Which needs less VRAM, gpt-oss-20b or Qwen3-30B-A3B?

gpt-oss-20b: about 15.6 GB at Q4_K_M, against 22.3 GB for Qwen3-30B-A3B. At Q8_0 it's 26.6 GB vs 38.3 GB.

Which is faster locally, gpt-oss-20b or Qwen3-30B-A3B?

Decode speed is limited by how many bytes are read per token. Qwen3-30B-A3B reads 3.0B parameters per token and gpt-oss-20b reads 3.6B, so Qwen3-30B-A3B should be faster on the same machine. Our estimate on the GeForce RTX 5090 at Q4 is up to 837 tok/s vs up to 698 tok/s. These are estimates, not benchmarks.

What is the cheapest GPU for gpt-oss-20b and Qwen3-30B-A3B?

At Q4: Radeon RX 7900 XT ($899) for gpt-oss-20b; Intel Arc Pro B70 32GB ($949) for Qwen3-30B-A3B. Prices are dated list-price snapshots.

Can a Mac run gpt-oss-20b and Qwen3-30B-A3B?

The cheapest Mac or mini PC we track for gpt-oss-20b is the Mac mini M6 24GB ($1,299). For Qwen3-30B-A3B it's the Mac mini M5 Pro 64GB ($3,199).

Which is better, gpt-oss-20b or Qwen3-30B-A3B?

We don't score answer quality. This comparison covers memory, context cache, hardware and speed. Pick the one that fits your hardware, then test both on your own prompts.

gpt-oss-20b vs Qwen3-30B-A3B: VRAM and speed for running locally

Side by side: how much memory each model needs at Q4, Q8 and FP16, how the KV cache grows with context, the cheapest GPU and Mac that run each, and estimated speed on 11 common machines.

gpt-oss-20b is lighter: about 15.6 GB at Q4 against 22.3 GB for Qwen3-30B-A3B, so it runs on 28 tracked devices vs 16. Qwen3-30B-A3B should be faster on the same hardware, since it reads 3.0B parameters per token against 3.6B. Which one gives better answers depends on your task, so check benchmarks for that; this page covers what it takes to run them.

gpt-oss-20b vs Qwen3-30B-A3B: specs and memory
	gpt-oss-20b	Qwen3-30B-A3B
Maker	openai	Qwen
License	apache-2.0	apache-2.0
Type	Mixture of experts	Mixture of experts
Total parameters	20.9B	30.5B
Active per token	3.6B	3.0B
Memory at Q4_K_M	15.6 GB	22.3 GB
Memory at Q8_0	26.6 GB	38.3 GB
Memory at FP16	49.1 GB	71.2 GB
KV cache growth	49 MB per 1k tokens, FP16	98 MB per 1k tokens, FP16
Memory at Q4, 32k context	16.3 GB 0.8 GB cache	25.1 GB 3.2 GB cache
Cheapest GPU at Q4	Radeon RX 7900 XT $899	Intel Arc Pro B70 32GB $949
Cheapest Mac / mini PC at Q4	Mac mini M6 24GB $1,299	Mac mini M5 Pro 64GB $3,199
Cheapest GPU at Q8	Intel Arc Pro B70 32GB $949	NVIDIA RTX 6000 Ada 48GB $6,799
Tracked devices that run it at Q4	28 of 82	16 of 82

Estimated speed on the same hardware

Decode tokens per second at Q4_K_M from memory bandwidth (how we estimate). MoE figures are upper bounds ("up to"). Estimates, not benchmarks.

Estimated tokens per second, gpt-oss-20b vs Qwen3-30B-A3B
Device	gpt-oss-20b	Qwen3-30B-A3B
GeForce RTX 3060 12GB12 GB usable · 360 GB/s · $329	doesn’t fit	doesn’t fit
GeForce RTX 4060 Ti 16GB16 GB usable · 288 GB/s · $499	tight fit	doesn’t fit
GeForce RTX 508016 GB usable · 960 GB/s · $999	tight fit	doesn’t fit
GeForce RTX 309024 GB usable · 936 GB/s · $1,499	up to 365	tight fit
Radeon RX 7900 XTX24 GB usable · 960 GB/s · $999	up to 374	tight fit
GeForce RTX 509032 GB usable · 1792 GB/s · $1,999	up to 698	up to 837
Mac mini M6 24GB18 GB usable · 170 GB/s · $1,299	up to 62	doesn’t fit
Mac mini M6 32GB24 GB usable · 170 GB/s · $1,799	up to 62	tight fit
Mac mini M5 Pro 64GB48 GB usable · 307 GB/s · $3,199	up to 113	up to 135
Framework Desktop (Ryzen AI Max+ 395) 128GB96 GB usable · 256 GB/s · $3,449	up to 94	up to 113
MacBook Pro M5 Max 128GB96 GB usable · 614 GB/s · $6,699	up to 225	up to 270

Hardware that runs only one of them

Run gpt-oss-20b but not Qwen3-30B-A3B: Radeon RX 7900 XT, Radeon RX 7900 XTX, NVIDIA RTX 4000 Ada 20GB, Mac mini M6 24GB, GeForce RTX 3090, GeForce RTX 4090, Mac mini M6 32GB, GeForce RTX 3090 Ti and 1 more.

Current priced devices, cheapest first, at Q4 with ~4k context.

Quick answers

Which needs less VRAM, gpt-oss-20b or Qwen3-30B-A3B?: gpt-oss-20b: about 15.6 GB at Q4_K_M, against 22.3 GB for Qwen3-30B-A3B. At Q8_0 it's 26.6 GB vs 38.3 GB.
Which is faster locally, gpt-oss-20b or Qwen3-30B-A3B?: Decode speed is limited by how many bytes are read per token. Qwen3-30B-A3B reads 3.0B parameters per token and gpt-oss-20b reads 3.6B, so Qwen3-30B-A3B should be faster on the same machine. Our estimate on the GeForce RTX 5090 at Q4 is up to 837 tok/s vs up to 698 tok/s. These are estimates, not benchmarks.
What is the cheapest GPU for gpt-oss-20b and Qwen3-30B-A3B?: At Q4: Radeon RX 7900 XT ($899) for gpt-oss-20b; Intel Arc Pro B70 32GB ($949) for Qwen3-30B-A3B. Prices are dated list-price snapshots.
Can a Mac run gpt-oss-20b and Qwen3-30B-A3B?: The cheapest Mac or mini PC we track for gpt-oss-20b is the Mac mini M6 24GB ($1,299). For Qwen3-30B-A3B it's the Mac mini M5 Pro 64GB ($3,199).
Which is better, gpt-oss-20b or Qwen3-30B-A3B?: We don't score answer quality. This comparison covers memory, context cache, hardware and speed. Pick the one that fits your hardware, then test both on your own prompts.

Related comparisons

Qwen3-30B-A3B vs Gemma 4 26B A4B22.3 vs 19.0 GB

All comparisons · MoE vs dense · Q4 vs Q8 vs FP16 · Context length and VRAM · VRAM calculator

gpt-oss-20b vs Qwen3-30B-A3B: VRAM and speed for running locally

Estimated speed on the same hardware

Hardware that runs only one of them

Quick answers

Related comparisons

New models, and what they need to run