Gemma 2 9B IT vs Qwen3.8 27B
Qwen3.8 27B leads llmrun Score 122.1 to 68.0; both fit 24 GB at Q4_K_M; Gemma 2 9B IT is 2.8× faster on RTX 4090 (~107 vs ~38 tok/s).
Model B · Alibaba
Qwen3.8 27B27.8B · 256K context · Apache 2.0 · Aug 2026
Choose Gemma 2 9B IT if you want…
Fits an 8 GB GPU
Q4_K_M · 7.3 GB; Qwen3.8 27B needs 8.8 GB at its smallest quant
2.8× faster on RTX 4090
~107 vs ~38 tok/s
Lighter on memory
6.1 vs 17.4 GB at Q4_K_M
Also does chat
Qwen3.8 27B doesn't list it
Choose Qwen3.8 27B if you want…
Higher llmrun Score
122.1 vs 68.0
Longer context window
256K vs 8K tokens
Also does vision, function-calling
Gemma 2 9B 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%.
8 GB
RTX 4060 · 8 GB tier
Gemma 2 9B IT
Q4_K_M · ~29 tok/s
7.3 GB · up to 8Kfits
Qwen3.8 27B
Doesn't fit
smallest quant needs 8.8 GB
12 GB
RTX 3060 12GB · 12 GB tier
Gemma 2 9B IT
Q4_K_M · ~38 tok/s
7.3 GB · up to 8Kmore headroom
Qwen3.8 27B
IQ3_XXS · ~20 tok/s
12 GB · up to 16K
16 GB
RTX 5060 Ti 16GB · 16 GB tier
Gemma 2 9B IT
Q4_K_M · ~48 tok/s
7.3 GB · up to 8Kmore headroom
Qwen3.8 27B
Q3_K_L · ~19 tok/s
15.4 GB · up to 16K
24 GBreference
RTX 4090 · 24 GB tier
Gemma 2 9B IT
Q4_K_M · ~107 tok/s
7.3 GB · up to 8Kfaster
Qwen3.8 27B
Q4_K_M · ~38 tok/s
17.9 GB · up to 64K
32 GB
RTX 5090 · 32 GB tier
Gemma 2 9B IT
Q4_K_M · ~191 tok/s
7.3 GB · up to 8Kfaster
Qwen3.8 27B
Q4_K_M · ~67 tok/s
17.9 GB · up to 256K
48 GB
RTX A6000 · 48 GB tier
Gemma 2 9B IT
Q4_K_M · ~82 tok/s
7.3 GB · up to 8Kfaster
Qwen3.8 27B
Q4_K_M · ~29 tok/s
17.9 GB · up to 256K
Mac 32 GB
Mac Mini M4 · Macs
Gemma 2 9B IT
Q4_K_M · ~14 tok/s
7.3 GB · up to 8Kfaster
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 9B IT
Q4_K_M · ~63 tok/s
7.3 GB · up to 8Kfaster
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 9B IT
Q4_K_M · ~63 tok/s
7.3 GB · up to 8Kfaster
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).
Overall
Gemma 2 9B IT
Qwen3.8 27B
Coding
Gemma 2 9B IT
no data
Qwen3.8 27B
Agents
Gemma 2 9B IT
no data
Qwen3.8 27B
Math
Gemma 2 9B IT
no data
Qwen3.8 27B
Science
Gemma 2 9B IT
no data
Qwen3.8 27B
Reasoning
Gemma 2 9B IT
no data
Qwen3.8 27B
Gemma 2 9B IT · #93 of 100 open models · #29 of 35 that fit 24 GB
Qwen3.8 27B · #11 of 100 open models · #1 of 35 that fit 24 GB
26 more boards (other shared and single-model boards)
Gemma 2 9B IT
1267.0#124/187 open
ArenaLMArena · Oct 2026
Qwen3.8 27B
1437.8#22/187 open
ArenaLMArena · Oct 2026
Only Gemma 2 9B IT (5)
- GPQA Diamond27.5%
- AIME 2024/20250.6%
- MMLU-Pro52.1%
- MATH Level 521.0%
- MMLU72.1%
Only Qwen3.8 27B (20)
- LiveBench Coding75.7
- LiveBench Reasoning80.0
- LMArena WebDev1593.2
- LiveBench Math86.2
- ARC-AGI-242.4%
- SciCode46.6%
- ARC-AGI87.5%
- APEX-Agents47.5%
- CritPt5.4%
- DTBench88.0%
- LiveBench 2026 Reasoning80.0
- LMCA41.4%
- LiveBench 2026 Browser32.0
- LiveBench 2026 Data Analysis76.6
- LiveBench 2026 Coding86.8
- LiveBench 2026 Long-Horizon27.9
- Surface Evolver Bench45.0%
- LiveBench 2026 Design75.9
- ProofBench16.0%
- LiveBench 2026 Research59.4
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 2 9B IT
4.3 GB3.8 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 9B IT
4.5 GB4.3 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 9B IT
5.0 GB4.8 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 9B IT
5.1 GB5.4 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 9B IT
6.1 GB5.8 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 9B IT
7.2 GB6.6 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 9B IT
8.4 GB7.6 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 9B IT
10.2 GB9.8 GB file
32K — · 128K —
Qwen3.8 27B
28.5 GB29.0 GB file
32K 29.9 GB · 128K 35.2 GB
19 more quants
IQ2_XXS
Gemma 2 9B IT
2.8 GB2.8 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 9B IT
3.1 GB3.1 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 9B IT
3.2 GB3.2 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 9B IT
3.4 GB3.4 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 9B IT
3.9 GB3.8 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 9B IT
4.2 GB4.1 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 9B IT
4.3 GB4.3 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 9B IT
4.6 GB4.5 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 9B IT
5.2 GB5.1 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 9B IT
5.5 GB5.2 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 9B IT
not listed
Qwen3.8 27B
16.4 GB17.4 GB file
32K 17.7 GB · 128K 23.1 GB
Q4_1
Gemma 2 9B IT
5.7 GB6.0 GB file
32K — · 128K —
Qwen3.8 27B
16.4 GB17.5 GB file
32K 17.7 GB · 128K 23.1 GB
Q4_K_S
Gemma 2 9B IT
5.7 GB5.5 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 9B IT
6.2 GB6.0 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 9B IT
6.4 GB6.5 GB file
32K — · 128K —
Qwen3.8 27B
not listed
Q5_1
Gemma 2 9B IT
7.0 GB7.0 GB file
32K — · 128K —
Qwen3.8 27B
not listed
Q5_K_S
Gemma 2 9B IT
7.0 GB6.5 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 9B IT
7.4 GB6.9 GB file
32K — · 128K —
Qwen3.8 27B
20.9 GB21.5 GB file
32K 22.2 GB · 128K 27.6 GB
BF16
Gemma 2 9B IT
20.3 GB~18.5 GB file
32K — · 128K —
Qwen3.8 27B
56.3 GB54.7 GB file
32K 57.7 GB · 128K 63.0 GB
Gemma 2 9B IT
Ollama · Q4_K_M
ollama run hf.co/bartowski/gemma-2-9b-it-GGUF:Q4_K_MQwen3.8 27B
Ollama · Q4_K_M
ollama run hf.co/unsloth/Qwen3.8-27B-GGUF:Q4_K_M| Spec | Gemma 2 9B IT | Qwen3.8 27B |
|---|---|---|
| Publisher | Alibaba | |
| Parameters | 9.2B | 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 9B IT or Qwen3.8 27B?
Qwen3.8 27B leads llmrun Score 122.1 to 68.0; both fit 24 GB at Q4_K_M; Gemma 2 9B IT is 2.8× faster on RTX 4090 (~107 vs ~38 tok/s). Choose Gemma 2 9B IT for fits an 8 GB GPU and 2.8× faster on RTX 4090; choose Qwen3.8 27B for higher llmrun Score and longer context window.
Which needs less VRAM, Gemma 2 9B IT or Qwen3.8 27B?
At Q4_K_M, Gemma 2 9B IT requires 6.1 GB while Qwen3.8 27B needs 17.4 GB, making Gemma 2 9B IT the easier model to run on your local setup.
Which is faster on RTX 4090?
Estimated decode speed on RTX 4090 is about 107 tok/s for Gemma 2 9B IT (Q4_K_M) and 38 tok/s for Qwen3.8 27B (Q4_K_M), so Gemma 2 9B IT is faster. Estimates, ±20%.
Can I run Gemma 2 9B IT or Qwen3.8 27B on a 16 GB GPU?
Gemma 2 9B IT fits at Q4_K_M; Qwen3.8 27B fits at Q3_K_L.
Which has a longer context window, Gemma 2 9B IT or Qwen3.8 27B?
Gemma 2 9B IT supports 8,192 tokens and Qwen3.8 27B supports 262,144 tokens.