The best GPU for running gpt-oss 120B (MoE) (2026)
Ranked from live rental prices and computed VRAM fit, not opinion. Every card is judged at Q4_K_M — the quantisation most people actually run — at 8k context, so it's a fair comparison. A card that can't fit gpt-oss 120B (MoE)at that quality isn't listed, because it could only run a crushed version.
Best value
NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition
Best throughput per dollar among cards that fit.
Cheapest that runs it
NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition
Lowest hourly rental that fits it — $1.690/hr, Q4_K_M.
No compromise
—
Most headroom and highest throughput.
Every card that runs it, ranked
Best quantisation each card fits at 8k context, with the cheapest live rental and a bandwidth-derived throughput estimate. Sorted by tokens/sec per dollar.
| GPU | VRAM | VRAM used | ~tok/s | Cheapest rental | tok/s per $ |
|---|---|---|---|---|---|
| NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition | 96 GB | 69 GB72% | — | $1.690 | — |
| NVIDIA RTX PRO 6000 Blackwell Workstation Edition | 96 GB | 69 GB72% | — | — | — |
How this ranking is made — and its limit
Fit and throughput are computed from gpt-oss 120B (MoE)'s own configuration with the engine behind our cost-to-run page (bits-per-weight validated to 0.7% median error). Rental prices are the cheapest live figure across the providers we track, last updated Wed, 22 Jul 2026 11:20:07 GMT.
The value column ranks renting, because that's what we can price precisely. If you're buyinga card, the fit and throughput columns are exactly what you need — but we don't publish a purchase-price value ranking, because we don't have verified street prices and won't invent them. For the buy-vs-rent decision itself, see the guides below.
Tokens/sec is a bandwidth-derived estimate, not a benchmark — we don't run our own hardware tests (editorial policy). This is a mixture-of-experts model without a known active-parameter count, so throughput is omitted rather than guessed.
Check it yourself
See exactly what fits, at any context length
Running gpt-oss 120B (MoE): common questions
How much VRAM do you need to run gpt-oss 120B (MoE)?
Can an RTX 4090 run gpt-oss 120B (MoE)?
Can an RTX 3090 run gpt-oss 120B (MoE)?
Can an RTX 4060 Ti 16GB run gpt-oss 120B (MoE)?
What's the cheapest way to run gpt-oss 120B (MoE)?
Before you buy
What --n-cpu-moe actually does
The trick that makes MoE models 5× faster — except it usually makes them slower, and the famous speedup only happens when the model didn't fit in the first place.
Is the DGX Spark worth it?
NVIDIA spent three months optimising it and token generation got slower — because 128 GB of memory on a 273 GB/s bus holds huge models and reads them slowly. Who should actually buy one.
RTX 5090 vs two RTX 3090s
Two 3090s give you 48 GB but not double the speed for chat — llama.cpp's default multi-GPU mode makes the cards take turns. What the benchmarks actually show.