DeepSeek V3.2 Exp vs GLM 4.7

DeepSeek V3.2 Exp and GLM 4.7 match in llmrun Score, with values of 109.0 versus 108.3; neither fits 24 GB.

Model A · DeepSeek

DeepSeek V3.2 Exp

109.0llmrun Score

685.4B · 41B active · 160K context · MIT · Sep 2025

ChatFunctions

Model B · Z.ai

GLM 4.7

108.3llmrun Score

358.3B · 35.6B active · 198K context · MIT · Dec 2025

ChatFunctions

Which should you choose?

Choose DeepSeek V3.2 Exp if you want…

Stronger at reasoning
113.4 vs 104.3

Choose GLM 4.7 if you want…

Stronger at science
111.2 vs 101.2
Ahead on the benchmarks
3 of 4 shared boards
Lighter on memory
215.6 vs 415.1 GB at Q4_K_M

On your hardware

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

MemoryDeepSeek V3.2 ExpGLM 4.7

8 GB

RTX 4060 · 8 GB tier

DeepSeek V3.2 Exp

Doesn't fit

smallest quant needs 292.8 GB

GLM 4.7

Doesn't fit

smallest quant needs 101.4 GB

12 GB

RTX 3060 12GB · 12 GB tier

DeepSeek V3.2 Exp

Doesn't fit

smallest quant needs 292.8 GB

GLM 4.7

Doesn't fit

smallest quant needs 101.4 GB

16 GB

RTX 5060 Ti 16GB · 16 GB tier

DeepSeek V3.2 Exp

Doesn't fit

smallest quant needs 292.8 GB

GLM 4.7

Doesn't fit

smallest quant needs 101.4 GB

24 GBreference

RTX 4090 · 24 GB tier

DeepSeek V3.2 Exp

Doesn't fit

smallest quant needs 292.8 GB

GLM 4.7

Doesn't fit

smallest quant needs 101.4 GB

32 GB

RTX 5090 · 32 GB tier

DeepSeek V3.2 Exp

Doesn't fit

smallest quant needs 292.8 GB

GLM 4.7

Doesn't fit

smallest quant needs 101.4 GB

48 GB

RTX A6000 · 48 GB tier

DeepSeek V3.2 Exp

Doesn't fit

smallest quant needs 292.8 GB

GLM 4.7

Doesn't fit

smallest quant needs 101.4 GB

Mac 32 GB

Mac Mini M4 · Macs

DeepSeek V3.2 Exp

Doesn't fit

smallest quant needs 292.8 GB

GLM 4.7

Doesn't fit

smallest quant needs 101.4 GB

Mac 64 GB

Mac Studio M4 Max · Macs

DeepSeek V3.2 Exp

Doesn't fit

smallest quant needs 292.8 GB

GLM 4.7

Doesn't fit

smallest quant needs 101.4 GB

Mac 128 GB

Mac Studio M4 Max · Macs

DeepSeek V3.2 Exp

Doesn't fit

smallest quant needs 292.8 GB

GLM 4.7

IQ2_M · ~20 tok/s

123.8 GB · up to 16Kfits

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

DeepSeek V3.2 Exp GLM 4.7

Overall

DeepSeek V3.2 Exp

109.0105–113

GLM 4.7

108.3105–112

Coding

DeepSeek V3.2 Exp

106.8101–113

GLM 4.7

101.388–115

Agents

DeepSeek V3.2 Exp

no data

GLM 4.7

105.898–114

Math

DeepSeek V3.2 Exp

no data

GLM 4.7

111.1104–118

Science

DeepSeek V3.2 Exp

101.280–122

GLM 4.7

111.2102–120

Reasoning

DeepSeek V3.2 Exp

113.4104–123

GLM 4.7

104.392–116

DeepSeek V3.2 Exp · #27 of 92 open models · #24 of 88 that fit ≤512 GB

GLM 4.7 · #29 of 92 open models · #18 of 77 that fit ≤256 GB

Benchmarks

4 shared boards: DeepSeek V3.2 Exp leads 1, GLM 4.7 leads 3 · Benchmarks imported Oct 2026

BoardDeepSeek V3.2 ExpGLM 4.7

LMArena Text

DeepSeek V3.2 Exp

1424.8#28/186 open

ArenaLMArena · Oct 2026

GLM 4.7

1441.2#18/186 open

ArenaLMArena · Oct 2026

LMArena WebDev

DeepSeek V3.2 Exp

1272.4#44/50 open

ArenaLMArena · Oct 2026

GLM 4.7

1435.0#22/50 open

ArenaLMArena · Oct 2026

SciCode

DeepSeek V3.2 Exp

38.9%#32/65 open

Lab-reportedEpoch AI · Sep 2025

GLM 4.7

45.1%#20/65 open

Lab-reportedEpoch AI · Dec 2025

CritPt

DeepSeek V3.2 Exp

2.9%#25/65 open

Lab-reportedEpoch AI · Sep 2025

GLM 4.7

1.7%#28/65 open

Lab-reportedEpoch AI · Dec 2025

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

CL-bench

DeepSeek V3.2 Exp

13.2%#5/7 open

Lab-reportedEpoch AI · Sep 2025

GLM 4.7

15.9%#4/7 open

Lab-reportedEpoch AI · Dec 2025

CL-bench Life

DeepSeek V3.2 Exp

9.5%#4/6 open

Lab-reportedEpoch AI · Sep 2025

GLM 4.7

10.9%#3/6 open

Lab-reportedEpoch AI · Dec 2025

Vending-Bench 2

DeepSeek V3.2 Exp

1034.0#12/17 open

Lab-reportedEpoch AI · Sep 2025

GLM 4.7

2376.8#9/17 open

Lab-reportedEpoch AI · Dec 2025

Only DeepSeek V3.2 Exp (5)

Only GLM 4.7 (8)

VRAM by quantization

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

QuantDeepSeek V3.2 ExpGLM 4.7

Q2_K

DeepSeek V3.2 Exp

295 GB~291.3 GB file

32K 294 GB · 128K 301 GB

GLM 4.7

153 GB131.2 GB file

32K 158 GB · 128K 173 GB

Q3_K_S

DeepSeek V3.2 Exp

not listed

GLM 4.7

157 GB155.0 GB file

32K 162 GB · 128K 178 GB

Q3_K_M

DeepSeek V3.2 Exp

338 GB~334.1 GB file

32K 337 GB · 128K 344 GB

GLM 4.7

175 GB171.3 GB file

32K 180 GB · 128K 196 GB

Q4_0

DeepSeek V3.2 Exp

not listed

GLM 4.7

180 GB203.0 GB file

32K 185 GB · 128K 200 GB

Q4_K_M

DeepSeek V3.2 Exp

415 GB~411.2 GB file

32K 414 GB · 128K 421 GB

GLM 4.7

216 GB216.5 GB file

32K 220 GB · 128K 236 GB

Q5_K_M

DeepSeek V3.2 Exp

492 GB~488.4 GB file

32K 491 GB · 128K 498 GB

GLM 4.7

256 GB254.2 GB file

32K 261 GB · 128K 276 GB

Q6_K

DeepSeek V3.2 Exp

569 GB~565.5 GB file

32K 568 GB · 128K 575 GB

GLM 4.7

296 GB294.4 GB file

32K 301 GB · 128K 317 GB

Q8_0

DeepSeek V3.2 Exp

689 GB~685.4 GB file

32K 688 GB · 128K 695 GB

GLM 4.7

359 GB381.0 GB file

32K 364 GB · 128K 379 GB

16 more quants

IQ2_XXS

DeepSeek V3.2 Exp

not listed

GLM 4.7

99.2 GB115.9 GB file

32K 104 GB · 128K 119 GB

IQ2_XS

DeepSeek V3.2 Exp

not listed

GLM 4.7

108 GB101.5 GB file

32K 113 GB · 128K 128 GB

IQ2_S

DeepSeek V3.2 Exp

not listed

GLM 4.7

113 GB102.3 GB file

32K 117 GB · 128K 133 GB

IQ2_M

DeepSeek V3.2 Exp

not listed

GLM 4.7

122 GB122.4 GB file

32K 126 GB · 128K 142 GB

IQ3_XXS

DeepSeek V3.2 Exp

not listed

GLM 4.7

139 GB145.1 GB file

32K 144 GB · 128K 160 GB

IQ3_XS

DeepSeek V3.2 Exp

not listed

GLM 4.7

148 GB148.7 GB file

32K 153 GB · 128K 169 GB

IQ3_S

DeepSeek V3.2 Exp

not listed

GLM 4.7

153 GB154.6 GB file

32K 158 GB · 128K 173 GB

IQ3_M

DeepSeek V3.2 Exp

not listed

GLM 4.7

162 GB164.8 GB file

32K 167 GB · 128K 182 GB

Q3_K_L

DeepSeek V3.2 Exp

not listed

GLM 4.7

184 GB170.6 GB file

32K 189 GB · 128K 205 GB

IQ4_XS

DeepSeek V3.2 Exp

not listed

GLM 4.7

193 GB191.6 GB file

32K 198 GB · 128K 213 GB

IQ4_NL

DeepSeek V3.2 Exp

not listed

GLM 4.7

202 GB202.5 GB file

32K 207 GB · 128K 222 GB

Q4_1

DeepSeek V3.2 Exp

not listed

GLM 4.7

202 GB224.6 GB file

32K 207 GB · 128K 222 GB

Q4_K_S

DeepSeek V3.2 Exp

not listed

GLM 4.7

202 GB203.7 GB file

32K 207 GB · 128K 222 GB

Q4_K_L

DeepSeek V3.2 Exp

not listed

GLM 4.7

220 GB219.1 GB file

32K 225 GB · 128K 240 GB

Q5_K_S

DeepSeek V3.2 Exp

not listed

GLM 4.7

247 GB247.0 GB file

32K 252 GB · 128K 267 GB

BF16

DeepSeek V3.2 Exp

1375 GB~1370.8 GB file

32K 1373 GB · 128K 1380 GB

GLM 4.7

717 GB716.8 GB file

32K 722 GB · 128K 738 GB

How to run each

DeepSeek V3.2 Exp

No local recipe · Q4_K_M

No GGUF repo entry exists for this model yet.

All ways to run DeepSeek V3.2 Exp →

GLM 4.7

Ollama · Q4_K_M

$ollama run hf.co/unsloth/GLM-4.7-GGUF:Q4_K_M

All ways to run GLM 4.7 →

Specifications

Specifications of DeepSeek V3.2 Exp and GLM 4.7
Spec	DeepSeek V3.2 Exp	GLM 4.7
Publisher	DeepSeek	Z.ai
Parameters	685.4B	358.3B
Active parameters	41B per token	36B per token
Architecture	DeepseekV32ForCausalLM	Glm4MoeForCausalLM
Context	160K tokens	198K tokens
Modalities	Chat, Function-calling	Chat, Function-calling
License	MIT	MIT
Released	Sep 2025	Dec 2025

Frequently Asked Questions

Which is better, DeepSeek V3.2 Exp or GLM 4.7?

DeepSeek V3.2 Exp and GLM 4.7 match in llmrun Score, with values of 109.0 versus 108.3; neither fits 24 GB. Choose DeepSeek V3.2 Exp for stronger at reasoning; choose GLM 4.7 for stronger at science and ahead on the benchmarks.

Which needs less VRAM, DeepSeek V3.2 Exp or GLM 4.7?

At Q4_K_M, DeepSeek V3.2 Exp requires 415.1 GB while GLM 4.7 needs 215.6 GB, making GLM 4.7 the easier model to run on your local setup.

Can I run DeepSeek V3.2 Exp or GLM 4.7 on a 16 GB GPU?

DeepSeek V3.2 Exp does not fit (smallest quant needs 292.8 GB); GLM 4.7 does not fit (smallest quant needs 101.4 GB).

Which has a longer context window, DeepSeek V3.2 Exp or GLM 4.7?

DeepSeek V3.2 Exp supports 163,840 tokens and GLM 4.7 supports 202,752 tokens.