI
FAMILY
gpt-oss
▸ VRAM REQUIREMENTS
QUANTBPWVRAMQUALITY
IQ2_XXS2.3835.3 GB65%
IQ2_M2.9343.3 GB75%
Q2_K3.1646.7 GB78%
IQ3_XXS3.2548.0 GB82%
IQ3_XS3.551.7 GB84%
Q3_K_S3.6453.7 GB85%
IQ3_M3.7655.5 GB86%
Q3_K_M459.0 GB88%
Q3_K_L4.363.4 GB90%
IQ4_XS4.4665.7 GB92%
Q4_K_S4.6768.8 GB93%
Q4_K_M4.8972.0 GB94%
Q5_K_S5.5781.9 GB96%
Q5_K_M5.783.9 GB96%
Q6_K6.5696.4 GB97%
Q8_08.5124.8 GB100%
FP1616234.5 GB100%
§ 01BENCHMARK SCORES
HumanEval88.3
MMLU-PRO90.0
LiveCodeBench70.7
SWE-bench62.4
AIME97.9
MATH-50066.7
GPQA Diamond80.1
HLE14.9
AA Intelligence24.5
AA Coding15.5
AA Math66.7
aa_ifbench58.3
aa_terminal_bench5.3
aa_tau245.0
aa_scicode36.0
aa_lcr43.7
§ 02RUN COMMAND

Run GPT-OSS 120B locally with Ollama — needs 72.0 GB VRAM at Q4_K_M:

$ollama run gpt-oss:120b
§ 03COMPATIBLE GPUs
30 @ Q4_K_M
NVIDIA H100 SXM5 80GB
80 GB · 3350 GB/s
NVIDIA H100 PCIe 80GB
80 GB · 2000 GB/s
NVIDIA A100 SXM 80GB
80 GB · 2039 GB/s
NVIDIA A100 PCIe 80GB
80 GB · 1935 GB/s
NVIDIA A100 SXM4 80 GB
80 GB · 2040 GB/s
NVIDIA A100 PCIe 80 GB
80 GB · 1940 GB/s
NVIDIA A100X
80 GB · 2040 GB/s
NVIDIA H100 PCIe 80 GB
80 GB · 2040 GB/s
NVIDIA H100 SXM5 80 GB
80 GB · 3360 GB/s
NVIDIA H100 CNX
80 GB · 2040 GB/s
NVIDIA A800 PCIe 80 GB
80 GB · 1940 GB/s
NVIDIA A800 SXM4 80 GB
80 GB · 2040 GB/s
NVIDIA H800 PCIe 80 GB
80 GB · 2040 GB/s
NVIDIA H800 SXM5
80 GB · 3360 GB/s
NVIDIA RTX 6000D
84 GB · 1570 GB/s