Qwen3.8 27B vs Qwen3 8B
Qwen3.8 27B leads llmrun Score 121.5 to 93.8; both fit 24 GB at Q4_K_M; Qwen3 8B is 3.1× faster on RTX 4090 (~119 vs ~38 tok/s).
Model A · Alibaba
Qwen3.8 27B27.8B · 256K context · Apache 2.0 · Aug 2026
Choose Qwen3.8 27B if you want…
Higher llmrun Score
121.5 vs 93.8
Stronger at reasoning
124.1 vs 81.1
Stronger at science
112.0 vs 87.7
Ahead on the benchmarks
4 of 4 shared boards
Longer context window
256K vs 40K tokens
Also does vision
Qwen3 8B doesn't list it
Choose Qwen3 8B if you want…
Fits an 8 GB GPU
Q4_K_M · 7.6 GB; Qwen3.8 27B needs 8.8 GB at its smallest quant
3.1× faster on RTX 4090
~119 vs ~38 tok/s
Lighter on memory
5.5 vs 17.4 GB at Q4_K_M
Also does chat
Qwen3.8 27B 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
Qwen3.8 27B
Doesn't fit
smallest quant needs 8.8 GB
Qwen3 8B
Q4_K_M · ~32 tok/s
7.6 GB · up to 16Kfits
12 GB
RTX 3060 12GB · 12 GB tier
Qwen3.8 27B
IQ3_XXS · ~20 tok/s
12 GB · up to 16K
Qwen3 8B
Q4_K_M · ~42 tok/s
7.6 GB · up to 40Kmore headroom
16 GB
RTX 5060 Ti 16GB · 16 GB tier
Qwen3.8 27B
Q3_K_L · ~19 tok/s
15.4 GB · up to 16K
Qwen3 8B
Q4_K_M · ~53 tok/s
7.6 GB · up to 40Kmore headroom
24 GBreference
RTX 4090 · 24 GB tier
Qwen3.8 27B
Q4_K_M · ~38 tok/s
17.9 GB · up to 64K
Qwen3 8B
Q4_K_M · ~119 tok/s
7.6 GB · up to 40Kfaster
32 GB
RTX 5090 · 32 GB tier
Qwen3.8 27B
Q4_K_M · ~67 tok/s
17.9 GB · up to 256K
Qwen3 8B
Q4_K_M · ~211 tok/s
7.6 GB · up to 40Kfaster
48 GB
RTX A6000 · 48 GB tier
Qwen3.8 27B
Q4_K_M · ~29 tok/s
17.9 GB · up to 256K
Qwen3 8B
Q4_K_M · ~90 tok/s
7.6 GB · up to 40Kfaster
Mac 32 GB
Mac Mini M4 · Macs
Qwen3.8 27B
Q4_K_M · ~5 tok/s
17.9 GB · up to 128K
Qwen3 8B
Q4_K_M · ~15 tok/s
7.6 GB · up to 40Kfaster
Mac 64 GB
Mac Studio M4 Max · Macs
Qwen3.8 27B
Q4_K_M · ~22 tok/s
17.9 GB · up to 256K
Qwen3 8B
Q4_K_M · ~69 tok/s
7.6 GB · up to 40Kfaster
Mac 128 GB
Mac Studio M4 Max · Macs
Qwen3.8 27B
Q4_K_M · ~22 tok/s
17.9 GB · up to 256K
Qwen3 8B
Q4_K_M · ~69 tok/s
7.6 GB · up to 40Kfaster
Reference GPU: RTX 4090. Tinted cell = the better pick on that machine (fits, more headroom, or at least 10% faster).
Overall
Qwen3.8 27B
Qwen3 8B
Coding
Qwen3.8 27B
Qwen3 8B
no data
Math
Qwen3.8 27B
Qwen3 8B
no data
Science
Qwen3.8 27B
Qwen3 8B
Reasoning
Qwen3.8 27B
Qwen3 8B
Qwen3.8 27B · #10 of 92 open models · #1 of 34 that fit 24 GB
Qwen3 8B · #62 of 92 open models · #18 of 34 that fit 24 GB
Qwen3.8 27B
46.6%#19/65 open
Lab-reportedEpoch AI · Aug 2026
Qwen3 8B
22.6%#60/65 open
Lab-reportedEpoch AI · Apr 2025
Qwen3.8 27B
5.4%#15/65 open
Lab-reportedEpoch AI · Aug 2026
Qwen3 8B
0.0%#63/65 open
Lab-reportedEpoch AI · Apr 2025
Qwen3.8 27B
88.0%#9/68 open
Lab-reportedEpoch AI · Aug 2026
Qwen3 8B
59.7%#50/68 open
Lab-reportedEpoch AI · Apr 2025
Qwen3.8 27B
41.4%#7/54 open
Lab-reportedEpoch AI · Aug 2026
Qwen3 8B
8.8%#49/54 open
Lab-reportedEpoch AI · Apr 2025
14 more boards (other shared and single-model boards)
Only Qwen3.8 27B (10)
- LMArena Text1438.1
- LiveBench Coding75.7
- LiveBench Reasoning80.0
- LMArena WebDev1592.8
- LiveBench Math86.2
- ARC-AGI-242.4%
- ARC-AGI87.5%
- APEX-Agents47.5%
- Surface Evolver Bench45.0%
- ProofBench16.0%
Only Qwen3 8B (4)
- GPQA Diamond56.8%
- AIME 2024/202556.1%
- Chess Puzzles5.0%
- Fiction.LiveBench62.1%
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
Qwen3.8 27B
12.6 GB10.8 GB file
32K 13.9 GB · 128K 19.3 GB
Qwen3 8B
4.1 GB3.3 GB file
32K 8.6 GB · 128K —
Q3_K_S
Qwen3.8 27B
12.9 GB12.7 GB file
32K 14.2 GB · 128K 19.6 GB
Qwen3 8B
4.2 GB3.8 GB file
32K 8.7 GB · 128K —
Q3_K_M
Qwen3.8 27B
14.3 GB13.4 GB file
32K 15.6 GB · 128K 21.0 GB
Qwen3 8B
4.6 GB4.1 GB file
32K 9.1 GB · 128K —
Q4_0
Qwen3.8 27B
14.6 GB~13.9 GB file
32K 16.0 GB · 128K 21.4 GB
Qwen3 8B
4.7 GB4.8 GB file
32K 9.2 GB · 128K —
Q4_K_M
Qwen3.8 27B
17.4 GB16.5 GB file
32K 18.8 GB · 128K 24.1 GB
Qwen3 8B
5.5 GB5.0 GB file
32K 10.1 GB · 128K —
Q5_K_M
Qwen3.8 27B
20.5 GB19.8 GB file
32K 21.9 GB · 128K 27.3 GB
Qwen3 8B
6.4 GB5.9 GB file
32K 11.0 GB · 128K —
Q6_K
Qwen3.8 27B
23.7 GB22.0 GB file
32K 25.0 GB · 128K 30.4 GB
Qwen3 8B
7.4 GB6.7 GB file
32K 11.9 GB · 128K —
Q8_0
Qwen3.8 27B
28.5 GB29.0 GB file
32K 29.9 GB · 128K 35.2 GB
Qwen3 8B
8.8 GB8.7 GB file
32K 13.3 GB · 128K —
19 more quants
IQ2_XXS
Qwen3.8 27B
8.4 GB7.3 GB file
32K 9.7 GB · 128K 15.1 GB
Qwen3 8B
2.9 GB2.6 GB file
32K 7.4 GB · 128K —
IQ2_XS
Qwen3.8 27B
9.1 GB9.1 GB file
32K 10.4 GB · 128K 15.8 GB
Qwen3 8B
3.1 GB2.7 GB file
32K 7.6 GB · 128K —
IQ2_S
Qwen3.8 27B
9.4 GB8.4 GB file
32K 10.8 GB · 128K 16.1 GB
Qwen3 8B
3.2 GB2.9 GB file
32K 7.7 GB · 128K —
IQ2_M
Qwen3.8 27B
10.1 GB10.5 GB file
32K 11.5 GB · 128K 16.8 GB
Qwen3 8B
3.4 GB3.1 GB file
32K 7.9 GB · 128K —
IQ3_XXS
Qwen3.8 27B
11.5 GB10.9 GB file
32K 12.9 GB · 128K 18.2 GB
Qwen3 8B
3.8 GB3.4 GB file
32K 8.3 GB · 128K —
Q2_K_S
Qwen3.8 27B
not listed
Qwen3 8B
3.9 GB3.1 GB file
32K 8.4 GB · 128K —
IQ3_XS
Qwen3.8 27B
12.2 GB10.4 GB file
32K 13.6 GB · 128K 18.9 GB
Qwen3 8B
4.0 GB3.6 GB file
32K 8.5 GB · 128K —
IQ3_S
Qwen3.8 27B
12.6 GB12.0 GB file
32K 13.9 GB · 128K 19.3 GB
Qwen3 8B
4.1 GB3.8 GB file
32K 8.6 GB · 128K —
IQ3_M
Qwen3.8 27B
13.3 GB14.9 GB file
32K 14.6 GB · 128K 20.0 GB
Qwen3 8B
4.3 GB3.9 GB file
32K 8.8 GB · 128K —
Q3_K_L
Qwen3.8 27B
15.0 GB14.1 GB file
32K 16.3 GB · 128K 21.7 GB
Qwen3 8B
4.8 GB4.4 GB file
32K 9.3 GB · 128K —
IQ4_XS
Qwen3.8 27B
15.7 GB14.3 GB file
32K 17.0 GB · 128K 22.4 GB
Qwen3 8B
5.0 GB4.6 GB file
32K 9.5 GB · 128K —
IQ4_NL
Qwen3.8 27B
16.4 GB17.4 GB file
32K 17.7 GB · 128K 23.1 GB
Qwen3 8B
5.2 GB4.8 GB file
32K 9.7 GB · 128K —
Q4_1
Qwen3.8 27B
16.4 GB17.5 GB file
32K 17.7 GB · 128K 23.1 GB
Qwen3 8B
5.2 GB5.2 GB file
32K 9.7 GB · 128K —
Q4_K_S
Qwen3.8 27B
16.4 GB15.4 GB file
32K 17.7 GB · 128K 23.1 GB
Qwen3 8B
5.2 GB4.8 GB file
32K 9.7 GB · 128K —
Q4_K_L
Qwen3.8 27B
17.8 GB18.8 GB file
32K 19.1 GB · 128K 24.5 GB
Qwen3 8B
5.6 GB5.5 GB file
32K 10.2 GB · 128K —
Q5_0
Qwen3.8 27B
not listed
Qwen3 8B
5.7 GB5.7 GB file
32K 10.3 GB · 128K —
Q5_K_S
Qwen3.8 27B
19.9 GB18.7 GB file
32K 21.2 GB · 128K 26.6 GB
Qwen3 8B
6.2 GB5.7 GB file
32K 10.8 GB · 128K —
Q5_K_L
Qwen3.8 27B
20.9 GB21.5 GB file
32K 22.2 GB · 128K 27.6 GB
Qwen3 8B
6.5 GB6.2 GB file
32K 11.1 GB · 128K —
BF16
Qwen3.8 27B
56.3 GB54.7 GB file
32K 57.7 GB · 128K 63.0 GB
Qwen3 8B
17.0 GB16.4 GB file
32K 21.5 GB · 128K —
Qwen3.8 27B
Ollama · Q4_K_M
ollama run hf.co/unsloth/Qwen3.8-27B-GGUF:Q4_K_MQwen3 8B
Ollama · Q4_K_M
ollama run hf.co/Qwen/Qwen3-8B-GGUF:Q4_K_M| Spec | Qwen3.8 27B | Qwen3 8B |
|---|---|---|
| Publisher | Alibaba | Alibaba |
| Parameters | 27.8B | 8.2B |
| Architecture | Qwen3_5ForConditionalGeneration | Qwen3ForCausalLM |
| Context | 256K tokens | 40K tokens |
| Modalities | Vision, Function-calling | Chat, Function-calling |
| License | Apache 2.0 | Apache 2.0 |
| Released | Aug 2026 | Apr 2025 |
Frequently Asked Questions
Which is better, Qwen3.8 27B or Qwen3 8B?
Qwen3.8 27B leads llmrun Score 121.5 to 93.8; both fit 24 GB at Q4_K_M; Qwen3 8B is 3.1× faster on RTX 4090 (~119 vs ~38 tok/s). Choose Qwen3.8 27B for higher llmrun Score and stronger at reasoning; choose Qwen3 8B for fits an 8 GB GPU and 3.1× faster on RTX 4090.
Which needs less VRAM, Qwen3.8 27B or Qwen3 8B?
At Q4_K_M, Qwen3.8 27B requires 17.4 GB while Qwen3 8B needs 5.5 GB, making Qwen3 8B the easier model to run on your local setup.
Which is faster on RTX 4090?
Estimated decode speed on RTX 4090 is about 38 tok/s for Qwen3.8 27B (Q4_K_M) and 119 tok/s for Qwen3 8B (Q4_K_M), so Qwen3 8B is faster. Estimates, ±20%.
Can I run Qwen3.8 27B or Qwen3 8B on a 16 GB GPU?
Qwen3.8 27B fits at Q3_K_L; Qwen3 8B fits at Q4_K_M.
Which has a longer context window, Qwen3.8 27B or Qwen3 8B?
Qwen3.8 27B supports 262,144 tokens and Qwen3 8B supports 40,960 tokens.