DeepSeek V3.2 Exp vs GLM 5.3

GLM 5.3 leads llmrun Score 130.1 to 109.0; neither fits 24 GB.

Run GLM 5.3 in the cloud →

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 5.3

130.1llmrun Score

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

ChatFunctions

Which should you choose?

Choose DeepSeek V3.2 Exp if you want…

More permissive license
MIT vs Other

Choose GLM 5.3 if you want…

Higher llmrun Score
130.1 vs 109.0
Stronger at science
130.6 vs 101.2
Stronger at coding
129.9 vs 106.8
Ahead on the benchmarks
5 of 6 shared boards
Longer context window
1M vs 160K tokens
Newer release
Aug 2026 vs Sep 2025

On your hardware

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

MemoryDeepSeek V3.2 ExpGLM 5.3

8 GB

RTX 4060 · 8 GB tier

DeepSeek V3.2 Exp

Doesn't fit

smallest quant needs 292.8 GB

GLM 5.3

Doesn't fit

smallest quant needs 256 GB

12 GB

RTX 3060 12GB · 12 GB tier

DeepSeek V3.2 Exp

Doesn't fit

smallest quant needs 292.8 GB

GLM 5.3

Doesn't fit

smallest quant needs 256 GB

16 GB

RTX 5060 Ti 16GB · 16 GB tier

DeepSeek V3.2 Exp

Doesn't fit

smallest quant needs 292.8 GB

GLM 5.3

Doesn't fit

smallest quant needs 256 GB

24 GBreference

RTX 4090 · 24 GB tier

DeepSeek V3.2 Exp

Doesn't fit

smallest quant needs 292.8 GB

GLM 5.3

Doesn't fit

smallest quant needs 256 GB

32 GB

RTX 5090 · 32 GB tier

DeepSeek V3.2 Exp

Doesn't fit

smallest quant needs 292.8 GB

GLM 5.3

Doesn't fit

smallest quant needs 256 GB

48 GB

RTX A6000 · 48 GB tier

DeepSeek V3.2 Exp

Doesn't fit

smallest quant needs 292.8 GB

GLM 5.3

Doesn't fit

smallest quant needs 256 GB

Mac 32 GB

Mac Mini M4 · Macs

DeepSeek V3.2 Exp

Doesn't fit

smallest quant needs 292.8 GB

GLM 5.3

Doesn't fit

smallest quant needs 256 GB

Mac 64 GB

Mac Studio M4 Max · Macs

DeepSeek V3.2 Exp

Doesn't fit

smallest quant needs 292.8 GB

GLM 5.3

Doesn't fit

smallest quant needs 256 GB

Mac 128 GB

Mac Studio M4 Max · Macs

DeepSeek V3.2 Exp

Doesn't fit

smallest quant needs 292.8 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 Exp GLM 5.3

Overall

DeepSeek V3.2 Exp

109.0105–114

GLM 5.3

130.1128–132

Coding

DeepSeek V3.2 Exp

106.8101–113

GLM 5.3

129.9124–136

Agents

DeepSeek V3.2 Exp

no data

GLM 5.3

133.5130–137

Math

DeepSeek V3.2 Exp

no data

GLM 5.3

128.5126–131

Science

DeepSeek V3.2 Exp

101.280–123

GLM 5.3

130.6118–143

Reasoning

DeepSeek V3.2 Exp

113.3104–123

GLM 5.3

130.1124–136

DeepSeek V3.2 Exp · #35 of 106 open models · #31 of 102 that fit ≤512 GB

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

Benchmarks

6 shared boards: DeepSeek V3.2 Exp leads 0, GLM 5.3 leads 5 · Benchmarks imported Nov 2026

BoardDeepSeek V3.2 ExpGLM 5.3

SciCode

DeepSeek V3.2 Exp

38.9%#40/72 open

Lab-reportedEpoch AI · Sep 2025

GLM 5.3

59.0%#4/72 open

Lab-reportedEpoch AI · Aug 2026

WeirdML

DeepSeek V3.2 Exp

39.5%#25/47 open

IndependentEpoch AI · Sep 2025

GLM 5.3

75.4%#2/47 open

IndependentEpoch AI · Aug 2026

CritPt

DeepSeek V3.2 Exp

2.9%#30/84 open

Lab-reportedEpoch AI · Sep 2025

GLM 5.3

19.1%#7/84 open

Lab-reportedEpoch AI · Aug 2026

DTBench

DeepSeek V3.2 Exp

87.7%#11/70 open

Lab-reportedEpoch AI · Sep 2025

GLM 5.3

87.7%#12/70 open

Lab-reportedEpoch AI · Aug 2026

LMCA

DeepSeek V3.2 Exp

29.1%#25/56 open

Lab-reportedEpoch AI · Sep 2025

GLM 5.3

55.5%#1/56 open

Lab-reportedEpoch AI · Aug 2026

Vending-Bench 2

DeepSeek V3.2 Exp

1034.0#12/17 open

Lab-reportedEpoch AI · Sep 2025

GLM 5.3

8163.6#2/17 open

Lab-reportedEpoch AI · Aug 2026

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

LMArena Text

DeepSeek V3.2 Exp

1425.1#29/188 open

ArenaLMArena · Oct 2026

GLM 5.3

1480.6#2/188 open

ArenaLMArena · Oct 2026

LMArena WebDev

DeepSeek V3.2 Exp

1271.4#49/55 open

ArenaLMArena · Oct 2026

GLM 5.3

1622.8#7/55 open

ArenaLMArena · Oct 2026

Only DeepSeek V3.2 Exp (4)

Only GLM 5.3 (24)

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 5.3

Q2_K

DeepSeek V3.2 Exp

295 GB~291.3 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_M

DeepSeek V3.2 Exp

338 GB~334.1 GB file

32K 337 GB · 128K 344 GB

GLM 5.3

371 GB~367.3 GB file

32K 370 GB · 128K 379 GB

Q4_K_M

DeepSeek V3.2 Exp

415 GB~411.2 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 Exp

492 GB~488.4 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 Exp

569 GB~565.5 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 Exp

689 GB~685.4 GB file

32K 688 GB · 128K 695 GB

GLM 5.3

758 GB801.4 GB file

32K 757 GB · 128K 765 GB

4 more quants

IQ2_M

DeepSeek V3.2 Exp

not listed

GLM 5.3

258 GB238.6 GB file

32K 257 GB · 128K 266 GB

IQ3_XXS

DeepSeek V3.2 Exp

not listed

GLM 5.3

296 GB281.7 GB file

32K 295 GB · 128K 304 GB

IQ4_XS

DeepSeek V3.2 Exp

not listed

GLM 5.3

409 GB365.3 GB file

32K 408 GB · 128K 417 GB

BF16

DeepSeek V3.2 Exp

1375 GB~1370.8 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 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 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 Exp and GLM 5.3
Spec	DeepSeek V3.2 Exp	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, Function-calling	Chat, Function-calling
License	MIT	Other
Released	Sep 2025	Aug 2026

Frequently Asked Questions

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

GLM 5.3 leads llmrun Score 130.1 to 109.0; neither fits 24 GB. Choose DeepSeek V3.2 Exp for more permissive license; choose GLM 5.3 for higher llmrun Score and stronger at science.

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

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

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

DeepSeek V3.2 Exp does not fit (smallest quant needs 292.8 GB); GLM 5.3 does not fit (smallest quant needs 256 GB).

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

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