llmrun

DeepSeek v3 vs GLM 5.3

GLM 5.3 leads llmrun Score 130.1 to 89.0; neither fits 24 GB.

Run GLM 5.3 in the cloud →

Model A · DeepSeek

DeepSeek v3
89.0llmrun Score

684.5B · 40.1B active · 160K context · Dec 2024

ChatFunctions

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

ChatFunctions

Which should you choose?

Choose GLM 5.3 if you want…

  • Higher llmrun Score

    130.1 vs 89.0

  • Stronger at reasoning

    130.1 vs 86.9

  • Stronger at science

    130.6 vs 89.5

  • Ahead on the benchmarks

    4 of 4 shared boards

  • Longer context window

    1M vs 160K tokens

  • Newer release

    Aug 2026 vs Dec 2024

DeepSeek v3: no clear edge over GLM 5.3 in the data we have.

On your hardware

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

8 GB

RTX 4060 · 8 GB tier

DeepSeek v3

Doesn't fit

smallest quant needs 189.7 GB

GLM 5.3

Doesn't fit

smallest quant needs 256 GB

12 GB

RTX 3060 12GB · 12 GB tier

DeepSeek v3

Doesn't fit

smallest quant needs 189.7 GB

GLM 5.3

Doesn't fit

smallest quant needs 256 GB

16 GB

RTX 5060 Ti 16GB · 16 GB tier

DeepSeek v3

Doesn't fit

smallest quant needs 189.7 GB

GLM 5.3

Doesn't fit

smallest quant needs 256 GB

24 GBreference

RTX 4090 · 24 GB tier

DeepSeek v3

Doesn't fit

smallest quant needs 189.7 GB

GLM 5.3

Doesn't fit

smallest quant needs 256 GB

32 GB

RTX 5090 · 32 GB tier

DeepSeek v3

Doesn't fit

smallest quant needs 189.7 GB

GLM 5.3

Doesn't fit

smallest quant needs 256 GB

48 GB

RTX A6000 · 48 GB tier

DeepSeek v3

Doesn't fit

smallest quant needs 189.7 GB

GLM 5.3

Doesn't fit

smallest quant needs 256 GB

Mac 32 GB

Mac Mini M4 · Macs

DeepSeek v3

Doesn't fit

smallest quant needs 189.7 GB

GLM 5.3

Doesn't fit

smallest quant needs 256 GB

Mac 64 GB

Mac Studio M4 Max · Macs

DeepSeek v3

Doesn't fit

smallest quant needs 189.7 GB

GLM 5.3

Doesn't fit

smallest quant needs 256 GB

Mac 128 GB

Mac Studio M4 Max · Macs

DeepSeek v3

Doesn't fit

smallest quant needs 189.7 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

Overall

DeepSeek v3

89.085–93

GLM 5.3

130.1128–132

Coding

DeepSeek v3

96.991–103

GLM 5.3

129.9124–136

Agents

DeepSeek v3

no data

GLM 5.3

133.5130–137

Math

DeepSeek v3

no data

GLM 5.3

128.5126–131

Science

DeepSeek v3

89.582–97

GLM 5.3

130.6118–143

Reasoning

DeepSeek v3

86.972–102

GLM 5.3

130.1124–136

DeepSeek v3 · #76 of 106 open models · #72 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 leads 0, GLM 5.3 leads 4 · Benchmarks imported Nov 2026

DeepSeek v3

56.5%#47/100 open

IndependentEpoch AI · Dec 2024

GLM 5.3

90.9%#8/100 open

IndependentEpoch AI · Aug 2026

DeepSeek v3

15.8%#58/88 open

IndependentEpoch AI · Dec 2024

GLM 5.3

91.1%#15/88 open

IndependentEpoch AI · Aug 2026

DeepSeek v3

35.8%#52/72 open

Lab-reportedEpoch AI · Dec 2024

GLM 5.3

59.0%#4/72 open

Lab-reportedEpoch AI · Aug 2026

DeepSeek v3

0.0%#54/84 open

Lab-reportedEpoch AI · Dec 2024

GLM 5.3

19.1%#7/84 open

Lab-reportedEpoch AI · Aug 2026

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

VRAM by quantization

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

Q2_K

DeepSeek v3

295 GB~290.9 GB file

32K 294 GB · 128K 300 GB

GLM 5.3

324 GB~320.2 GB file

32K 323 GB · 128K 332 GB

Q3_K_M

DeepSeek v3

338 GB319.2 GB file

32K 336 GB · 128K 343 GB

GLM 5.3

371 GB~367.3 GB file

32K 370 GB · 128K 379 GB

Q4_K_M

DeepSeek v3

415 GB404.4 GB file

32K 413 GB · 128K 420 GB

GLM 5.3

456 GB~452.0 GB file

32K 455 GB · 128K 464 GB

Q5_K_M

DeepSeek v3

492 GB475.4 GB file

32K 490 GB · 128K 497 GB

GLM 5.3

541 GB~536.8 GB file

32K 540 GB · 128K 549 GB

Q6_K

DeepSeek v3

569 GB550.8 GB file

32K 567 GB · 128K 574 GB

GLM 5.3

626 GB~621.5 GB file

32K 625 GB · 128K 634 GB

Q8_0

DeepSeek v3

688 GB713.3 GB file

32K 687 GB · 128K 694 GB

GLM 5.3

758 GB801.4 GB file

32K 757 GB · 128K 765 GB

11 more quants

IQ2_XXS

DeepSeek v3

192 GB174.4 GB file

32K 191 GB · 128K 198 GB

GLM 5.3

not listed

IQ2_XS

DeepSeek v3

209 GB195.1 GB file

32K 208 GB · 128K 215 GB

GLM 5.3

not listed

IQ2_S

DeepSeek v3

218 GB197.0 GB file

32K 217 GB · 128K 223 GB

GLM 5.3

not listed

IQ2_M

DeepSeek v3

235 GB217.4 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

269 GB257.9 GB file

32K 268 GB · 128K 275 GB

GLM 5.3

296 GB281.7 GB file

32K 295 GB · 128K 304 GB

IQ3_XS

DeepSeek v3

286 GB272.8 GB file

32K 285 GB · 128K 292 GB

GLM 5.3

not listed

IQ3_S

DeepSeek v3

295 GB289.1 GB file

32K 294 GB · 128K 300 GB

GLM 5.3

not listed

IQ3_M

DeepSeek v3

312 GB292.1 GB file

32K 311 GB · 128K 318 GB

GLM 5.3

not listed

IQ4_XS

DeepSeek v3

not listed

GLM 5.3

409 GB365.3 GB file

32K 408 GB · 128K 417 GB

IQ4_NL

DeepSeek v3

389 GB378.1 GB file

32K 388 GB · 128K 395 GB

GLM 5.3

not listed

BF16

DeepSeek v3

1373 GB1342.3 GB file

32K 1372 GB · 128K 1378 GB

GLM 5.3

1511 GB1508.0 GB file

32K 1510 GB · 128K 1519 GB

How to run each

Specifications

Specifications of DeepSeek v3 and GLM 5.3
SpecDeepSeek v3GLM 5.3
PublisherDeepSeekZ.ai
Parameters684.5B753.3B
Active parameters40B per token42B per token
ArchitectureDeepseekV3ForCausalLMGlmMoeDsaForCausalLM
Context160K tokens1M tokens
ModalitiesChat, Function-callingChat, Function-calling
License—Other
ReleasedDec 2024Aug 2026

Frequently Asked Questions

Which is better, DeepSeek v3 or GLM 5.3?

GLM 5.3 leads llmrun Score 130.1 to 89.0; neither fits 24 GB. Choose GLM 5.3 for higher llmrun Score and stronger at reasoning.

Which needs less VRAM, DeepSeek v3 or GLM 5.3?

At Q4_K_M, DeepSeek v3 requires 414.6 GB while GLM 5.3 needs 456.2 GB, making DeepSeek v3 the easier model to run on your local setup.

Can I run DeepSeek v3 or GLM 5.3 on a 16 GB GPU?

DeepSeek v3 does not fit (smallest quant needs 189.7 GB); GLM 5.3 does not fit (smallest quant needs 256 GB).

Which has a longer context window, DeepSeek v3 or GLM 5.3?

DeepSeek v3 supports 163,840 tokens and GLM 5.3 supports 1,048,576 tokens.

DeepSeek v3 vs GLM 5.3 — VRAM & GPU Comparison | llmrun