DeepSeek v3 0324 vs GLM 5.3
GLM 5.3 leads llmrun Score 130.1 to 93.9; neither fits 24 GB.
Model A · DeepSeek
DeepSeek v3 0324684.5B · 40.1B active · 160K context · MIT · Mar 2025
Model B · Z.ai
GLM 5.3753.3B · 41.8B active · 1M context · Other · Aug 2026
Choose DeepSeek v3 0324 if you want…
More permissive license
MIT vs Other
Choose GLM 5.3 if you want…
Higher llmrun Score
130.1 vs 93.9
Stronger at reasoning
130.1 vs 87.8
Stronger at science
130.6 vs 97.9
Ahead on the benchmarks
7 of 7 shared boards
Longer context window
1M vs 160K tokens
Newer release
Aug 2026 vs Mar 2025
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 0324
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 0324
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 0324
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 0324
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 0324
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 0324
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 0324
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 0324
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 0324
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).
Overall
DeepSeek v3 0324
GLM 5.3
Coding
DeepSeek v3 0324
GLM 5.3
Agents
DeepSeek v3 0324
no data
GLM 5.3
Math
DeepSeek v3 0324
no data
GLM 5.3
Science
DeepSeek v3 0324
GLM 5.3
Reasoning
DeepSeek v3 0324
GLM 5.3
DeepSeek v3 0324 · #72 of 106 open models · #68 of 102 that fit ≤512 GB
GLM 5.3 · #6 of 106 open models · #4 of 102 that fit ≤512 GB
DeepSeek v3 0324
67.6%#37/100 open
IndependentEpoch AI · Mar 2025
GLM 5.3
90.9%#8/100 open
IndependentEpoch AI · Aug 2026
DeepSeek v3 0324
37.8%#50/88 open
IndependentEpoch AI · Mar 2025
GLM 5.3
91.1%#15/88 open
IndependentEpoch AI · Aug 2026
DeepSeek v3 0324
39.0%#39/72 open
Lab-reportedEpoch AI · Mar 2025
GLM 5.3
59.0%#4/72 open
Lab-reportedEpoch AI · Aug 2026
DeepSeek v3 0324
36.1%#34/47 open
IndependentEpoch AI · Mar 2025
GLM 5.3
75.4%#2/47 open
IndependentEpoch AI · Aug 2026
DeepSeek v3 0324
0.0%#55/84 open
Lab-reportedEpoch AI · Mar 2025
GLM 5.3
19.1%#7/84 open
Lab-reportedEpoch AI · Aug 2026
DeepSeek v3 0324
64.8%#40/70 open
Lab-reportedEpoch AI · Mar 2025
GLM 5.3
87.7%#12/70 open
Lab-reportedEpoch AI · Aug 2026
DeepSeek v3 0324
15.5%#43/56 open
Lab-reportedEpoch AI · Mar 2025
GLM 5.3
55.5%#1/56 open
Lab-reportedEpoch AI · Aug 2026
32 more boards (other shared and single-model boards)
DeepSeek v3 0324
1395.2#53/188 open
ArenaLMArena · Oct 2026
GLM 5.3
1480.6#2/188 open
ArenaLMArena · Oct 2026
Only DeepSeek v3 0324 (7)
- SWE-bench Verified42.0%
- MMLU-Pro81.3%
- Aider Polyglot55.1%
- SimpleBench27.2%
- MATH Level 575.5%
- Fiction.LiveBench50.0%
- METR Time Horizons49.6%
Only GLM 5.3 (24)
- LiveBench Coding79.0
- LiveBench Reasoning85.8
- FrontierMath68.8%
- LMArena WebDev1622.8
- LiveBench Math87.9
- SimpleQA41.0%
- FrontierMath Tier 429.3%
- DeepSWE69.0%
- FrontierCode40.1%
- APEX-Agents56.6%
- Chess Puzzles37.0%
- LiveBench 2026 Reasoning85.8
- Mystery Game Puzzles33.0%
- Vending-Bench 28163.6
- LiveBench 2026 Browser0.0
- LiveBench 2026 Data Analysis70.2
- ALE-Bench1317.4
- CursorBench42.6%
- FrontierSWE30.2%
- LiveBench 2026 Coding82.8
- LiveBench 2026 Long-Horizon35.9
- LiveBench 2026 Design77.3
- ProofBench49.0%
- LiveBench 2026 Research73.2
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 0324
295 GB244.0 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_S
DeepSeek v3 0324
303 GB289.1 GB file
32K 302 GB · 128K 309 GB
GLM 5.3
not listed
Q3_K_M
DeepSeek v3 0324
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_0
DeepSeek v3 0324
346 GB379.0 GB file
32K 345 GB · 128K 352 GB
GLM 5.3
not listed
Q4_K_M
DeepSeek v3 0324
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 0324
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 0324
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 0324
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 0324
192 GB218.7 GB file
32K 191 GB · 128K 198 GB
GLM 5.3
not listed
IQ2_S
DeepSeek v3 0324
218 GB197.0 GB file
32K 217 GB · 128K 223 GB
GLM 5.3
not listed
IQ2_M
DeepSeek v3 0324
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 0324
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
Q3_K_L
DeepSeek v3 0324
355 GB347.4 GB file
32K 353 GB · 128K 360 GB
GLM 5.3
not listed
IQ4_XS
DeepSeek v3 0324
372 GB357.1 GB file
32K 371 GB · 128K 377 GB
GLM 5.3
409 GB365.3 GB file
32K 408 GB · 128K 417 GB
IQ4_NL
DeepSeek v3 0324
389 GB378.1 GB file
32K 388 GB · 128K 395 GB
GLM 5.3
not listed
Q4_1
DeepSeek v3 0324
389 GB419.9 GB file
32K 388 GB · 128K 395 GB
GLM 5.3
not listed
Q4_K_S
DeepSeek v3 0324
389 GB380.0 GB file
32K 388 GB · 128K 395 GB
GLM 5.3
not listed
Q5_K_S
DeepSeek v3 0324
475 GB461.8 GB file
32K 473 GB · 128K 480 GB
GLM 5.3
not listed
BF16
DeepSeek v3 0324
1373 GB1342.3 GB file
32K 1372 GB · 128K 1379 GB
GLM 5.3
1511 GB1508.0 GB file
32K 1510 GB · 128K 1519 GB
DeepSeek v3 0324
Ollama · Q4_K_M
ollama run hf.co/unsloth/DeepSeek-V3-0324-GGUF:Q4_K_MGLM 5.3
Ollama · Q4_K_M
ollama run hf.co/unsloth/GLM-5.3-GGUF| Spec | DeepSeek v3 0324 | GLM 5.3 |
|---|---|---|
| Publisher | DeepSeek | Z.ai |
| Parameters | 684.5B | 753.3B |
| Active parameters | 40B per token | 42B per token |
| Architecture | DeepseekV3ForCausalLM | GlmMoeDsaForCausalLM |
| Context | 160K tokens | 1M tokens |
| Modalities | Chat, Function-calling | Chat, Function-calling |
| License | MIT | Other |
| Released | Mar 2025 | Aug 2026 |
Frequently Asked Questions
Which is better, DeepSeek v3 0324 or GLM 5.3?
GLM 5.3 leads llmrun Score 130.1 to 93.9; neither fits 24 GB. Choose DeepSeek v3 0324 for more permissive license; choose GLM 5.3 for higher llmrun Score and stronger at reasoning.
Which needs less VRAM, DeepSeek v3 0324 or GLM 5.3?
At Q4_K_M, DeepSeek v3 0324 requires 414.6 GB while GLM 5.3 needs 456.2 GB, making DeepSeek v3 0324 the easier model to run on your local setup.
Can I run DeepSeek v3 0324 or GLM 5.3 on a 16 GB GPU?
DeepSeek v3 0324 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 0324 or GLM 5.3?
DeepSeek v3 0324 supports 163,840 tokens and GLM 5.3 supports 1,048,576 tokens.