Gemma 2 27B IT vs Qwen3.8 27B

Qwen3.8 27B leads llmrun Score 122.1 to 72.7; both fit 24 GB at Q4_K_M.

Model A · Google

Gemma 2 27B IT

72.7llmrun Score

27.2B · 8K context · Gemma Terms · Jun 2024

Chat

Model B · Alibaba

Qwen3.8 27B

122.1llmrun Score

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

VisionFunctions

Which should you choose?

Choose Gemma 2 27B IT if you want…

Also does chat
Qwen3.8 27B doesn't list it

Choose Qwen3.8 27B if you want…

Higher llmrun Score
122.1 vs 72.7
Fits a 12 GB GPU
IQ3_XXS · 12 GB; Gemma 2 27B IT needs 9.8 GB at its smallest quant
Longer context window
256K vs 8K tokens
Also does vision, function-calling
Gemma 2 27B IT doesn't list it
More permissive license
Apache 2.0 vs Gemma Terms
Newer release
Aug 2026 vs Jun 2024

On your hardware

Each model at its default quant (Q4_K_M), a smaller one when it must. Estimates, ±20%.

MemoryGemma 2 27B ITQwen3.8 27B

8 GB

RTX 4060 · 8 GB tier

Gemma 2 27B IT

Doesn't fit

smallest quant needs 9.8 GB

Qwen3.8 27B

Doesn't fit

smallest quant needs 8.8 GB

12 GB

RTX 3060 12GB · 12 GB tier

Gemma 2 27B IT

IQ2_M · ~23 tok/s

11.7 GB · up to 8K

Qwen3.8 27B

IQ3_XXS · ~20 tok/s

12 GB · up to 16Kbetter quant

16 GB

RTX 5060 Ti 16GB · 16 GB tier

Gemma 2 27B IT

IQ3_M · ~22 tok/s

15 GB · up to 8K

Qwen3.8 27B

Q3_K_L · ~19 tok/s

15.4 GB · up to 16K

24 GBreference

RTX 4090 · 24 GB tier

Gemma 2 27B IT

Q4_K_M · ~37 tok/s

19.5 GB · up to 8K

Qwen3.8 27B

Q4_K_M · ~38 tok/s

17.9 GB · up to 64K

32 GB

RTX 5090 · 32 GB tier

Gemma 2 27B IT

Q4_K_M · ~65 tok/s

19.5 GB · up to 8K

Qwen3.8 27B

Q4_K_M · ~67 tok/s

17.9 GB · up to 256K

48 GB

RTX A6000 · 48 GB tier

Gemma 2 27B IT

Q4_K_M · ~28 tok/s

19.5 GB · up to 8K

Qwen3.8 27B

Q4_K_M · ~29 tok/s

17.9 GB · up to 256K

Mac 32 GB

Mac Mini M4 · Macs

Gemma 2 27B IT

Q4_K_M · ~5 tok/s

19.5 GB · up to 8K

Qwen3.8 27B

Q4_K_M · ~5 tok/s

17.9 GB · up to 128K

Mac 64 GB

Mac Studio M4 Max · Macs

Gemma 2 27B IT

Q4_K_M · ~21 tok/s

19.5 GB · up to 8K

Qwen3.8 27B

Q4_K_M · ~22 tok/s

17.9 GB · up to 256K

Mac 128 GB

Mac Studio M4 Max · Macs

Gemma 2 27B IT

Q4_K_M · ~21 tok/s

19.5 GB · up to 8K

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 2 27B IT Qwen3.8 27B

Overall

Gemma 2 27B IT

72.766–79

Qwen3.8 27B

122.1120–124

Coding

Gemma 2 27B IT

no data

Qwen3.8 27B

119.7114–125

Agents

Gemma 2 27B IT

no data

Qwen3.8 27B

122.8117–129

Math

Gemma 2 27B IT

no data

Qwen3.8 27B

117.5111–124

Science

Gemma 2 27B IT

no data

Qwen3.8 27B

112.093–131

Reasoning

Gemma 2 27B IT

no data

Qwen3.8 27B

124.0121–127

Gemma 2 27B IT · #91 of 100 open models · #28 of 35 that fit 24 GB

Qwen3.8 27B · #11 of 100 open models · #1 of 35 that fit 24 GB

Benchmarks

The two models share no benchmark board.

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

LMArena Text

Gemma 2 27B IT

1289.5#112/187 open

ArenaLMArena · Oct 2026

Qwen3.8 27B

1437.8#22/187 open

ArenaLMArena · Oct 2026

Only Gemma 2 27B IT (5)

Only Qwen3.8 27B (20)

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 2 27B ITQwen3.8 27B

Q2_K

Gemma 2 27B IT

12.7 GB10.4 GB file

32K — · 128K —

Qwen3.8 27B

12.6 GB10.8 GB file

32K 13.9 GB · 128K 19.3 GB

Q3_K_S

Gemma 2 27B IT

13.1 GB12.2 GB file

32K — · 128K —

Qwen3.8 27B

12.9 GB12.7 GB file

32K 14.2 GB · 128K 19.6 GB

Q3_K_M

Gemma 2 27B IT

14.6 GB13.4 GB file

32K — · 128K —

Qwen3.8 27B

14.3 GB13.4 GB file

32K 15.6 GB · 128K 21.0 GB

Q4_0

Gemma 2 27B IT

15.0 GB15.7 GB file

32K — · 128K —

Qwen3.8 27B

14.6 GB~13.9 GB file

32K 16.0 GB · 128K 21.4 GB

Q4_K_M

Gemma 2 27B IT

18.0 GB16.6 GB file

32K — · 128K —

Qwen3.8 27B

17.4 GB16.5 GB file

32K 18.8 GB · 128K 24.1 GB

Q5_K_M

Gemma 2 27B IT

21.3 GB19.4 GB file

32K — · 128K —

Qwen3.8 27B

20.5 GB19.8 GB file

32K 21.9 GB · 128K 27.3 GB

Q6_K

Gemma 2 27B IT

24.7 GB22.3 GB file

32K — · 128K —

Qwen3.8 27B

23.7 GB22.0 GB file

32K 25.0 GB · 128K 30.4 GB

Q8_0

Gemma 2 27B IT

30.0 GB28.9 GB file

32K — · 128K —

Qwen3.8 27B

28.5 GB29.0 GB file

32K 29.9 GB · 128K 35.2 GB

18 more quants

IQ2_XXS

Gemma 2 27B IT

8.2 GB7.6 GB file

32K — · 128K —

Qwen3.8 27B

8.4 GB7.3 GB file

32K 9.7 GB · 128K 15.1 GB

IQ2_XS

Gemma 2 27B IT

9.0 GB8.4 GB file

32K — · 128K —

Qwen3.8 27B

9.1 GB9.1 GB file

32K 10.4 GB · 128K 15.8 GB

IQ2_S

Gemma 2 27B IT

9.4 GB8.7 GB file

32K — · 128K —

Qwen3.8 27B

9.4 GB8.4 GB file

32K 10.8 GB · 128K 16.1 GB

IQ2_M

Gemma 2 27B IT

10.1 GB9.4 GB file

32K — · 128K —

Qwen3.8 27B

10.1 GB10.5 GB file

32K 11.5 GB · 128K 16.8 GB

IQ3_XXS

Gemma 2 27B IT

11.6 GB10.8 GB file

32K — · 128K —

Qwen3.8 27B

11.5 GB10.9 GB file

32K 12.9 GB · 128K 18.2 GB

IQ3_XS

Gemma 2 27B IT

12.4 GB11.6 GB file

32K — · 128K —

Qwen3.8 27B

12.2 GB10.4 GB file

32K 13.6 GB · 128K 18.9 GB

IQ3_S

Gemma 2 27B IT

12.7 GB12.2 GB file

32K — · 128K —

Qwen3.8 27B

12.6 GB12.0 GB file

32K 13.9 GB · 128K 19.3 GB

IQ3_M

Gemma 2 27B IT

13.5 GB12.5 GB file

32K — · 128K —

Qwen3.8 27B

13.3 GB14.9 GB file

32K 14.6 GB · 128K 20.0 GB

Q3_K_L

Gemma 2 27B IT

15.4 GB14.5 GB file

32K — · 128K —

Qwen3.8 27B

15.0 GB14.1 GB file

32K 16.3 GB · 128K 21.7 GB

IQ4_XS

Gemma 2 27B IT

16.1 GB14.8 GB file

32K — · 128K —

Qwen3.8 27B

15.7 GB14.3 GB file

32K 17.0 GB · 128K 22.4 GB

IQ4_NL

Gemma 2 27B IT

not listed

Qwen3.8 27B

16.4 GB17.4 GB file

32K 17.7 GB · 128K 23.1 GB

Q4_1

Gemma 2 27B IT

not listed

Qwen3.8 27B

16.4 GB17.5 GB file

32K 17.7 GB · 128K 23.1 GB

Q4_K_S

Gemma 2 27B IT

16.9 GB15.7 GB file

32K — · 128K —

Qwen3.8 27B

16.4 GB15.4 GB file

32K 17.7 GB · 128K 23.1 GB

Q4_K_L

Gemma 2 27B IT

18.3 GB16.9 GB file

32K — · 128K —

Qwen3.8 27B

17.8 GB18.8 GB file

32K 19.1 GB · 128K 24.5 GB

Q5_0

Gemma 2 27B IT

18.7 GB18.9 GB file

32K — · 128K —

Qwen3.8 27B

not listed

Q5_K_S

Gemma 2 27B IT

20.6 GB18.9 GB file

32K — · 128K —

Qwen3.8 27B

19.9 GB18.7 GB file

32K 21.2 GB · 128K 26.6 GB

Q5_K_L

Gemma 2 27B IT

21.7 GB19.7 GB file

32K — · 128K —

Qwen3.8 27B

20.9 GB21.5 GB file

32K 22.2 GB · 128K 27.6 GB

BF16

Gemma 2 27B IT

59.9 GB~54.5 GB file

32K — · 128K —

Qwen3.8 27B

56.3 GB54.7 GB file

32K 57.7 GB · 128K 63.0 GB

How to run each

Gemma 2 27B IT

Ollama · Q4_K_M

$ollama run hf.co/bartowski/gemma-2-27b-it-GGUF:Q4_K_M

All ways to run Gemma 2 27B 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 2 27B IT and Qwen3.8 27B
Spec	Gemma 2 27B IT	Qwen3.8 27B
Publisher	Google	Alibaba
Parameters	27.2B	27.8B
Architecture	—	Qwen3_5ForConditionalGeneration
Context	8K tokens	256K tokens
Modalities	Chat	Vision, Function-calling
License	Gemma Terms	Apache 2.0
Released	Jun 2024	Aug 2026

Frequently Asked Questions

Which is better, Gemma 2 27B IT or Qwen3.8 27B?

Qwen3.8 27B leads llmrun Score 122.1 to 72.7; both fit 24 GB at Q4_K_M. Choose Gemma 2 27B IT for also does chat; choose Qwen3.8 27B for higher llmrun Score and fits a 12 GB GPU.

Which needs less VRAM, Gemma 2 27B IT or Qwen3.8 27B?

At Q4_K_M, Gemma 2 27B IT requires 18.0 GB while Qwen3.8 27B needs 17.4 GB, making Qwen3.8 27B the easier model to run on your local setup.

Which is faster on RTX 4090?

Estimated decode speed on RTX 4090 is about 37 tok/s for Gemma 2 27B IT (Q4_K_M) and 38 tok/s for Qwen3.8 27B (Q4_K_M), so Qwen3.8 27B is faster. Estimates, ±20%.

Can I run Gemma 2 27B IT or Qwen3.8 27B on a 16 GB GPU?

Gemma 2 27B IT fits at IQ3_M; Qwen3.8 27B fits at Q3_K_L.

Which has a longer context window, Gemma 2 27B IT or Qwen3.8 27B?

Gemma 2 27B IT supports 8,192 tokens and Qwen3.8 27B supports 262,144 tokens.