Gemma 4 31B IT vs QwQ 32B
Gemma 4 31B IT leads llmrun Score 106.7 to 96.2; both fit 24 GB at Q4_K_M.
Model A · Google
Gemma 4 31B IT31.3B · 256K context · Apache 2.0 · Mar 2026
Model B · Alibaba
QwQ 32B32.8B · 40K context · Apache 2.0 · Mar 2025
Choose Gemma 4 31B IT if you want…
Higher llmrun Score
106.7 vs 96.2
Fits a 16 GB GPU
IQ3_XS · 15.8 GB; QwQ 32B needs 13.6 GB at its smallest quant
Longer context window
256K vs 40K tokens
Also does vision
QwQ 32B doesn't list it
Newer release
Mar 2026 vs Mar 2025
Choose QwQ 32B if you want…
Also does chat, reasoning
Gemma 4 31B IT doesn't list it
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
QwQ 32B
Doesn't fit
smallest quant needs 13.6 GB
12 GB
RTX 3060 12GB · 12 GB tier
Gemma 4 31B IT
IQ2_XXS · ~23 tok/s
11.5 GB · up to 16Kfits
QwQ 32B
Doesn't fit
smallest quant needs 13.6 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
QwQ 32B
IQ2_M · ~25 tok/s
15.7 GB · up to 16K
24 GBreference
RTX 4090 · 24 GB tier
Gemma 4 31B IT
Q4_K_M · ~32 tok/s
21.7 GB · up to 32Kmore headroom
QwQ 32B
Q4_K_M · ~32 tok/stight
24.3 GB · up to 8K
32 GB
RTX 5090 · 32 GB tier
Gemma 4 31B IT
Q4_K_M · ~57 tok/s
21.7 GB · up to 64K
QwQ 32B
Q4_K_M · ~57 tok/s
24.3 GB · up to 40K
48 GB
RTX A6000 · 48 GB tier
Gemma 4 31B IT
Q4_K_M · ~25 tok/s
21.7 GB · up to 128K
QwQ 32B
Q4_K_M · ~24 tok/s
24.3 GB · up to 40K
Mac 32 GB
Mac Mini M4 · Macs
Gemma 4 31B IT
Q4_K_M · ~4 tok/s
21.7 GB · up to 64K
QwQ 32B
Q4_K_M · ~4 tok/s
24.3 GB · up to 16K
Mac 64 GB
Mac Studio M4 Max · Macs
Gemma 4 31B IT
Q4_K_M · ~19 tok/s
21.7 GB · up to 256K
QwQ 32B
Q4_K_M · ~19 tok/s
24.3 GB · up to 40K
Mac 128 GB
Mac Studio M4 Max · Macs
Gemma 4 31B IT
Q4_K_M · ~19 tok/s
21.7 GB · up to 256K
QwQ 32B
Q4_K_M · ~19 tok/s
24.3 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
Gemma 4 31B IT
QwQ 32B
Coding
Gemma 4 31B IT
QwQ 32B
no data
Science
Gemma 4 31B IT
QwQ 32B
no data
Reasoning
Gemma 4 31B IT
QwQ 32B
no data
Gemma 4 31B IT · #42 of 106 open models · #4 of 36 that fit 24 GB
QwQ 32B · #70 of 106 open models · #17 of 36 that fit 24 GB
Gemma 4 31B IT
75.8%#30/100 open
IndependentEpoch AI · Apr 2026
QwQ 32B
65.3%#40/100 open
IndependentEpoch AI · Mar 2025
Gemma 4 31B IT
73.3%#28/88 open
IndependentEpoch AI · Apr 2026
QwQ 32B
59.2%#40/88 open
IndependentEpoch AI · Mar 2025
21 more boards (other shared and single-model boards)
Gemma 4 31B IT
1452.3#14/188 open
ArenaLMArena · Oct 2026
QwQ 32B
1335.6#86/188 open
ArenaLMArena · Oct 2026
Only Gemma 4 31B IT (17)
- LMArena WebDev1368.7
- SciCode45.5%
- SimpleQA10.4%
- WeirdML52.3%
- CritPt1.4%
- DTBench82.7%
- ForecastBench61.3
- LiveBench 2026 Reasoning68.3
- LMCA39.3%
- LiveBench 2026 Browser4.0
- LiveBench 2026 Data Analysis53.3
- ALE-Bench925.5
- LiveBench 2026 Coding49.0
- LiveBench 2026 Long-Horizon13.3
- Surface Evolver Bench30.6%
- LiveBench 2026 Design58.4
- LiveBench 2026 Research44.4
Only QwQ 32B (3)
- MMLU-Pro69.1%
- Aider Polyglot20.9%
- Fiction.LiveBench83.3%
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
QwQ 32B
14.8 GB12.3 GB file
32K 22.8 GB · 128K —
Q3_K_S
Gemma 4 31B IT
15.3 GB13.2 GB file
32K 18.7 GB · 128K 31.4 GB
QwQ 32B
15.2 GB14.4 GB file
32K 23.2 GB · 128K —
Q3_K_M
Gemma 4 31B IT
16.9 GB14.7 GB file
32K 20.3 GB · 128K 33.0 GB
QwQ 32B
16.8 GB15.9 GB file
32K 24.9 GB · 128K —
Q4_0
Gemma 4 31B IT
17.3 GB17.3 GB file
32K 20.7 GB · 128K 33.4 GB
QwQ 32B
17.2 GB18.7 GB file
32K 25.3 GB · 128K —
Q4_K_M
Gemma 4 31B IT
20.4 GB18.3 GB file
32K 23.8 GB · 128K 36.5 GB
QwQ 32B
20.5 GB19.9 GB file
32K 28.6 GB · 128K —
Q5_K_M
Gemma 4 31B IT
23.9 GB21.7 GB file
32K 27.3 GB · 128K 40.0 GB
QwQ 32B
24.2 GB23.3 GB file
32K 32.2 GB · 128K —
Q6_K
Gemma 4 31B IT
27.4 GB25.2 GB file
32K 30.9 GB · 128K 43.5 GB
QwQ 32B
27.9 GB26.9 GB file
32K 35.9 GB · 128K —
Q8_0
Gemma 4 31B IT
32.9 GB32.6 GB file
32K 36.3 GB · 128K 49.0 GB
QwQ 32B
33.6 GB34.8 GB file
32K 41.7 GB · 128K —
20 more quants
IQ2_XXS
Gemma 4 31B IT
10.2 GB8.5 GB file
32K 13.7 GB · 128K 26.3 GB
QwQ 32B
9.9 GB9.0 GB file
32K 17.9 GB · 128K —
IQ2_XS
Gemma 4 31B IT
11.0 GB11.5 GB file
32K 14.4 GB · 128K 27.1 GB
QwQ 32B
10.7 GB10.0 GB file
32K 18.7 GB · 128K —
IQ2_S
Gemma 4 31B IT
11.4 GB12.1 GB file
32K 14.8 GB · 128K 27.5 GB
QwQ 32B
11.1 GB10.4 GB file
32K 19.1 GB · 128K —
IQ2_M
Gemma 4 31B IT
12.2 GB10.8 GB file
32K 15.6 GB · 128K 28.3 GB
QwQ 32B
11.9 GB11.3 GB file
32K 19.9 GB · 128K —
IQ3_XXS
Gemma 4 31B IT
13.7 GB11.8 GB file
32K 17.2 GB · 128K 29.9 GB
QwQ 32B
13.5 GB12.8 GB file
32K 21.6 GB · 128K —
Q2_K_S
Gemma 4 31B IT
14.1 GB11.0 GB file
32K 17.6 GB · 128K 30.3 GB
QwQ 32B
13.9 GB11.5 GB file
32K 22.0 GB · 128K —
IQ3_XS
Gemma 4 31B IT
14.5 GB13.8 GB file
32K 18.0 GB · 128K 30.6 GB
QwQ 32B
14.4 GB13.7 GB file
32K 22.4 GB · 128K —
IQ3_S
Gemma 4 31B IT
14.9 GB13.8 GB file
32K 18.4 GB · 128K 31.0 GB
QwQ 32B
14.8 GB14.4 GB file
32K 22.8 GB · 128K —
IQ3_M
Gemma 4 31B IT
15.7 GB15.1 GB file
32K 19.1 GB · 128K 31.8 GB
QwQ 32B
15.6 GB14.8 GB file
32K 23.6 GB · 128K —
Q3_K_L
Gemma 4 31B IT
17.7 GB16.8 GB file
32K 21.1 GB · 128K 33.8 GB
QwQ 32B
17.6 GB17.2 GB file
32K 25.7 GB · 128K —
IQ4_XS
Gemma 4 31B IT
18.4 GB16.4 GB file
32K 21.9 GB · 128K 34.6 GB
QwQ 32B
18.5 GB17.7 GB file
32K 26.5 GB · 128K —
IQ4_NL
Gemma 4 31B IT
19.2 GB17.3 GB file
32K 22.7 GB · 128K 35.3 GB
QwQ 32B
19.3 GB18.7 GB file
32K 27.3 GB · 128K —
Q4_1
Gemma 4 31B IT
19.2 GB19.1 GB file
32K 22.7 GB · 128K 35.3 GB
QwQ 32B
19.3 GB20.6 GB file
32K 27.3 GB · 128K —
Q4_K_S
Gemma 4 31B IT
19.2 GB17.4 GB file
32K 22.7 GB · 128K 35.3 GB
QwQ 32B
19.3 GB18.8 GB file
32K 27.3 GB · 128K —
Q4_K_L
Gemma 4 31B IT
20.8 GB19.9 GB file
32K 24.2 GB · 128K 36.9 GB
QwQ 32B
20.9 GB20.4 GB file
32K 29.0 GB · 128K —
Q5_0
Gemma 4 31B IT
21.2 GB21.3 GB file
32K 24.6 GB · 128K 37.3 GB
QwQ 32B
21.3 GB22.6 GB file
32K 29.4 GB · 128K —
Q5_1
Gemma 4 31B IT
not listed
QwQ 32B
23.4 GB24.6 GB file
32K 31.4 GB · 128K —
Q5_K_S
Gemma 4 31B IT
23.1 GB21.1 GB file
32K 26.6 GB · 128K 39.2 GB
QwQ 32B
23.4 GB22.6 GB file
32K 31.4 GB · 128K —
Q5_K_L
Gemma 4 31B IT
24.3 GB23.0 GB file
32K 27.7 GB · 128K 40.4 GB
QwQ 32B
24.6 GB23.7 GB file
32K 32.6 GB · 128K —
BF16
Gemma 4 31B IT
64.2 GB61.4 GB file
32K 67.6 GB · 128K 80.3 GB
QwQ 32B
66.4 GB65.5 GB file
32K 74.4 GB · 128K —
Gemma 4 31B IT
Ollama · Q4_K_M
ollama run hf.co/unsloth/gemma-4-31B-it-GGUF:Q4_K_MQwQ 32B
Ollama · Q4_K_M
ollama run hf.co/Qwen/QwQ-32B-GGUF:Q4_K_M| Spec | Gemma 4 31B IT | QwQ 32B |
|---|---|---|
| Publisher | Alibaba | |
| Parameters | 31.3B | 32.8B |
| Architecture | Gemma4ForConditionalGeneration | Qwen2ForCausalLM |
| Context | 256K tokens | 40K tokens |
| Modalities | Vision, Function-calling | Chat, Reasoning, Function-calling |
| License | Apache 2.0 | Apache 2.0 |
| Released | Mar 2026 | Mar 2025 |
Frequently Asked Questions
Which is better, Gemma 4 31B IT or QwQ 32B?
Gemma 4 31B IT leads llmrun Score 106.7 to 96.2; both fit 24 GB at Q4_K_M. Choose Gemma 4 31B IT for higher llmrun Score and fits a 16 GB GPU; choose QwQ 32B for also does chat, reasoning.
Which needs less VRAM, Gemma 4 31B IT or QwQ 32B?
At Q4_K_M, Gemma 4 31B IT requires 20.4 GB while QwQ 32B needs 20.5 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 32 tok/s for QwQ 32B (Q4_K_M), so Gemma 4 31B IT is faster. Estimates, ±20%.
Can I run Gemma 4 31B IT or QwQ 32B on a 16 GB GPU?
Gemma 4 31B IT fits at IQ3_XS; QwQ 32B fits at IQ2_M.
Which has a longer context window, Gemma 4 31B IT or QwQ 32B?
Gemma 4 31B IT supports 262,144 tokens and QwQ 32B supports 40,960 tokens.