Gemma 3 4B IT vs Qwen3.8 27B
Qwen3.8 27B leads llmrun Score 121.5 to 64.0; both fit 24 GB at Q4_K_M; Gemma 3 4B IT is 6.1× faster on RTX 4090 (~231 vs ~38 tok/s).
Model B · Alibaba
Qwen3.8 27B27.8B · 256K context · Apache 2.0 · Aug 2026
Choose Gemma 3 4B IT if you want…
Fits an 8 GB GPU
Q4_K_M · 5 GB; Qwen3.8 27B needs 8.8 GB at its smallest quant
6.1× faster on RTX 4090
~231 vs ~38 tok/s
Lighter on memory
2.8 vs 17.4 GB at Q4_K_M
Choose Qwen3.8 27B if you want…
Higher llmrun Score
121.5 vs 64.0
Stronger at reasoning
124.1 vs 68.5
Ahead on the benchmarks
3 of 3 shared boards
Also does function-calling
Gemma 3 4B IT doesn't list it
More permissive license
Apache 2.0 vs Gemma Terms
Newer release
Aug 2026 vs Feb 2025
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 3 4B IT
Q4_K_M · ~62 tok/s
5 GB · up to 32Kfits
Qwen3.8 27B
Doesn't fit
smallest quant needs 8.8 GB
12 GB
RTX 3060 12GB · 12 GB tier
Gemma 3 4B IT
Q4_K_M · ~82 tok/s
5 GB · up to 32Kmore 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 4B IT
Q4_K_M · ~103 tok/s
5 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 4B IT
Q4_K_M · ~231 tok/s
5 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 4B IT
Q4_K_M · ~410 tok/s
5 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 4B IT
Q4_K_M · ~176 tok/s
5 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 4B IT
Q4_K_M · ~30 tok/s
5 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 4B IT
Q4_K_M · ~135 tok/s
5 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 4B IT
Q4_K_M · ~135 tok/s
5 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).
Overall
Gemma 3 4B IT
Qwen3.8 27B
Coding
Gemma 3 4B IT
no data
Qwen3.8 27B
Math
Gemma 3 4B IT
no data
Qwen3.8 27B
Science
Gemma 3 4B IT
no data
Qwen3.8 27B
Reasoning
Gemma 3 4B IT
Qwen3.8 27B
Gemma 3 4B IT · #87 of 92 open models · #30 of 34 that fit 24 GB
Qwen3.8 27B · #10 of 92 open models · #1 of 34 that fit 24 GB
Benchmarks
3 shared boards: Gemma 3 4B IT leads 0, Qwen3.8 27B leads 3 · Benchmarks imported Oct 2026
Gemma 3 4B IT
1303.3#104/186 open
ArenaLMArena · Oct 2026
Qwen3.8 27B
1438.1#22/186 open
ArenaLMArena · Oct 2026
Gemma 3 4B IT
50.9%#58/68 open
Lab-reportedEpoch AI · Mar 2025
Qwen3.8 27B
88.0%#9/68 open
Lab-reportedEpoch AI · Aug 2026
Gemma 3 4B IT
2.8%#54/54 open
Lab-reportedEpoch AI · Mar 2025
Qwen3.8 27B
41.4%#7/54 open
Lab-reportedEpoch AI · Aug 2026
15 more boards (other shared and single-model boards)
Only Gemma 3 4B IT (4)
- GPQA Diamond23.2%
- AIME 2024/20257.5%
- MMLU-Pro43.6%
- Chess Puzzles0.0%
Only Qwen3.8 27B (11)
- LiveBench Coding75.7
- LiveBench Reasoning80.0
- LMArena WebDev1592.8
- LiveBench Math86.2
- ARC-AGI-242.4%
- SciCode46.6%
- ARC-AGI87.5%
- CritPt5.4%
- APEX-Agents47.5%
- Surface Evolver Bench45.0%
- ProofBench16.0%
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 3 4B IT
2.0 GB1.7 GB file
32K 6.6 GB · 128K 21.4 GB
Qwen3.8 27B
12.6 GB10.8 GB file
32K 13.9 GB · 128K 19.3 GB
Q3_K_S
Gemma 3 4B IT
2.1 GB1.9 GB file
32K 6.7 GB · 128K 21.5 GB
Qwen3.8 27B
12.9 GB12.7 GB file
32K 14.2 GB · 128K 19.6 GB
Q3_K_M
Gemma 3 4B IT
2.3 GB2.1 GB file
32K 6.9 GB · 128K 21.7 GB
Qwen3.8 27B
14.3 GB13.4 GB file
32K 15.6 GB · 128K 21.0 GB
Q4_0
Gemma 3 4B IT
2.4 GB2.4 GB file
32K 7.0 GB · 128K 21.8 GB
Qwen3.8 27B
14.6 GB~13.9 GB file
32K 16.0 GB · 128K 21.4 GB
Q4_K_M
Gemma 3 4B IT
2.8 GB2.5 GB file
32K 7.5 GB · 128K 22.3 GB
Qwen3.8 27B
17.4 GB16.5 GB file
32K 18.8 GB · 128K 24.1 GB
Q5_K_M
Gemma 3 4B IT
3.4 GB2.8 GB file
32K 8.0 GB · 128K 22.8 GB
Qwen3.8 27B
20.5 GB19.8 GB file
32K 21.9 GB · 128K 27.3 GB
Q6_K
Gemma 3 4B IT
3.9 GB3.2 GB file
32K 8.5 GB · 128K 23.3 GB
Qwen3.8 27B
23.7 GB22.0 GB file
32K 25.0 GB · 128K 30.4 GB
Q8_0
Gemma 3 4B IT
4.7 GB4.1 GB file
32K 9.4 GB · 128K 24.1 GB
Qwen3.8 27B
28.5 GB29.0 GB file
32K 29.9 GB · 128K 35.2 GB
19 more quants
IQ2_XXS
Gemma 3 4B IT
1.3 GB1.3 GB file
32K 5.9 GB · 128K 20.7 GB
Qwen3.8 27B
8.4 GB7.3 GB file
32K 9.7 GB · 128K 15.1 GB
IQ2_XS
Gemma 3 4B IT
1.4 GB1.4 GB file
32K 6.0 GB · 128K 20.8 GB
Qwen3.8 27B
9.1 GB9.1 GB file
32K 10.4 GB · 128K 15.8 GB
IQ2_S
Gemma 3 4B IT
1.5 GB1.4 GB file
32K 6.1 GB · 128K 20.9 GB
Qwen3.8 27B
9.4 GB8.4 GB file
32K 10.8 GB · 128K 16.1 GB
IQ2_M
Gemma 3 4B IT
1.6 GB1.6 GB file
32K 6.2 GB · 128K 21.0 GB
Qwen3.8 27B
10.1 GB10.5 GB file
32K 11.5 GB · 128K 16.8 GB
IQ3_XXS
Gemma 3 4B IT
1.8 GB1.7 GB file
32K 6.5 GB · 128K 21.2 GB
Qwen3.8 27B
11.5 GB10.9 GB file
32K 12.9 GB · 128K 18.2 GB
Q2_K_S
Gemma 3 4B IT
1.9 GB1.6 GB file
32K 6.5 GB · 128K 21.3 GB
Qwen3.8 27B
not listed
IQ3_XS
Gemma 3 4B IT
2.0 GB1.9 GB file
32K 6.6 GB · 128K 21.4 GB
Qwen3.8 27B
12.2 GB10.4 GB file
32K 13.6 GB · 128K 18.9 GB
IQ3_S
Gemma 3 4B IT
2.0 GB1.9 GB file
32K 6.6 GB · 128K 21.4 GB
Qwen3.8 27B
12.6 GB12.0 GB file
32K 13.9 GB · 128K 19.3 GB
IQ3_M
Gemma 3 4B IT
2.1 GB2.0 GB file
32K 6.8 GB · 128K 21.5 GB
Qwen3.8 27B
13.3 GB14.9 GB file
32K 14.6 GB · 128K 20.0 GB
Q3_K_L
Gemma 3 4B IT
2.4 GB2.2 GB file
32K 7.0 GB · 128K 21.8 GB
Qwen3.8 27B
15.0 GB14.1 GB file
32K 16.3 GB · 128K 21.7 GB
IQ4_XS
Gemma 3 4B IT
2.5 GB2.3 GB file
32K 7.2 GB · 128K 22.0 GB
Qwen3.8 27B
15.7 GB14.3 GB file
32K 17.0 GB · 128K 22.4 GB
IQ4_NL
Gemma 3 4B IT
2.7 GB2.4 GB file
32K 7.3 GB · 128K 22.1 GB
Qwen3.8 27B
16.4 GB17.4 GB file
32K 17.7 GB · 128K 23.1 GB
Q4_1
Gemma 3 4B IT
2.7 GB2.6 GB file
32K 7.3 GB · 128K 22.1 GB
Qwen3.8 27B
16.4 GB17.5 GB file
32K 17.7 GB · 128K 23.1 GB
Q4_K_S
Gemma 3 4B IT
2.7 GB2.4 GB file
32K 7.3 GB · 128K 22.1 GB
Qwen3.8 27B
16.4 GB15.4 GB file
32K 17.7 GB · 128K 23.1 GB
Q4_K_L
Gemma 3 4B IT
2.9 GB2.7 GB file
32K 7.5 GB · 128K 22.3 GB
Qwen3.8 27B
17.8 GB18.8 GB file
32K 19.1 GB · 128K 24.5 GB
Q5_0
Gemma 3 4B IT
3.0 GB2.8 GB file
32K 7.6 GB · 128K 22.4 GB
Qwen3.8 27B
not listed
Q5_K_S
Gemma 3 4B IT
3.3 GB2.8 GB file
32K 7.9 GB · 128K 22.7 GB
Qwen3.8 27B
19.9 GB18.7 GB file
32K 21.2 GB · 128K 26.6 GB
Q5_K_L
Gemma 3 4B IT
3.4 GB3.0 GB file
32K 8.1 GB · 128K 22.8 GB
Qwen3.8 27B
20.9 GB21.5 GB file
32K 22.2 GB · 128K 27.6 GB
BF16
Gemma 3 4B IT
9.5 GB7.8 GB file
32K 14.1 GB · 128K 28.9 GB
Qwen3.8 27B
56.3 GB54.7 GB file
32K 57.7 GB · 128K 63.0 GB
Gemma 3 4B IT
Ollama · Q4_K_M
ollama run hf.co/MaziyarPanahi/gemma-3-4b-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 3 4B IT | Qwen3.8 27B |
|---|---|---|
| Publisher | Alibaba | |
| Parameters | 4.3B | 27.8B |
| Architecture | — | Qwen3_5ForConditionalGeneration |
| Context | — | 256K tokens |
| Modalities | Vision | Vision, Function-calling |
| License | Gemma Terms | Apache 2.0 |
| Released | Feb 2025 | Aug 2026 |
Frequently Asked Questions
Which is better, Gemma 3 4B IT or Qwen3.8 27B?
Qwen3.8 27B leads llmrun Score 121.5 to 64.0; both fit 24 GB at Q4_K_M; Gemma 3 4B IT is 6.1× faster on RTX 4090 (~231 vs ~38 tok/s). Choose Gemma 3 4B IT for fits an 8 GB GPU and 6.1× faster on RTX 4090; choose Qwen3.8 27B for higher llmrun Score and stronger at reasoning.
Which needs less VRAM, Gemma 3 4B IT or Qwen3.8 27B?
At Q4_K_M, Gemma 3 4B IT requires 2.8 GB while Qwen3.8 27B needs 17.4 GB, making Gemma 3 4B IT the easier model to run on your local setup.
Which is faster on RTX 4090?
Estimated decode speed on RTX 4090 is about 231 tok/s for Gemma 3 4B IT (Q4_K_M) and 38 tok/s for Qwen3.8 27B (Q4_K_M), so Gemma 3 4B IT is faster. Estimates, ±20%.
Can I run Gemma 3 4B IT or Qwen3.8 27B on a 16 GB GPU?
Gemma 3 4B IT fits at Q4_K_M; Qwen3.8 27B fits at Q3_K_L.