OpenAI · 21B total / 3.6B active · MoE

Best hardware to run GPT-OSS 20B locally

GPT-OSS 20B needs about 13 GB at MXFP4 (native). 17 of the 17 priced rigs we track can hold it. Here's the cheapest, the best value and the fastest. Prices & stock checked 2026-10-23. Prices change daily and some retailers block our checker, so always confirm on the store page.

Our picks

Mac miniAvailable

Mac mini M5 Pro

15-core CPU / 16-core GPU, 24GB

$1,699at Apple Store

Cheapest that fits. Lowest price we've seen on any tracked rig that holds GPT-OSS 20B at 4-bit (13 of 17 GB usable).

Fits~82 tok/sMXFP4 (native)
Check price
Mac miniAvailable

Mac mini M5 Pro

15-core CPU / 16-core GPU, 24GB

$1,699at Apple Store

Best value. Lowest price per token/sec among complete systems where it fits comfortably: about $21 per tok/s at 4-bit. Same machine as the cheapest pick.

Fits~82 tok/sMXFP4 (native)
Check price
RTX 5090In stock

NVIDIA GeForce RTX 5090 Founders Edition

32GB card

$8,500at Newegg

Fastest. Most memory bandwidth of the rigs that fit it (1,792 GB/s), so the quickest decode: ~264 tok/s at 4-bit.

Fits~264 tok/sMXFP4 (native)

Suggested quant: Q8_0 (~197 tok/s)

GPU price is card only: you still need a host PC.

Check price

Which quant to use

Use MXFP4 (native) on most rigs: it needs ~13 GB. Q8_0 (~25 GB) is a bit more accurate and fits comfortably on 14 of these rigs, e.g. the GMKtec EVO-X2. GPT-OSS 20B ships natively in MXFP4 (native), so that's the format to grab.

Every rig that fits it

MachinePrice4-bit fit & speedSuggested quant$ per tok/s
Mac mini M5 ProMac mini$1,699
Fits~82 tok/s
MXFP4 (native)$21
GMKtec EVO-X2Strix Halo$2,200
Fits~69 tok/s
Q8_0$32
Mac Studio M5 MaxMac Studio$2,499
Fits~101 tok/s
MXFP4 (native)$25
Mac Studio M5 MaxMac Studio$3,099
Fits~114 tok/s
Q8_0$27
Framework Desktop DIYStrix Halo$3,449
Fits~69 tok/s
Q8_0$50
GMKtec EVO-X2Strix Halo$3,500
Fits~69 tok/s
Q8_0$51
Minisforum MS-S1 MaxStrix Halo$3,919
Fits~69 tok/s
Q8_0$57
Beelink GTR9 ProStrix Halo$4,349
Fits~69 tok/s
Q8_0$63
Gigabyte GeForce RTX 4090 Windforce V2RTX 4090 (card only, needs a host PC)$4,899
Fits~209 tok/s
MXFP4 (native)$23
Mac Studio M5 UltraMac Studio$5,499
Fits~119 tok/s
Q8_0$46
Lenovo ThinkStation PGXDGX Spark / GB10$5,859
Fits~80 tok/s
Q8_0$73
ASUS Ascent GX10DGX Spark / GB10$5,999
Fits~80 tok/s
Q8_0$75
NVIDIA DGX SparkDGX Spark / GB10$6,950
Fits~80 tok/s
Q8_0$87
HP ZGX Nano G1nDGX Spark / GB10$7,699
Fits~80 tok/s
Q8_0$96
Gigabyte AI TOP ATOMDGX Spark / GB10$8,499
Fits~80 tok/s
Q8_0$106
NVIDIA GeForce RTX 5090 Founders EditionRTX 5090 (card only, needs a host PC)$8,500
Fits~264 tok/s
Q8_0$32
PNY NVIDIA RTX PRO 6000 BlackwellRTX PRO 6000 (card only, needs a host PC)$17,899
Fits~264 tok/s
Q8_0$68

Sorted by lowest price. Speeds are estimated single-user decode at ~8K context. Full fit table, including rigs that don't fit: GPT-OSS 20B memory requirements. How we estimate

FAQ

How much memory does GPT-OSS 20B need?

About 13 GB at MXFP4 (native) and 25 GB at Q8_0, including runtime overhead and ~8K tokens of context for one user. Longer context needs more.

What's the cheapest hardware to run GPT-OSS 20B locally?

Of the rigs we track, the Mac mini M5 Pro at $1,699, estimated ~82 tok/s at 4-bit. Prices checked 2026-10-23.

Which quant should I use for GPT-OSS 20B?

MXFP4 (native) is the default: about 13 GB. Q8_0 needs about 25 GB; use it only if you have the room and still get usable speed.

How fast does GPT-OSS 20B run?

It has 3.6B active parameters per token, so speed is set by memory bandwidth: from ~69 tok/s on the slowest rig that fits to ~264 tok/s on the NVIDIA GeForce RTX 5090 Founders Edition. Estimates, not benchmarks.

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