DeepSeek V4 Pro 0813 vs GLM 5.3

DeepSeek V4 Pro 0813 and GLM 5.3 match in llmrun Score, with values of 129.2 versus 130.1; neither fits 24 GB.

Model A · DeepSeek

DeepSeek V4 Pro 0813

129.2llmrun Score

1650.5B · 102.3B active · 1M context · MIT · Aug 2026

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 V4 Pro 0813 if you want…

More permissive license
MIT vs Other

Choose GLM 5.3 if you want…

Lighter on memory
456.2 vs 990.6 GB at Q4_K_M
Also does function-calling
DeepSeek V4 Pro 0813 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 V4 Pro 0813GLM 5.3

8 GB

RTX 4060 · 8 GB tier

DeepSeek V4 Pro 0813

Doesn't fit

smallest quant needs 640.1 GB

GLM 5.3

Doesn't fit

smallest quant needs 256 GB

12 GB

RTX 3060 12GB · 12 GB tier

DeepSeek V4 Pro 0813

Doesn't fit

smallest quant needs 640.1 GB

GLM 5.3

Doesn't fit

smallest quant needs 256 GB

16 GB

RTX 5060 Ti 16GB · 16 GB tier

DeepSeek V4 Pro 0813

Doesn't fit

smallest quant needs 640.1 GB

GLM 5.3

Doesn't fit

smallest quant needs 256 GB

24 GBreference

RTX 4090 · 24 GB tier

DeepSeek V4 Pro 0813

Doesn't fit

smallest quant needs 640.1 GB

GLM 5.3

Doesn't fit

smallest quant needs 256 GB

32 GB

RTX 5090 · 32 GB tier

DeepSeek V4 Pro 0813

Doesn't fit

smallest quant needs 640.1 GB

GLM 5.3

Doesn't fit

smallest quant needs 256 GB

48 GB

RTX A6000 · 48 GB tier

DeepSeek V4 Pro 0813

Doesn't fit

smallest quant needs 640.1 GB

GLM 5.3

Doesn't fit

smallest quant needs 256 GB

Mac 32 GB

Mac Mini M4 · Macs

DeepSeek V4 Pro 0813

Doesn't fit

smallest quant needs 640.1 GB

GLM 5.3

Doesn't fit

smallest quant needs 256 GB

Mac 64 GB

Mac Studio M4 Max · Macs

DeepSeek V4 Pro 0813

Doesn't fit

smallest quant needs 640.1 GB

GLM 5.3

Doesn't fit

smallest quant needs 256 GB

Mac 128 GB

Mac Studio M4 Max · Macs

DeepSeek V4 Pro 0813

Doesn't fit

smallest quant needs 640.1 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 V4 Pro 0813 GLM 5.3

Overall

DeepSeek V4 Pro 0813

129.2127–131

GLM 5.3

130.1128–132

Coding

DeepSeek V4 Pro 0813

125.2119–132

GLM 5.3

130.1124–136

Agents

DeepSeek V4 Pro 0813

no data

GLM 5.3

133.4130–137

Math

DeepSeek V4 Pro 0813

128.3126–131

GLM 5.3

128.6126–131

Science

DeepSeek V4 Pro 0813

126.3114–138

GLM 5.3

130.8119–143

Reasoning

DeepSeek V4 Pro 0813

131.1128–134

GLM 5.3

130.1124–136

DeepSeek V4 Pro 0813 · #6 of 100 open models · #6 of 99 that fit ≤1 TB

GLM 5.3 · #4 of 100 open models · #3 of 96 that fit ≤512 GB

Benchmarks

19 shared boards: DeepSeek V4 Pro 0813 leads 9, GLM 5.3 leads 9 · Benchmarks imported Oct 2026

BoardDeepSeek V4 Pro 0813GLM 5.3

GPQA Diamond

DeepSeek V4 Pro 0813

91.7%#3/98 open

IndependentEpoch AI · Aug 2026

GLM 5.3

90.9%#7/98 open

IndependentEpoch AI · Aug 2026

LiveBench Coding

DeepSeek V4 Pro 0813

77.2#7/19 open

IndependentLiveBench · Jun 2026

GLM 5.3

79.0#4/19 open

IndependentLiveBench · Jun 2026

LiveBench Reasoning

DeepSeek V4 Pro 0813

85.8#6/19 open

IndependentLiveBench · Jun 2026

GLM 5.3

85.8#7/19 open

IndependentLiveBench · Jun 2026

AIME 2024/2025

DeepSeek V4 Pro 0813

98.6%#1/86 open

IndependentEpoch AI · Aug 2026

GLM 5.3

91.1%#13/86 open

IndependentEpoch AI · Aug 2026

FrontierMath

DeepSeek V4 Pro 0813

64.6%#5/17 open

IndependentEpoch AI · Aug 2026

GLM 5.3

68.8%#3/17 open

IndependentEpoch AI · Aug 2026

LiveBench Math

DeepSeek V4 Pro 0813

95.1#1/19 open

IndependentLiveBench · Jun 2026

GLM 5.3

87.9#8/19 open

IndependentLiveBench · Jun 2026

SciCode

DeepSeek V4 Pro 0813

51.0%#9/66 open

Lab-reportedEpoch AI · Aug 2026

GLM 5.3

59.0%#3/66 open

Lab-reportedEpoch AI · Aug 2026

SimpleQA

DeepSeek V4 Pro 0813

52.9%#2/17 open

IndependentEpoch AI · Aug 2026

GLM 5.3

41.0%#6/17 open

IndependentEpoch AI · Aug 2026

FrontierMath Tier 4

DeepSeek V4 Pro 0813

26.8%#6/13 open

IndependentEpoch AI · Aug 2026

GLM 5.3

29.3%#4/13 open

IndependentEpoch AI · Aug 2026

WeirdML

DeepSeek V4 Pro 0813

66.2%#4/46 open

IndependentEpoch AI · Aug 2026

GLM 5.3

75.4%#2/46 open

IndependentEpoch AI · Aug 2026

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

FrontierCode

DeepSeek V4 Pro 0813

28.5%#6/12 open

Lab-reportedEpoch AI · Aug 2026

GLM 5.3

40.1%#3/12 open

Lab-reportedEpoch AI · Aug 2026

ALE-Bench

DeepSeek V4 Pro 0813

1403.2#2/43 open

Lab-reportedEpoch AI · Aug 2026

GLM 5.3

1317.4#3/43 open

Lab-reportedEpoch AI · Aug 2026

APEX-Agents

DeepSeek V4 Pro 0813

47.3%#6/16 open

Lab-reportedEpoch AI · Aug 2026

GLM 5.3

56.6%#2/16 open

Lab-reportedEpoch AI · Aug 2026

Chess Puzzles

DeepSeek V4 Pro 0813

46.0%#2/14 open

IndependentEpoch AI · Aug 2026

GLM 5.3

37.0%#4/14 open

IndependentEpoch AI · Aug 2026

CritPt

DeepSeek V4 Pro 0813

18.0%#5/66 open

Lab-reportedEpoch AI · Aug 2026

GLM 5.3

19.1%#4/66 open

Lab-reportedEpoch AI · Aug 2026

DTBench

DeepSeek V4 Pro 0813

93.9%#1/68 open

Lab-reportedEpoch AI · Aug 2026

GLM 5.3

87.7%#11/68 open

Lab-reportedEpoch AI · Aug 2026

LMCA

DeepSeek V4 Pro 0813

45.5%#5/54 open

Lab-reportedEpoch AI · Aug 2026

GLM 5.3

55.5%#1/54 open

Lab-reportedEpoch AI · Aug 2026

Mystery Game Puzzles

DeepSeek V4 Pro 0813

43.0%#2/18 open

IndependentEpoch AI · Aug 2026

GLM 5.3

33.0%#4/18 open

IndependentEpoch AI · Aug 2026

ProofBench

DeepSeek V4 Pro 0813

50.0%#7/26 open

Lab-reportedEpoch AI · Aug 2026

GLM 5.3

49.0%#8/26 open

Lab-reportedEpoch AI · Aug 2026

LMArena Text

DeepSeek V4 Pro 0813

1464.6#9/187 open

ArenaLMArena · Oct 2026

GLM 5.3

1478.5#3/187 open

ArenaLMArena · Oct 2026

LMArena WebDev

DeepSeek V4 Pro 0813

1582.0#11/52 open

ArenaLMArena · Oct 2026

GLM 5.3

1621.1#6/52 open

ArenaLMArena · Oct 2026

Only DeepSeek V4 Pro 0813 (2)

ARC-AGI-261.3%
ARC-AGI90.5%

Only GLM 5.3 (11)

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 V4 Pro 0813GLM 5.3

Q2_K

DeepSeek V4 Pro 0813

702 GB587.3 GB file

32K 702 GB · 128K 704 GB

GLM 5.3

324 GB~320.2 GB file

32K 323 GB · 128K 332 GB

Q3_K_M

DeepSeek V4 Pro 0813

805 GB763.7 GB file

32K 805 GB · 128K 807 GB

GLM 5.3

371 GB~367.3 GB file

32K 370 GB · 128K 379 GB

Q4_0

DeepSeek V4 Pro 0813

826 GB885.3 GB file

32K 826 GB · 128K 827 GB

GLM 5.3

not listed

Q4_K_M

DeepSeek V4 Pro 0813

991 GB~990.3 GB file

32K 991 GB · 128K 992 GB

GLM 5.3

456 GB~452.0 GB file

32K 455 GB · 128K 464 GB

Q5_K_M

DeepSeek V4 Pro 0813

1176 GB~1176.0 GB file

32K 1177 GB · 128K 1178 GB

GLM 5.3

541 GB~536.8 GB file

32K 540 GB · 128K 549 GB

Q6_K

DeepSeek V4 Pro 0813

1362 GB~1361.7 GB file

32K 1362 GB · 128K 1364 GB

GLM 5.3

626 GB~621.5 GB file

32K 625 GB · 128K 634 GB

Q8_0

DeepSeek V4 Pro 0813

1651 GB~1650.5 GB file

32K 1651 GB · 128K 1653 GB

GLM 5.3

758 GB801.4 GB file

32K 757 GB · 128K 765 GB

5 more quants

IQ2_M

DeepSeek V4 Pro 0813

not listed

GLM 5.3

258 GB238.6 GB file

32K 257 GB · 128K 266 GB

IQ3_XXS

DeepSeek V4 Pro 0813

640 GB619.5 GB file

32K 640 GB · 128K 642 GB

GLM 5.3

296 GB281.7 GB file

32K 295 GB · 128K 304 GB

IQ4_XS

DeepSeek V4 Pro 0813

not listed

GLM 5.3

409 GB365.3 GB file

32K 408 GB · 128K 417 GB

Q4_1

DeepSeek V4 Pro 0813

929 GB983.6 GB file

32K 929 GB · 128K 930 GB

GLM 5.3

not listed

BF16

DeepSeek V4 Pro 0813

3301 GB~3301.0 GB file

32K 3302 GB · 128K 3303 GB

GLM 5.3

1511 GB1508.0 GB file

32K 1510 GB · 128K 1519 GB

How to run each

DeepSeek V4 Pro 0813

Ollama · Q4_K_M

$ollama run hf.co/unsloth/DeepSeek-V4-Pro-0813-GGUF

All ways to run DeepSeek V4 Pro 0813 →

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 V4 Pro 0813 and GLM 5.3
Spec	DeepSeek V4 Pro 0813	GLM 5.3
Publisher	DeepSeek	Z.ai
Parameters	1650.5B	753.3B
Active parameters	102B per token	42B per token
Architecture	DeepseekV4ForCausalLM	GlmMoeDsaForCausalLM
Context	1M tokens	1M tokens
Modalities	Chat	Chat, Function-calling
License	MIT	Other
Released	Aug 2026	Aug 2026

Frequently Asked Questions

Which is better, DeepSeek V4 Pro 0813 or GLM 5.3?

DeepSeek V4 Pro 0813 and GLM 5.3 match in llmrun Score, with values of 129.2 versus 130.1; neither fits 24 GB. Choose DeepSeek V4 Pro 0813 for more permissive license; choose GLM 5.3 for lighter on memory and also does function-calling.

Which needs less VRAM, DeepSeek V4 Pro 0813 or GLM 5.3?

At Q4_K_M, DeepSeek V4 Pro 0813 requires 990.6 GB while GLM 5.3 needs 456.2 GB, making GLM 5.3 the easier model to run on your local setup.

Can I run DeepSeek V4 Pro 0813 or GLM 5.3 on a 16 GB GPU?

DeepSeek V4 Pro 0813 does not fit (smallest quant needs 640.1 GB); GLM 5.3 does not fit (smallest quant needs 256 GB).

Which has a longer context window, DeepSeek V4 Pro 0813 or GLM 5.3?

DeepSeek V4 Pro 0813 supports 1,048,576 tokens and GLM 5.3 supports 1,048,576 tokens.