DeepSeek V3.2 vs GLM 5.3

GLM 5.3 leads llmrun Score 130.1 to 110.4; neither fits 24 GB.

Run GLM 5.3 in the cloud →

Model A · DeepSeek

DeepSeek V3.2

110.4llmrun Score

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

Chat

Model B · Z.ai

GLM 5.3

130.1llmrun Score

753.3B · 41.8B active · 1M context · Other · Aug 2026

ChatFunctions

Which should you choose?

Choose DeepSeek V3.2 if you want…

More permissive license
MIT vs Other

Choose GLM 5.3 if you want…

Higher llmrun Score
130.1 vs 110.4
Stronger at agents
133.5 vs 108.1
Stronger at reasoning
130.1 vs 112.0
Ahead on the benchmarks
4 of 4 shared boards
Longer context window
1M vs 160K tokens
Also does function-calling
DeepSeek V3.2 doesn't list it

On your hardware

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

MemoryDeepSeek V3.2GLM 5.3

8 GB

RTX 4060 · 8 GB tier

DeepSeek V3.2

Doesn't fit

smallest quant needs 189.9 GB

GLM 5.3

Doesn't fit

smallest quant needs 256 GB

12 GB

RTX 3060 12GB · 12 GB tier

DeepSeek V3.2

Doesn't fit

smallest quant needs 189.9 GB

GLM 5.3

Doesn't fit

smallest quant needs 256 GB

16 GB

RTX 5060 Ti 16GB · 16 GB tier

DeepSeek V3.2

Doesn't fit

smallest quant needs 189.9 GB

GLM 5.3

Doesn't fit

smallest quant needs 256 GB

24 GBreference

RTX 4090 · 24 GB tier

DeepSeek V3.2

Doesn't fit

smallest quant needs 189.9 GB

GLM 5.3

Doesn't fit

smallest quant needs 256 GB

32 GB

RTX 5090 · 32 GB tier

DeepSeek V3.2

Doesn't fit

smallest quant needs 189.9 GB

GLM 5.3

Doesn't fit

smallest quant needs 256 GB

48 GB

RTX A6000 · 48 GB tier

DeepSeek V3.2

Doesn't fit

smallest quant needs 189.9 GB

GLM 5.3

Doesn't fit

smallest quant needs 256 GB

Mac 32 GB

Mac Mini M4 · Macs

DeepSeek V3.2

Doesn't fit

smallest quant needs 189.9 GB

GLM 5.3

Doesn't fit

smallest quant needs 256 GB

Mac 64 GB

Mac Studio M4 Max · Macs

DeepSeek V3.2

Doesn't fit

smallest quant needs 189.9 GB

GLM 5.3

Doesn't fit

smallest quant needs 256 GB

Mac 128 GB

Mac Studio M4 Max · Macs

DeepSeek V3.2

Doesn't fit

smallest quant needs 189.9 GB

GLM 5.3

Doesn't fit

smallest quant needs 256 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

DeepSeek V3.2 GLM 5.3

Overall

DeepSeek V3.2

110.4107–113

GLM 5.3

130.1128–132

Coding

DeepSeek V3.2

no data

GLM 5.3

129.9124–136

Agents

DeepSeek V3.2

108.1103–113

GLM 5.3

133.5130–137

Math

DeepSeek V3.2

no data

GLM 5.3

128.5126–131

Science

DeepSeek V3.2

no data

GLM 5.3

130.6118–143

Reasoning

DeepSeek V3.2

112.0108–116

GLM 5.3

130.1124–136

DeepSeek V3.2 · #31 of 106 open models · #27 of 102 that fit ≤512 GB

GLM 5.3 · #6 of 106 open models · #4 of 102 that fit ≤512 GB

Benchmarks

4 shared boards: DeepSeek V3.2 leads 0, GLM 5.3 leads 4 · Benchmarks imported Nov 2026

BoardDeepSeek V3.2GLM 5.3

APEX-Agents

DeepSeek V3.2

21.3%#19/20 open

Lab-reportedEpoch AI · Dec 2025

GLM 5.3

56.6%#2/20 open

Lab-reportedEpoch AI · Aug 2026

DTBench

DeepSeek V3.2

85.6%#16/70 open

Lab-reportedEpoch AI · Dec 2025

GLM 5.3

87.7%#12/70 open

Lab-reportedEpoch AI · Aug 2026

LMCA

DeepSeek V3.2

28.8%#26/56 open

Lab-reportedEpoch AI · Dec 2025

GLM 5.3

55.5%#1/56 open

Lab-reportedEpoch AI · Aug 2026

ProofBench

DeepSeek V3.2

8.0%#23/31 open

Lab-reportedEpoch AI · Dec 2025

GLM 5.3

49.0%#9/31 open

Lab-reportedEpoch AI · Aug 2026

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

LMArena Text

DeepSeek V3.2

1424.6#31/188 open

ArenaLMArena · Oct 2026

GLM 5.3

1480.6#2/188 open

ArenaLMArena · Oct 2026

LMArena WebDev

DeepSeek V3.2

1362.5#36/55 open

ArenaLMArena · Oct 2026

GLM 5.3

1622.8#7/55 open

ArenaLMArena · Oct 2026

Only DeepSeek V3.2 (10)

Only GLM 5.3 (26)

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 V3.2GLM 5.3

Q2_K

DeepSeek V3.2

295 GB245.4 GB file

32K 294 GB · 128K 301 GB

GLM 5.3

324 GB~320.2 GB file

32K 323 GB · 128K 332 GB

Q3_K_S

DeepSeek V3.2

304 GB290.4 GB file

32K 302 GB · 128K 309 GB

GLM 5.3

not listed

Q3_K_M

DeepSeek V3.2

338 GB320.2 GB file

32K 337 GB · 128K 344 GB

GLM 5.3

371 GB~367.3 GB file

32K 370 GB · 128K 379 GB

Q4_0

DeepSeek V3.2

347 GB380.1 GB file

32K 345 GB · 128K 352 GB

GLM 5.3

not listed

Q4_K_M

DeepSeek V3.2

415 GB405.4 GB file

32K 414 GB · 128K 421 GB

GLM 5.3

456 GB~452.0 GB file

32K 455 GB · 128K 464 GB

Q5_K_M

DeepSeek V3.2

492 GB476.2 GB file

32K 491 GB · 128K 498 GB

GLM 5.3

541 GB~536.8 GB file

32K 540 GB · 128K 549 GB

Q6_K

DeepSeek V3.2

569 GB551.3 GB file

32K 568 GB · 128K 575 GB

GLM 5.3

626 GB~621.5 GB file

32K 625 GB · 128K 634 GB

Q8_0

DeepSeek V3.2

689 GB713.3 GB file

32K 688 GB · 128K 695 GB

GLM 5.3

758 GB801.4 GB file

32K 757 GB · 128K 765 GB

9 more quants

IQ2_XXS

DeepSeek V3.2

192 GB217.1 GB file

32K 191 GB · 128K 198 GB

GLM 5.3

not listed

IQ2_M

DeepSeek V3.2

235 GB228.1 GB file

32K 234 GB · 128K 241 GB

GLM 5.3

258 GB238.6 GB file

32K 257 GB · 128K 266 GB

IQ3_XXS

DeepSeek V3.2

269 GB273.1 GB file

32K 268 GB · 128K 275 GB

GLM 5.3

296 GB281.7 GB file

32K 295 GB · 128K 304 GB

IQ4_XS

DeepSeek V3.2

372 GB358.3 GB file

32K 371 GB · 128K 378 GB

GLM 5.3

409 GB365.3 GB file

32K 408 GB · 128K 417 GB

IQ4_NL

DeepSeek V3.2

389 GB379.1 GB file

32K 388 GB · 128K 395 GB

GLM 5.3

not listed

Q4_1

DeepSeek V3.2

389 GB420.8 GB file

32K 388 GB · 128K 395 GB

GLM 5.3

not listed

Q4_K_S

DeepSeek V3.2

389 GB381.1 GB file

32K 388 GB · 128K 395 GB

GLM 5.3

not listed

Q5_K_S

DeepSeek V3.2

475 GB462.6 GB file

32K 474 GB · 128K 481 GB

GLM 5.3

not listed

BF16

DeepSeek V3.2

1375 GB1342.3 GB file

32K 1373 GB · 128K 1380 GB

GLM 5.3

1511 GB1508.0 GB file

32K 1510 GB · 128K 1519 GB

How to run each

DeepSeek V3.2

Ollama · Q4_K_M

$ollama run hf.co/unsloth/DeepSeek-V3.2-GGUF:Q4_K_M

All ways to run DeepSeek V3.2 →

GLM 5.3

Ollama · Q4_K_M

$ollama run hf.co/unsloth/GLM-5.3-GGUF

All ways to run GLM 5.3 →

Specifications

Specifications of DeepSeek V3.2 and GLM 5.3
Spec	DeepSeek V3.2	GLM 5.3
Publisher	DeepSeek	Z.ai
Parameters	685.4B	753.3B
Active parameters	41B per token	42B per token
Architecture	DeepseekV32ForCausalLM	GlmMoeDsaForCausalLM
Context	160K tokens	1M tokens
Modalities	Chat	Chat, Function-calling
License	MIT	Other
Released	Dec 2025	Aug 2026

Frequently Asked Questions

Which is better, DeepSeek V3.2 or GLM 5.3?

GLM 5.3 leads llmrun Score 130.1 to 110.4; neither fits 24 GB. Choose DeepSeek V3.2 for more permissive license; choose GLM 5.3 for higher llmrun Score and stronger at agents.

Which needs less VRAM, DeepSeek V3.2 or GLM 5.3?

At Q4_K_M, DeepSeek V3.2 requires 415.1 GB while GLM 5.3 needs 456.2 GB, making DeepSeek V3.2 the easier model to run on your local setup.

Can I run DeepSeek V3.2 or GLM 5.3 on a 16 GB GPU?

DeepSeek V3.2 does not fit (smallest quant needs 189.9 GB); GLM 5.3 does not fit (smallest quant needs 256 GB).

Which has a longer context window, DeepSeek V3.2 or GLM 5.3?

DeepSeek V3.2 supports 163,840 tokens and GLM 5.3 supports 1,048,576 tokens.