Gemma 3 12B IT vs Qwen3.8 27B

Qwen3.8 27B leads llmrun Score 121.5 to 74.2; both fit 24 GB at Q4_K_M; Gemma 3 12B IT is 2.2× faster on RTX 4090 (~82 vs ~38 tok/s).

Model A · Google

Gemma 3 12B IT

74.2llmrun Score

12.2B · 32K context · Gemma Terms · Mar 2025

Vision

Model B · Alibaba

Qwen3.8 27B

121.5llmrun Score

27.8B · 256K context · Apache 2.0 · Aug 2026

VisionFunctions

Which should you choose?

Choose Gemma 3 12B IT if you want…

2.2× faster on RTX 4090
~82 vs ~38 tok/s
Lighter on memory
8.0 vs 17.4 GB at Q4_K_M

Choose Qwen3.8 27B if you want…

Higher llmrun Score
121.5 vs 74.2
Stronger at reasoning
124.1 vs 66.0
Stronger at science
112.0 vs 71.7
Ahead on the benchmarks
5 of 5 shared boards
Longer context window
256K vs 32K tokens
Also does function-calling
Gemma 3 12B 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%.

MemoryGemma 3 12B ITQwen3.8 27B

8 GB

RTX 4060 · 8 GB tier

Gemma 3 12B IT

IQ2_M · ~39 tok/s

7.4 GB · up to 16Kfits

Qwen3.8 27B

Doesn't fit

smallest quant needs 8.8 GB

12 GB

RTX 3060 12GB · 12 GB tier

Gemma 3 12B IT

Q4_K_M · ~29 tok/s

10.9 GB · up to 16Kmore headroom

Qwen3.8 27B

IQ3_XXS · ~20 tok/s

12 GB · up to 16K

16 GB

RTX 5060 Ti 16GB · 16 GB tier

Gemma 3 12B IT

Q4_K_M · ~36 tok/s

10.9 GB · up to 32Kmore headroom

Qwen3.8 27B

Q3_K_L · ~19 tok/s

15.4 GB · up to 16K

24 GBreference

RTX 4090 · 24 GB tier

Gemma 3 12B IT

Q4_K_M · ~82 tok/s

10.9 GB · up to 32Kfaster

Qwen3.8 27B

Q4_K_M · ~38 tok/s

17.9 GB · up to 64K

32 GB

RTX 5090 · 32 GB tier

Gemma 3 12B IT

Q4_K_M · ~145 tok/s

10.9 GB · up to 32Kfaster

Qwen3.8 27B

Q4_K_M · ~67 tok/s

17.9 GB · up to 256K

48 GB

RTX A6000 · 48 GB tier

Gemma 3 12B IT

Q4_K_M · ~62 tok/s

10.9 GB · up to 32Kfaster

Qwen3.8 27B

Q4_K_M · ~29 tok/s

17.9 GB · up to 256K

Mac 32 GB

Mac Mini M4 · Macs

Gemma 3 12B IT

Q4_K_M · ~10 tok/s

10.9 GB · up to 32Kfaster

Qwen3.8 27B

Q4_K_M · ~5 tok/s

17.9 GB · up to 128K

Mac 64 GB

Mac Studio M4 Max · Macs

Gemma 3 12B IT

Q4_K_M · ~48 tok/s

10.9 GB · up to 32Kfaster

Qwen3.8 27B

Q4_K_M · ~22 tok/s

17.9 GB · up to 256K

Mac 128 GB

Mac Studio M4 Max · Macs

Gemma 3 12B IT

Q4_K_M · ~48 tok/s

10.9 GB · up to 32Kfaster

Qwen3.8 27B

Q4_K_M · ~22 tok/s

17.9 GB · up to 256K

Reference GPU: RTX 4090. Tinted cell = the better pick on that machine (fits, more headroom, or at least 10% faster).

llmrun Score

with its 90% range · bars share one scale

Gemma 3 12B IT Qwen3.8 27B

Overall

Gemma 3 12B IT

74.269–80

Qwen3.8 27B

121.5119–124

Coding

Gemma 3 12B IT

no data

Qwen3.8 27B

112.1105–119

Math

Gemma 3 12B IT

no data

Qwen3.8 27B

117.5111–125

Science

Gemma 3 12B IT

71.761–83

Qwen3.8 27B

112.093–131

Reasoning

Gemma 3 12B IT

66.052–80

Qwen3.8 27B

124.1121–127

Gemma 3 12B IT · #82 of 92 open models · #26 of 34 that fit 24 GB

Qwen3.8 27B · #10 of 92 open models · #1 of 34 that fit 24 GB

Benchmarks

5 shared boards: Gemma 3 12B IT leads 0, Qwen3.8 27B leads 5 · Benchmarks imported Oct 2026

BoardGemma 3 12B ITQwen3.8 27B

LMArena Text

Gemma 3 12B IT

1341.8#82/186 open

ArenaLMArena · Oct 2026

Qwen3.8 27B

1438.1#22/186 open

ArenaLMArena · Oct 2026

SciCode

Gemma 3 12B IT

17.4%#62/65 open

Lab-reportedEpoch AI · Mar 2025

Qwen3.8 27B

46.6%#19/65 open

Lab-reportedEpoch AI · Aug 2026

CritPt

Gemma 3 12B IT

0.0%#48/65 open

Lab-reportedEpoch AI · Mar 2025

Qwen3.8 27B

5.4%#15/65 open

Lab-reportedEpoch AI · Aug 2026

DTBench

Gemma 3 12B IT

48.8%#62/68 open

Lab-reportedEpoch AI · Mar 2025

Qwen3.8 27B

88.0%#9/68 open

Lab-reportedEpoch AI · Aug 2026

LMCA

Gemma 3 12B IT

4.5%#53/54 open

Lab-reportedEpoch AI · Mar 2025

Qwen3.8 27B

41.4%#7/54 open

Lab-reportedEpoch AI · Aug 2026

13 more boards (other shared and single-model boards)

Only Gemma 3 12B IT (4)

Only Qwen3.8 27B (9)

VRAM by quantization

Memory to load the model and 2K context; below it, the total at 32K and 128K context. Lighter side in bold.

QuantGemma 3 12B ITQwen3.8 27B

Q2_K

Gemma 3 12B IT

5.7 GB4.8 GB file

32K 11.9 GB · 128K —

Qwen3.8 27B

12.6 GB10.8 GB file

32K 13.9 GB · 128K 19.3 GB

Q3_K_S

Gemma 3 12B IT

5.9 GB5.5 GB file

32K 12.1 GB · 128K —

Qwen3.8 27B

12.9 GB12.7 GB file

32K 14.2 GB · 128K 19.6 GB

Q3_K_M

Gemma 3 12B IT

6.5 GB6.0 GB file

32K 12.7 GB · 128K —

Qwen3.8 27B

14.3 GB13.4 GB file

32K 15.6 GB · 128K 21.0 GB

Q4_0

Gemma 3 12B IT

6.7 GB6.9 GB file

32K 12.9 GB · 128K —

Qwen3.8 27B

14.6 GB~13.9 GB file

32K 16.0 GB · 128K 21.4 GB

Q4_K_M

Gemma 3 12B IT

8.0 GB7.3 GB file

32K 14.2 GB · 128K —

Qwen3.8 27B

17.4 GB16.5 GB file

32K 18.8 GB · 128K 24.1 GB

Q5_K_M

Gemma 3 12B IT

9.6 GB8.4 GB file

32K 15.7 GB · 128K —

Qwen3.8 27B

20.5 GB19.8 GB file

32K 21.9 GB · 128K 27.3 GB

Q6_K

Gemma 3 12B IT

11.1 GB9.7 GB file

32K 17.3 GB · 128K —

Qwen3.8 27B

23.7 GB22.0 GB file

32K 25.0 GB · 128K 30.4 GB

Q8_0

Gemma 3 12B IT

13.4 GB12.5 GB file

32K 19.6 GB · 128K —

Qwen3.8 27B

28.5 GB29.0 GB file

32K 29.9 GB · 128K 35.2 GB

19 more quants

IQ2_XXS

Gemma 3 12B IT

3.7 GB3.6 GB file

32K 9.9 GB · 128K —

Qwen3.8 27B

8.4 GB7.3 GB file

32K 9.7 GB · 128K 15.1 GB

IQ2_XS

Gemma 3 12B IT

4.0 GB3.8 GB file

32K 10.2 GB · 128K —

Qwen3.8 27B

9.1 GB9.1 GB file

32K 10.4 GB · 128K 15.8 GB

IQ2_S

Gemma 3 12B IT

4.2 GB4.0 GB file

32K 10.4 GB · 128K —

Qwen3.8 27B

9.4 GB8.4 GB file

32K 10.8 GB · 128K 16.1 GB

IQ2_M

Gemma 3 12B IT

4.5 GB4.4 GB file

32K 10.7 GB · 128K —

Qwen3.8 27B

10.1 GB10.5 GB file

32K 11.5 GB · 128K 16.8 GB

IQ3_XXS

Gemma 3 12B IT

5.2 GB4.8 GB file

32K 11.4 GB · 128K —

Qwen3.8 27B

11.5 GB10.9 GB file

32K 12.9 GB · 128K 18.2 GB

Q2_K_S

Gemma 3 12B IT

5.4 GB4.4 GB file

32K 11.6 GB · 128K —

Qwen3.8 27B

not listed

IQ3_XS

Gemma 3 12B IT

5.5 GB5.2 GB file

32K 11.7 GB · 128K —

Qwen3.8 27B

12.2 GB10.4 GB file

32K 13.6 GB · 128K 18.9 GB

IQ3_S

Gemma 3 12B IT

5.7 GB5.5 GB file

32K 11.9 GB · 128K —

Qwen3.8 27B

12.6 GB12.0 GB file

32K 13.9 GB · 128K 19.3 GB

IQ3_M

Gemma 3 12B IT

6.0 GB5.7 GB file

32K 12.2 GB · 128K —

Qwen3.8 27B

13.3 GB14.9 GB file

32K 14.6 GB · 128K 20.0 GB

Q3_K_L

Gemma 3 12B IT

6.9 GB6.5 GB file

32K 13.1 GB · 128K —

Qwen3.8 27B

15.0 GB14.1 GB file

32K 16.3 GB · 128K 21.7 GB

IQ4_XS

Gemma 3 12B IT

7.2 GB6.6 GB file

32K 13.4 GB · 128K —

Qwen3.8 27B

15.7 GB14.3 GB file

32K 17.0 GB · 128K 22.4 GB

IQ4_NL

Gemma 3 12B IT

7.5 GB6.9 GB file

32K 13.7 GB · 128K —

Qwen3.8 27B

16.4 GB17.4 GB file

32K 17.7 GB · 128K 23.1 GB

Q4_1

Gemma 3 12B IT

7.5 GB7.6 GB file

32K 13.7 GB · 128K —

Qwen3.8 27B

16.4 GB17.5 GB file

32K 17.7 GB · 128K 23.1 GB

Q4_K_S

Gemma 3 12B IT

7.5 GB6.9 GB file

32K 13.7 GB · 128K —

Qwen3.8 27B

16.4 GB15.4 GB file

32K 17.7 GB · 128K 23.1 GB

Q4_K_L

Gemma 3 12B IT

8.2 GB7.5 GB file

32K 14.4 GB · 128K —

Qwen3.8 27B

17.8 GB18.8 GB file

32K 19.1 GB · 128K 24.5 GB

Q5_0

Gemma 3 12B IT

8.4 GB8.2 GB file

32K 14.6 GB · 128K —

Qwen3.8 27B

not listed

Q5_K_S

Gemma 3 12B IT

9.2 GB8.2 GB file

32K 15.4 GB · 128K —

Qwen3.8 27B

19.9 GB18.7 GB file

32K 21.2 GB · 128K 26.6 GB

Q5_K_L

Gemma 3 12B IT

9.7 GB8.7 GB file

32K 15.9 GB · 128K —

Qwen3.8 27B

20.9 GB21.5 GB file

32K 22.2 GB · 128K 27.6 GB

BF16

Gemma 3 12B IT

26.8 GB23.5 GB file

32K 33.0 GB · 128K —

Qwen3.8 27B

56.3 GB54.7 GB file

32K 57.7 GB · 128K 63.0 GB

How to run each

Gemma 3 12B IT

Ollama · Q4_K_M

$ollama run hf.co/MaziyarPanahi/gemma-3-12b-it-GGUF:Q4_K_M

All ways to run Gemma 3 12B IT →

Qwen3.8 27B

Ollama · Q4_K_M

$ollama run hf.co/unsloth/Qwen3.8-27B-GGUF:Q4_K_M

All ways to run Qwen3.8 27B →

Specifications

Specifications of Gemma 3 12B IT and Qwen3.8 27B
Spec	Gemma 3 12B IT	Qwen3.8 27B
Publisher	Google	Alibaba
Parameters	12.2B	27.8B
Architecture	—	Qwen3_5ForConditionalGeneration
Context	32K tokens	256K tokens
Modalities	Vision	Vision, Function-calling
License	Gemma Terms	Apache 2.0
Released	Mar 2025	Aug 2026

Frequently Asked Questions

Which is better, Gemma 3 12B IT or Qwen3.8 27B?

Qwen3.8 27B leads llmrun Score 121.5 to 74.2; both fit 24 GB at Q4_K_M; Gemma 3 12B IT is 2.2× faster on RTX 4090 (~82 vs ~38 tok/s). Choose Gemma 3 12B IT for 2.2× faster on RTX 4090 and lighter on memory; choose Qwen3.8 27B for higher llmrun Score and stronger at reasoning.

Which needs less VRAM, Gemma 3 12B IT or Qwen3.8 27B?

At Q4_K_M, Gemma 3 12B IT requires 8.0 GB while Qwen3.8 27B needs 17.4 GB, making Gemma 3 12B IT the easier model to run on your local setup.

Which is faster on RTX 4090?

Estimated decode speed on RTX 4090 is about 82 tok/s for Gemma 3 12B IT (Q4_K_M) and 38 tok/s for Qwen3.8 27B (Q4_K_M), so Gemma 3 12B IT is faster. Estimates, ±20%.

Can I run Gemma 3 12B IT or Qwen3.8 27B on a 16 GB GPU?

Gemma 3 12B IT fits at Q4_K_M; Qwen3.8 27B fits at Q3_K_L.

Which has a longer context window, Gemma 3 12B IT or Qwen3.8 27B?

Gemma 3 12B IT supports 32,768 tokens and Qwen3.8 27B supports 262,144 tokens.