Qwen3.8 27B vs GLM 5

Qwen3.8 27B leads llmrun Score 121.5 to 111.4; only Qwen3.8 27B fits 24 GB (Q4_K_M); GLM 5 needs 209.1 GB even at its smallest quant.

Model A · Alibaba

Qwen3.8 27B

121.5llmrun Score

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

VisionFunctions

Model B · Z.ai

GLM 5

111.4llmrun Score

753.9B · 42.4B active · 198K context · MIT · Feb 2026

ChatFunctions

Which should you choose?

Choose Qwen3.8 27B if you want…

Higher llmrun Score
121.5 vs 111.4
Stronger at reasoning
124.1 vs 109.1
Ahead on the benchmarks
3 of 4 shared boards
Fits a 12 GB GPU
IQ3_XXS · 12 GB; GLM 5 needs 209.1 GB at its smallest quant
Fits a Mac 32 GB
Q4_K_M · 17.9 GB; GLM 5 needs 209.1 GB at its smallest quant
Lighter on memory
17.4 vs 456.5 GB at Q4_K_M

Choose GLM 5 if you want…

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%.

MemoryQwen3.8 27BGLM 5

8 GB

RTX 4060 · 8 GB tier

Qwen3.8 27B

Doesn't fit

smallest quant needs 8.8 GB

GLM 5

Doesn't fit

smallest quant needs 209.1 GB

12 GB

RTX 3060 12GB · 12 GB tier

Qwen3.8 27B

IQ3_XXS · ~20 tok/s

12 GB · up to 16Kfits

GLM 5

Doesn't fit

smallest quant needs 209.1 GB

16 GB

RTX 5060 Ti 16GB · 16 GB tier

Qwen3.8 27B

Q3_K_L · ~19 tok/s

15.4 GB · up to 16Kfits

GLM 5

Doesn't fit

smallest quant needs 209.1 GB

24 GBreference

RTX 4090 · 24 GB tier

Qwen3.8 27B

Q4_K_M · ~38 tok/s

17.9 GB · up to 64Kfits

GLM 5

Doesn't fit

smallest quant needs 209.1 GB

32 GB

RTX 5090 · 32 GB tier

Qwen3.8 27B

Q4_K_M · ~67 tok/s

17.9 GB · up to 256Kfits

GLM 5

Doesn't fit

smallest quant needs 209.1 GB

48 GB

RTX A6000 · 48 GB tier

Qwen3.8 27B

Q4_K_M · ~29 tok/s

17.9 GB · up to 256Kfits

GLM 5

Doesn't fit

smallest quant needs 209.1 GB

Mac 32 GB

Mac Mini M4 · Macs

Qwen3.8 27B

Q4_K_M · ~5 tok/s

17.9 GB · up to 128Kfits

GLM 5

Doesn't fit

smallest quant needs 209.1 GB

Mac 64 GB

Mac Studio M4 Max · Macs

Qwen3.8 27B

Q4_K_M · ~22 tok/s

17.9 GB · up to 256Kfits

GLM 5

Doesn't fit

smallest quant needs 209.1 GB

Mac 128 GB

Mac Studio M4 Max · Macs

Qwen3.8 27B

Q4_K_M · ~22 tok/s

17.9 GB · up to 256Kfits

GLM 5

Doesn't fit

smallest quant needs 209.1 GB

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

Qwen3.8 27B GLM 5

Overall

Qwen3.8 27B

121.5119–124

GLM 5

111.4109–114

Coding

Qwen3.8 27B

112.1105–119

GLM 5

110.2103–118

Agents

Qwen3.8 27B

no data

GLM 5

117.9112–124

Math

Qwen3.8 27B

117.5111–125

GLM 5

no data

Science

Qwen3.8 27B

112.093–131

GLM 5

no data

Reasoning

Qwen3.8 27B

124.1121–127

GLM 5

109.1105–113

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

GLM 5 · #21 of 92 open models · #18 of 88 that fit ≤512 GB

Benchmarks

4 shared boards: Qwen3.8 27B leads 3, GLM 5 leads 1 · Benchmarks imported Oct 2026

BoardQwen3.8 27BGLM 5

LMArena Text

Qwen3.8 27B

1438.1#22/186 open

ArenaLMArena · Oct 2026

GLM 5

1457.5#12/186 open

ArenaLMArena · Oct 2026

LMArena WebDev

Qwen3.8 27B

1592.8#10/50 open

ArenaLMArena · Oct 2026

GLM 5

1434.4#23/50 open

ArenaLMArena · Oct 2026

ARC-AGI-2

Qwen3.8 27B

42.4%#5/18 open

IndependentEpoch AI · Aug 2026

GLM 5

4.9%#11/18 open

IndependentEpoch AI · Feb 2026

ARC-AGI

Qwen3.8 27B

87.5%#5/18 open

IndependentEpoch AI · Aug 2026

GLM 5

44.7%#12/18 open

IndependentEpoch AI · Feb 2026

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

Only Qwen3.8 27B (10)

Only GLM 5 (13)

VRAM by quantization

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

QuantQwen3.8 27BGLM 5

Q2_K

Qwen3.8 27B

12.6 GB10.8 GB file

32K 13.9 GB · 128K 19.3 GB

GLM 5

325 GB276.0 GB file

32K 324 GB · 128K 332 GB

Q3_K_S

Qwen3.8 27B

12.9 GB12.7 GB file

32K 14.2 GB · 128K 19.6 GB

GLM 5

334 GB326.3 GB file

32K 333 GB · 128K 342 GB

Q3_K_M

Qwen3.8 27B

14.3 GB13.4 GB file

32K 15.6 GB · 128K 21.0 GB

GLM 5

372 GB360.3 GB file

32K 371 GB · 128K 380 GB

Q4_0

Qwen3.8 27B

14.6 GB~13.9 GB file

32K 16.0 GB · 128K 21.4 GB

GLM 5

381 GB427.1 GB file

32K 380 GB · 128K 389 GB

Q4_K_M

Qwen3.8 27B

17.4 GB16.5 GB file

32K 18.8 GB · 128K 24.1 GB

GLM 5

457 GB455.9 GB file

32K 456 GB · 128K 464 GB

Q5_K_M

Qwen3.8 27B

20.5 GB19.8 GB file

32K 21.9 GB · 128K 27.3 GB

GLM 5

541 GB535.2 GB file

32K 540 GB · 128K 549 GB

Q6_K

Qwen3.8 27B

23.7 GB22.0 GB file

32K 25.0 GB · 128K 30.4 GB

GLM 5

626 GB619.4 GB file

32K 625 GB · 128K 634 GB

Q8_0

Qwen3.8 27B

28.5 GB29.0 GB file

32K 29.9 GB · 128K 35.2 GB

GLM 5

758 GB801.3 GB file

32K 757 GB · 128K 766 GB

17 more quants

IQ2_XXS

Qwen3.8 27B

8.4 GB7.3 GB file

32K 9.7 GB · 128K 15.1 GB

GLM 5

212 GB241.1 GB file

32K 211 GB · 128K 219 GB

IQ2_XS

Qwen3.8 27B

9.1 GB9.1 GB file

32K 10.4 GB · 128K 15.8 GB

GLM 5

not listed

IQ2_S

Qwen3.8 27B

9.4 GB8.4 GB file

32K 10.8 GB · 128K 16.1 GB

GLM 5

not listed

IQ2_M

Qwen3.8 27B

10.1 GB10.5 GB file

32K 11.5 GB · 128K 16.8 GB

GLM 5

259 GB254.8 GB file

32K 258 GB · 128K 267 GB

IQ3_XXS

Qwen3.8 27B

11.5 GB10.9 GB file

32K 12.9 GB · 128K 18.2 GB

GLM 5

296 GB304.5 GB file

32K 295 GB · 128K 304 GB

IQ3_XS

Qwen3.8 27B

12.2 GB10.4 GB file

32K 13.6 GB · 128K 18.9 GB

GLM 5

not listed

IQ3_S

Qwen3.8 27B

12.6 GB12.0 GB file

32K 13.9 GB · 128K 19.3 GB

GLM 5

not listed

IQ3_M

Qwen3.8 27B

13.3 GB14.9 GB file

32K 14.6 GB · 128K 20.0 GB

GLM 5

not listed

Q3_K_L

Qwen3.8 27B

15.0 GB14.1 GB file

32K 16.3 GB · 128K 21.7 GB

GLM 5

not listed

IQ4_XS

Qwen3.8 27B

15.7 GB14.3 GB file

32K 17.0 GB · 128K 22.4 GB

GLM 5

409 GB402.9 GB file

32K 408 GB · 128K 417 GB

IQ4_NL

Qwen3.8 27B

16.4 GB17.4 GB file

32K 17.7 GB · 128K 23.1 GB

GLM 5

428 GB425.9 GB file

32K 427 GB · 128K 436 GB

Q4_1

Qwen3.8 27B

16.4 GB17.5 GB file

32K 17.7 GB · 128K 23.1 GB

GLM 5

428 GB472.7 GB file

32K 427 GB · 128K 436 GB

Q4_K_S

Qwen3.8 27B

16.4 GB15.4 GB file

32K 17.7 GB · 128K 23.1 GB

GLM 5

428 GB428.4 GB file

32K 427 GB · 128K 436 GB

Q4_K_L

Qwen3.8 27B

17.8 GB18.8 GB file

32K 19.1 GB · 128K 24.5 GB

GLM 5

not listed

Q5_K_S

Qwen3.8 27B

19.9 GB18.7 GB file

32K 21.2 GB · 128K 26.6 GB

GLM 5

523 GB519.7 GB file

32K 522 GB · 128K 530 GB

Q5_K_L

Qwen3.8 27B

20.9 GB21.5 GB file

32K 22.2 GB · 128K 27.6 GB

GLM 5

not listed

BF16

Qwen3.8 27B

56.3 GB54.7 GB file

32K 57.7 GB · 128K 63.0 GB

GLM 5

1512 GB1508.0 GB file

32K 1511 GB · 128K 1520 GB

How to run each

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 →

GLM 5

Ollama · Q4_K_M

$ollama run hf.co/unsloth/GLM-5-GGUF:Q4_K_M

All ways to run GLM 5 →

Specifications

Specifications of Qwen3.8 27B and GLM 5
Spec	Qwen3.8 27B	GLM 5
Publisher	Alibaba	Z.ai
Parameters	27.8B	753.9B
Active parameters	—	42B per token
Architecture	Qwen3_5ForConditionalGeneration	GlmMoeDsaForCausalLM
Context	256K tokens	198K tokens
Modalities	Vision, Function-calling	Chat, Function-calling
License	Apache 2.0	MIT
Released	Aug 2026	Feb 2026

Frequently Asked Questions

Which is better, Qwen3.8 27B or GLM 5?

Qwen3.8 27B leads llmrun Score 121.5 to 111.4; only Qwen3.8 27B fits 24 GB (Q4_K_M); GLM 5 needs 209.1 GB even at its smallest quant. Choose Qwen3.8 27B for higher llmrun Score and stronger at reasoning; choose GLM 5 for also does chat.

Which needs less VRAM, Qwen3.8 27B or GLM 5?

At Q4_K_M, Qwen3.8 27B requires 17.4 GB while GLM 5 needs 456.5 GB, making Qwen3.8 27B the easier model to run on your local setup.

Can I run Qwen3.8 27B or GLM 5 on a 16 GB GPU?

Qwen3.8 27B fits at Q3_K_L; GLM 5 does not fit (smallest quant needs 209.1 GB).

Which has a longer context window, Qwen3.8 27B or GLM 5?

Qwen3.8 27B supports 262,144 tokens and GLM 5 supports 202,752 tokens.