Qwen3 30B A3B Instruct 2507 vs Qwen3 32B
Qwen3 30B A3B Instruct 2507 and Qwen3 32B match in llmrun Score, with values of 96.5 versus 98.4; both fit 24 GB at Q4_K_M; Qwen3 30B A3B Instruct 2507 is 5.4× faster on RTX 4090 (~173 vs ~32 tok/s).
Model A · Alibaba
Qwen3 30B A3B Instruct 250730.5B · 3.4B active · 256K context · Apache 2.0 · Jul 2025
Choose Qwen3 30B A3B Instruct 2507 if you want…
5.4× faster on RTX 4090
~173 vs ~32 tok/s
Longer context window
256K vs 40K tokens
Newer release
Jul 2025 vs Apr 2025
Qwen3 32B: no clear edge over Qwen3 30B A3B Instruct 2507 in the data we have.
On your hardware
Each model at its default quant (Q4_K_M), a smaller one when it must. Estimates, ±20%.
8 GB
RTX 4060 · 8 GB tier
Qwen3 30B A3B Instruct 2507
Doesn't fit
smallest quant needs 9.5 GB
Qwen3 32B
Doesn't fit
smallest quant needs 12 GB
12 GB
RTX 3060 12GB · 12 GB tier
Qwen3 30B A3B Instruct 2507
IQ2_M · ~130 tok/s
11.4 GB · up to 16K
Qwen3 32B
IQ2_XXS · ~24 tok/s
12 GB · up to 16K
16 GB
RTX 5060 Ti 16GB · 16 GB tier
Qwen3 30B A3B Instruct 2507
Q3_K_M · ~119 tok/s
16 GB · up to 16K
Qwen3 32B
IQ3_XXS · ~22 tok/s
15.7 GB · up to 16K
24 GBreference
RTX 4090 · 24 GB tier
Qwen3 30B A3B Instruct 2507
Q4_K_M · ~173 tok/s
19.4 GB · up to 64Kfaster
Qwen3 32B
Q4_K_M · ~32 tok/s
22.6 GB · up to 16K
32 GB
RTX 5090 · 32 GB tier
Qwen3 30B A3B Instruct 2507
Q4_K_M · ~227 tok/s
19.4 GB · up to 256Kfaster
Qwen3 32B
Q4_K_M · ~57 tok/s
22.6 GB · up to 40K
48 GB
RTX A6000 · 48 GB tier
Qwen3 30B A3B Instruct 2507
Q4_K_M · ~148 tok/s
19.4 GB · up to 256Kfaster
Qwen3 32B
Q4_K_M · ~25 tok/s
22.6 GB · up to 40K
Mac 32 GB
Mac Mini M4 · Macs
Qwen3 30B A3B Instruct 2507
Q4_K_M · ~29 tok/s
19.4 GB · up to 128Kfaster
Qwen3 32B
Q4_K_M · ~4 tok/s
22.6 GB · up to 40K
Mac 64 GB
Mac Studio M4 Max · Macs
Qwen3 30B A3B Instruct 2507
Q4_K_M · ~67 tok/s
19.4 GB · up to 256Kfaster
Qwen3 32B
Q4_K_M · ~19 tok/s
22.6 GB · up to 40K
Mac 128 GB
Mac Studio M4 Max · Macs
Qwen3 30B A3B Instruct 2507
Q4_K_M · ~67 tok/s
19.4 GB · up to 256Kfaster
Qwen3 32B
Q4_K_M · ~19 tok/s
22.6 GB · up to 40K
Reference GPU: RTX 4090. Tinted cell = the better pick on that machine (fits, more headroom, or at least 10% faster).
Overall
Qwen3 30B A3B Instruct 2507
Qwen3 32B
Coding
Qwen3 30B A3B Instruct 2507
no data
Qwen3 32B
Science
Qwen3 30B A3B Instruct 2507
no data
Qwen3 32B
Reasoning
Qwen3 30B A3B Instruct 2507
Qwen3 32B
Qwen3 30B A3B Instruct 2507 · #56 of 92 open models · #14 of 34 that fit 24 GB
Qwen3 32B · #52 of 92 open models · #11 of 34 that fit 24 GB
Benchmarks
6 shared boards: Qwen3 30B A3B Instruct 2507 leads 2, Qwen3 32B leads 3 · Benchmarks imported Oct 2026
Qwen3 30B A3B Instruct 2507
55.6%#48/97 open
IndependentEpoch AI · Jul 2025
Qwen3 32B
65.7%#36/97 open
IndependentEpoch AI · Apr 2025
Qwen3 30B A3B Instruct 2507
1382.4#59/186 open
ArenaLMArena · Oct 2026
Qwen3 32B
1346.9#78/186 open
ArenaLMArena · Oct 2026
Qwen3 30B A3B Instruct 2507
62.2%#35/85 open
IndependentEpoch AI · Jul 2025
Qwen3 32B
66.9%#30/85 open
IndependentEpoch AI · Apr 2025
Qwen3 30B A3B Instruct 2507
2.0%#39/67 open
IndependentEpoch AI · Jul 2025
Qwen3 32B
5.0%#30/67 open
IndependentEpoch AI · Apr 2025
Qwen3 30B A3B Instruct 2507
67.2%#36/68 open
Lab-reportedEpoch AI · Jul 2025
Qwen3 32B
67.5%#35/68 open
Lab-reportedEpoch AI · Apr 2025
Qwen3 30B A3B Instruct 2507
22.4%#31/54 open
Lab-reportedEpoch AI · Jul 2025
Qwen3 32B
17.3%#37/54 open
Lab-reportedEpoch AI · Apr 2025
4 more boards (other shared and single-model boards)
Only Qwen3 32B (4)
- Aider Polyglot40.0%
- SciCode35.4%
- CritPt0.3%
- Fiction.LiveBench74.2%
VRAM by quantization
Memory to load the model and 2K context; below it, the total at 32K and 128K context. Lighter side in bold.
Q2_K
Qwen3 30B A3B Instruct 2507
13.4 GB11.3 GB file
32K 14.9 GB · 128K 19.7 GB
Qwen3 32B
14.6 GB12.3 GB file
32K 19.6 GB · 128K —
Q3_K_S
Qwen3 30B A3B Instruct 2507
13.8 GB13.3 GB file
32K 15.3 GB · 128K 20.1 GB
Qwen3 32B
15.0 GB14.4 GB file
32K 20.0 GB · 128K —
Q3_K_M
Qwen3 30B A3B Instruct 2507
15.3 GB14.7 GB file
32K 16.8 GB · 128K 21.6 GB
Qwen3 32B
16.6 GB16.0 GB file
32K 21.6 GB · 128K —
Q4_0
Qwen3 30B A3B Instruct 2507
15.7 GB17.4 GB file
32K 17.2 GB · 128K 22.0 GB
Qwen3 32B
17.0 GB18.7 GB file
32K 22.1 GB · 128K —
Q4_K_M
Qwen3 30B A3B Instruct 2507
18.7 GB18.6 GB file
32K 20.2 GB · 128K 25.1 GB
Qwen3 32B
20.3 GB19.8 GB file
32K 25.3 GB · 128K —
Q5_K_M
Qwen3 30B A3B Instruct 2507
22.2 GB21.7 GB file
32K 23.7 GB · 128K 28.5 GB
Qwen3 32B
24.0 GB23.2 GB file
32K 29.0 GB · 128K —
Q6_K
Qwen3 30B A3B Instruct 2507
25.6 GB25.1 GB file
32K 27.1 GB · 128K 31.9 GB
Qwen3 32B
27.7 GB26.9 GB file
32K 32.7 GB · 128K —
Q8_0
Qwen3 30B A3B Instruct 2507
30.9 GB32.5 GB file
32K 32.4 GB · 128K 37.3 GB
Qwen3 32B
33.4 GB34.8 GB file
32K 38.4 GB · 128K —
19 more quants
IQ2_XXS
Qwen3 30B A3B Instruct 2507
8.8 GB10.3 GB file
32K 10.3 GB · 128K 15.1 GB
Qwen3 32B
9.7 GB9.3 GB file
32K 14.7 GB · 128K —
IQ2_XS
Qwen3 30B A3B Instruct 2507
9.6 GB8.7 GB file
32K 11.1 GB · 128K 15.9 GB
Qwen3 32B
10.5 GB10.0 GB file
32K 15.5 GB · 128K —
IQ2_S
Qwen3 30B A3B Instruct 2507
9.9 GB8.7 GB file
32K 11.5 GB · 128K 16.3 GB
Qwen3 32B
10.9 GB10.5 GB file
32K 15.9 GB · 128K —
IQ2_M
Qwen3 30B A3B Instruct 2507
10.7 GB10.8 GB file
32K 12.2 GB · 128K 17.1 GB
Qwen3 32B
11.7 GB11.6 GB file
32K 16.7 GB · 128K —
IQ3_XXS
Qwen3 30B A3B Instruct 2507
12.2 GB12.9 GB file
32K 13.7 GB · 128K 18.6 GB
Qwen3 32B
13.3 GB13.0 GB file
32K 18.4 GB · 128K —
Q2_K_S
Qwen3 30B A3B Instruct 2507
12.6 GB10.5 GB file
32K 14.1 GB · 128K 19.0 GB
Qwen3 32B
not listed
IQ3_XS
Qwen3 30B A3B Instruct 2507
13.0 GB12.7 GB file
32K 14.5 GB · 128K 19.3 GB
Qwen3 32B
14.2 GB13.7 GB file
32K 19.2 GB · 128K —
IQ3_S
Qwen3 30B A3B Instruct 2507
13.4 GB10.3 GB file
32K 14.9 GB · 128K 19.7 GB
Qwen3 32B
not listed
IQ3_M
Qwen3 30B A3B Instruct 2507
14.1 GB14.1 GB file
32K 15.7 GB · 128K 20.5 GB
Qwen3 32B
15.4 GB14.9 GB file
32K 20.4 GB · 128K —
Q3_K_L
Qwen3 30B A3B Instruct 2507
16.1 GB15.9 GB file
32K 17.6 GB · 128K 22.4 GB
Qwen3 32B
17.4 GB17.3 GB file
32K 22.5 GB · 128K —
IQ4_XS
Qwen3 30B A3B Instruct 2507
16.8 GB16.4 GB file
32K 18.3 GB · 128K 23.2 GB
Qwen3 32B
18.3 GB17.7 GB file
32K 23.3 GB · 128K —
IQ4_NL
Qwen3 30B A3B Instruct 2507
17.6 GB17.3 GB file
32K 19.1 GB · 128K 23.9 GB
Qwen3 32B
19.1 GB18.7 GB file
32K 24.1 GB · 128K —
Q4_1
Qwen3 30B A3B Instruct 2507
17.6 GB19.2 GB file
32K 19.1 GB · 128K 23.9 GB
Qwen3 32B
19.1 GB20.6 GB file
32K 24.1 GB · 128K —
Q4_K_S
Qwen3 30B A3B Instruct 2507
17.6 GB17.5 GB file
32K 19.1 GB · 128K 23.9 GB
Qwen3 32B
19.1 GB18.8 GB file
32K 24.1 GB · 128K —
Q4_K_L
Qwen3 30B A3B Instruct 2507
19.1 GB18.9 GB file
32K 20.6 GB · 128K 25.4 GB
Qwen3 32B
20.7 GB20.3 GB file
32K 25.7 GB · 128K —
Q5_0
Qwen3 30B A3B Instruct 2507
19.5 GB21.1 GB file
32K 21.0 GB · 128K 25.8 GB
Qwen3 32B
21.1 GB22.6 GB file
32K 26.1 GB · 128K —
Q5_K_S
Qwen3 30B A3B Instruct 2507
21.4 GB21.1 GB file
32K 22.9 GB · 128K 27.7 GB
Qwen3 32B
23.2 GB22.6 GB file
32K 28.2 GB · 128K —
Q5_K_L
Qwen3 30B A3B Instruct 2507
22.5 GB21.9 GB file
32K 24.1 GB · 128K 28.9 GB
Qwen3 32B
24.4 GB23.7 GB file
32K 29.4 GB · 128K —
BF16
Qwen3 30B A3B Instruct 2507
61.5 GB61.1 GB file
32K 63.0 GB · 128K 67.8 GB
Qwen3 32B
66.2 GB65.5 GB file
32K 71.2 GB · 128K —
Qwen3 30B A3B Instruct 2507
Ollama · Q4_K_M
ollama run hf.co/unsloth/Qwen3-30B-A3B-Instruct-2507-GGUF:Q4_K_MQwen3 32B
Ollama · Q4_K_M
ollama run hf.co/MaziyarPanahi/Qwen3-32B-GGUF:Q4_K_M| Spec | Qwen3 30B A3B Instruct 2507 | Qwen3 32B |
|---|---|---|
| Publisher | Alibaba | Alibaba |
| Parameters | 30.5B | 32.8B |
| Active parameters | 3.4B per token | — |
| Architecture | Qwen3MoeForCausalLM | Qwen3ForCausalLM |
| Context | 256K tokens | 40K tokens |
| Modalities | Chat, Function-calling | Chat, Function-calling |
| License | Apache 2.0 | Apache 2.0 |
| Released | Jul 2025 | Apr 2025 |
Frequently Asked Questions
Which is better, Qwen3 30B A3B Instruct 2507 or Qwen3 32B?
Qwen3 30B A3B Instruct 2507 and Qwen3 32B match in llmrun Score, with values of 96.5 versus 98.4; both fit 24 GB at Q4_K_M; Qwen3 30B A3B Instruct 2507 is 5.4× faster on RTX 4090 (~173 vs ~32 tok/s). Choose Qwen3 30B A3B Instruct 2507 for 5.4× faster on RTX 4090 and longer context window.
Which needs less VRAM, Qwen3 30B A3B Instruct 2507 or Qwen3 32B?
At Q4_K_M, Qwen3 30B A3B Instruct 2507 requires 18.7 GB while Qwen3 32B needs 20.3 GB, making Qwen3 30B A3B Instruct 2507 the easier model to run on your local setup.
Which is faster on RTX 4090?
Estimated decode speed on RTX 4090 is about 173 tok/s for Qwen3 30B A3B Instruct 2507 (Q4_K_M) and 32 tok/s for Qwen3 32B (Q4_K_M), so Qwen3 30B A3B Instruct 2507 is faster. Estimates, ±20%.
Can I run Qwen3 30B A3B Instruct 2507 or Qwen3 32B on a 16 GB GPU?
Qwen3 30B A3B Instruct 2507 fits at Q3_K_M; Qwen3 32B fits at IQ3_XXS.
Which has a longer context window, Qwen3 30B A3B Instruct 2507 or Qwen3 32B?
Qwen3 30B A3B Instruct 2507 supports 262,144 tokens and Qwen3 32B supports 40,960 tokens.