Gemma 4 31B IT vs Qwen3.5 35B A3B
Gemma 4 31B IT and Qwen3.5 35B A3B match in llmrun Score, with values of 106.1 versus 105.6; both fit 24 GB at Q4_K_M; Qwen3.5 35B A3B is 4.7× faster on RTX 4090 (~151 vs ~32 tok/s).
Model A · Google
Gemma 4 31B IT31.3B · 256K context · Apache 2.0 · Mar 2026
Model B · Alibaba
Qwen3.5 35B A3B36.0B · 4.7B active · 256K context · Apache 2.0 · Feb 2026
Choose Gemma 4 31B IT if you want…
Ahead on the benchmarks
7 of 9 shared boards
Fits a 16 GB GPU
IQ3_XS · 15.8 GB; Qwen3.5 35B A3B needs 15.7 GB at its smallest quant
Also does function-calling
Qwen3.5 35B A3B doesn't list it
Choose Qwen3.5 35B A3B if you want…
4.7× faster on RTX 4090
~151 vs ~32 tok/s
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
Gemma 4 31B IT
Doesn't fit
smallest quant needs 11.5 GB
Qwen3.5 35B A3B
Doesn't fit
smallest quant needs 15.7 GB
12 GB
RTX 3060 12GB · 12 GB tier
Gemma 4 31B IT
IQ2_XXS · ~23 tok/s
11.5 GB · up to 16Kfits
Qwen3.5 35B A3B
Doesn't fit
smallest quant needs 15.7 GB
16 GB
RTX 5060 Ti 16GB · 16 GB tier
Gemma 4 31B IT
IQ3_XS · ~20 tok/s
15.8 GB · up to 16Kbetter quant
Qwen3.5 35B A3B
Q2_K · ~108 tok/s
15.7 GB · up to 32K
24 GBreference
RTX 4090 · 24 GB tier
Gemma 4 31B IT
Q4_K_M · ~32 tok/s
21.7 GB · up to 32K
Qwen3.5 35B A3B
Q4_K_M · ~151 tok/s
22 GB · up to 128Kfaster
32 GB
RTX 5090 · 32 GB tier
Gemma 4 31B IT
Q4_K_M · ~57 tok/s
21.7 GB · up to 64K
Qwen3.5 35B A3B
Q4_K_M · ~213 tok/s
22 GB · up to 256Kfaster
48 GB
RTX A6000 · 48 GB tier
Gemma 4 31B IT
Q4_K_M · ~25 tok/s
21.7 GB · up to 128K
Qwen3.5 35B A3B
Q4_K_M · ~125 tok/s
22 GB · up to 256Kfaster
Mac 32 GB
Mac Mini M4 · Macs
Gemma 4 31B IT
Q4_K_M · ~4 tok/s
21.7 GB · up to 64K
Qwen3.5 35B A3B
Q4_K_M · ~24 tok/s
22 GB · up to 256Kfaster
Mac 64 GB
Mac Studio M4 Max · Macs
Gemma 4 31B IT
Q4_K_M · ~19 tok/s
21.7 GB · up to 256K
Qwen3.5 35B A3B
Q4_K_M · ~64 tok/s
22 GB · up to 256Kfaster
Mac 128 GB
Mac Studio M4 Max · Macs
Gemma 4 31B IT
Q4_K_M · ~19 tok/s
21.7 GB · up to 256K
Qwen3.5 35B A3B
Q4_K_M · ~64 tok/s
22 GB · up to 256Kfaster
Reference GPU: RTX 4090. Tinted cell = the better pick on that machine (fits, more headroom, or at least 10% faster).
Overall
Gemma 4 31B IT
Qwen3.5 35B A3B
Coding
Gemma 4 31B IT
Qwen3.5 35B A3B
no data
Science
Gemma 4 31B IT
Qwen3.5 35B A3B
Reasoning
Gemma 4 31B IT
Qwen3.5 35B A3B
Gemma 4 31B IT · #35 of 92 open models · #4 of 34 that fit 24 GB
Qwen3.5 35B A3B · #36 of 92 open models · #5 of 34 that fit 24 GB
Benchmarks
9 shared boards: Gemma 4 31B IT leads 7, Qwen3.5 35B A3B leads 2 · Benchmarks imported Oct 2026
Gemma 4 31B IT
75.8%#27/97 open
IndependentEpoch AI · Apr 2026
Qwen3.5 35B A3B
83.5%#22/97 open
IndependentEpoch AI · Feb 2026
Gemma 4 31B IT
1452.4#14/186 open
ArenaLMArena · Oct 2026
Qwen3.5 35B A3B
1393.8#53/186 open
ArenaLMArena · Oct 2026
Gemma 4 31B IT
73.3%#25/85 open
IndependentEpoch AI · Apr 2026
Qwen3.5 35B A3B
70.0%#28/85 open
IndependentEpoch AI · Feb 2026
Gemma 4 31B IT
1365.9#30/50 open
ArenaLMArena · Oct 2026
Qwen3.5 35B A3B
1253.9#46/50 open
ArenaLMArena · Oct 2026
Gemma 4 31B IT
43.4%#23/65 open
Lab-reportedEpoch AI · Apr 2026
Qwen3.5 35B A3B
29.3%#52/65 open
Lab-reportedEpoch AI · Feb 2026
Gemma 4 31B IT
5.0%#29/67 open
IndependentEpoch AI · Apr 2026
Qwen3.5 35B A3B
10.0%#24/67 open
IndependentEpoch AI · Feb 2026
Gemma 4 31B IT
1.4%#29/65 open
Lab-reportedEpoch AI · Apr 2026
Qwen3.5 35B A3B
0.6%#38/65 open
Lab-reportedEpoch AI · Feb 2026
Gemma 4 31B IT
82.7%#19/68 open
Lab-reportedEpoch AI · Apr 2026
Qwen3.5 35B A3B
80.0%#23/68 open
Lab-reportedEpoch AI · Feb 2026
Gemma 4 31B IT
39.3%#9/54 open
Lab-reportedEpoch AI · Apr 2026
Qwen3.5 35B A3B
29.5%#22/54 open
Lab-reportedEpoch AI · Feb 2026
5 more boards (other shared and single-model boards)
Only Gemma 4 31B IT (4)
- SimpleQA10.4%
- WeirdML52.3%
- ALE-Bench925.5
- Surface Evolver Bench30.6%
Only Qwen3.5 35B A3B (1)
- MMLU-Pro85.3%
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
Gemma 4 31B IT
14.9 GB12.6 GB file
32K 18.4 GB · 128K 31.0 GB
Qwen3.5 35B A3B
15.7 GB~15.3 GB file
32K 15.9 GB · 128K 16.9 GB
Q3_K_S
Gemma 4 31B IT
15.3 GB13.2 GB file
32K 18.7 GB · 128K 31.4 GB
Qwen3.5 35B A3B
not listed
Q3_K_M
Gemma 4 31B IT
16.9 GB14.7 GB file
32K 20.3 GB · 128K 33.0 GB
Qwen3.5 35B A3B
17.9 GB~17.5 GB file
32K 18.2 GB · 128K 19.2 GB
Q4_0
Gemma 4 31B IT
17.3 GB17.3 GB file
32K 20.7 GB · 128K 33.4 GB
Qwen3.5 35B A3B
not listed
Q4_K_M
Gemma 4 31B IT
20.4 GB18.3 GB file
32K 23.8 GB · 128K 36.5 GB
Qwen3.5 35B A3B
22.0 GB~21.6 GB file
32K 22.2 GB · 128K 23.2 GB
Q5_K_M
Gemma 4 31B IT
23.9 GB21.7 GB file
32K 27.3 GB · 128K 40.0 GB
Qwen3.5 35B A3B
26.0 GB~25.6 GB file
32K 26.3 GB · 128K 27.3 GB
Q6_K
Gemma 4 31B IT
27.4 GB25.2 GB file
32K 30.9 GB · 128K 43.5 GB
Qwen3.5 35B A3B
30.0 GB~29.7 GB file
32K 30.3 GB · 128K 31.3 GB
Q8_0
Gemma 4 31B IT
32.9 GB~31.3 GB file
32K 36.3 GB · 128K 49.0 GB
Qwen3.5 35B A3B
36.3 GB~36.0 GB file
32K 36.6 GB · 128K 37.6 GB
19 more quants
IQ2_XXS
Gemma 4 31B IT
10.2 GB8.5 GB file
32K 13.7 GB · 128K 26.3 GB
Qwen3.5 35B A3B
not listed
IQ2_XS
Gemma 4 31B IT
11.0 GB11.5 GB file
32K 14.4 GB · 128K 27.1 GB
Qwen3.5 35B A3B
not listed
IQ2_S
Gemma 4 31B IT
11.4 GB12.1 GB file
32K 14.8 GB · 128K 27.5 GB
Qwen3.5 35B A3B
not listed
IQ2_M
Gemma 4 31B IT
12.2 GB10.8 GB file
32K 15.6 GB · 128K 28.3 GB
Qwen3.5 35B A3B
not listed
IQ3_XXS
Gemma 4 31B IT
13.7 GB11.8 GB file
32K 17.2 GB · 128K 29.9 GB
Qwen3.5 35B A3B
not listed
Q2_K_S
Gemma 4 31B IT
14.1 GB11.0 GB file
32K 17.6 GB · 128K 30.3 GB
Qwen3.5 35B A3B
not listed
IQ3_XS
Gemma 4 31B IT
14.5 GB13.8 GB file
32K 18.0 GB · 128K 30.6 GB
Qwen3.5 35B A3B
not listed
IQ3_S
Gemma 4 31B IT
14.9 GB13.8 GB file
32K 18.4 GB · 128K 31.0 GB
Qwen3.5 35B A3B
not listed
IQ3_M
Gemma 4 31B IT
15.7 GB15.1 GB file
32K 19.1 GB · 128K 31.8 GB
Qwen3.5 35B A3B
not listed
Q3_K_L
Gemma 4 31B IT
17.7 GB16.8 GB file
32K 21.1 GB · 128K 33.8 GB
Qwen3.5 35B A3B
not listed
IQ4_XS
Gemma 4 31B IT
18.4 GB16.4 GB file
32K 21.9 GB · 128K 34.6 GB
Qwen3.5 35B A3B
not listed
IQ4_NL
Gemma 4 31B IT
19.2 GB17.3 GB file
32K 22.7 GB · 128K 35.3 GB
Qwen3.5 35B A3B
not listed
Q4_1
Gemma 4 31B IT
19.2 GB19.1 GB file
32K 22.7 GB · 128K 35.3 GB
Qwen3.5 35B A3B
not listed
Q4_K_S
Gemma 4 31B IT
19.2 GB17.4 GB file
32K 22.7 GB · 128K 35.3 GB
Qwen3.5 35B A3B
not listed
Q4_K_L
Gemma 4 31B IT
20.8 GB19.9 GB file
32K 24.2 GB · 128K 36.9 GB
Qwen3.5 35B A3B
not listed
Q5_0
Gemma 4 31B IT
21.2 GB21.3 GB file
32K 24.6 GB · 128K 37.3 GB
Qwen3.5 35B A3B
not listed
Q5_K_S
Gemma 4 31B IT
23.1 GB21.1 GB file
32K 26.6 GB · 128K 39.2 GB
Qwen3.5 35B A3B
not listed
Q5_K_L
Gemma 4 31B IT
24.3 GB23.0 GB file
32K 27.7 GB · 128K 40.4 GB
Qwen3.5 35B A3B
not listed
BF16
Gemma 4 31B IT
64.2 GB~62.5 GB file
32K 67.6 GB · 128K 80.3 GB
Qwen3.5 35B A3B
72.3 GB~71.9 GB file
32K 72.5 GB · 128K 73.6 GB
Gemma 4 31B IT
Ollama · Q4_K_M
ollama run hf.co/unsloth/gemma-4-31B-it-GGUF:Q4_K_MQwen3.5 35B A3B
No local recipe · Q4_K_M
No GGUF repo entry exists for this model yet.
All ways to run Qwen3.5 35B A3B →| Spec | Gemma 4 31B IT | Qwen3.5 35B A3B |
|---|---|---|
| Publisher | Alibaba | |
| Parameters | 31.3B | 36.0B |
| Active parameters | — | 4.7B per token |
| Architecture | Gemma4ForConditionalGeneration | Qwen3_5MoeForConditionalGeneration |
| Context | 256K tokens | 256K tokens |
| Modalities | Vision, Function-calling | Vision |
| License | Apache 2.0 | Apache 2.0 |
| Released | Mar 2026 | Feb 2026 |
Frequently Asked Questions
Which is better, Gemma 4 31B IT or Qwen3.5 35B A3B?
Gemma 4 31B IT and Qwen3.5 35B A3B match in llmrun Score, with values of 106.1 versus 105.6; both fit 24 GB at Q4_K_M; Qwen3.5 35B A3B is 4.7× faster on RTX 4090 (~151 vs ~32 tok/s). Choose Gemma 4 31B IT for ahead on the benchmarks and fits a 16 GB GPU; choose Qwen3.5 35B A3B for 4.7× faster on RTX 4090.
Which needs less VRAM, Gemma 4 31B IT or Qwen3.5 35B A3B?
At Q4_K_M, Gemma 4 31B IT requires 20.4 GB while Qwen3.5 35B A3B needs 22.0 GB, making Gemma 4 31B IT the easier model to run on your local setup.
Which is faster on RTX 4090?
Estimated decode speed on RTX 4090 is about 32 tok/s for Gemma 4 31B IT (Q4_K_M) and 151 tok/s for Qwen3.5 35B A3B (Q4_K_M), so Qwen3.5 35B A3B is faster. Estimates, ±20%.
Can I run Gemma 4 31B IT or Qwen3.5 35B A3B on a 16 GB GPU?
Gemma 4 31B IT fits at IQ3_XS; Qwen3.5 35B A3B fits at Q2_K.
Which has a longer context window, Gemma 4 31B IT or Qwen3.5 35B A3B?
Gemma 4 31B IT supports 262,144 tokens and Qwen3.5 35B A3B supports 262,144 tokens.