DeepSeek v3 0324 vs GLM 5.3 Flash
GLM 5.3 Flash leads llmrun Score 124.1 to 93.9; neither fits 24 GB.
Run GLM 5.3 Flash in the cloud →
Model A · DeepSeek
DeepSeek v3 0324684.5B · 40.1B active · 160K context · MIT · Mar 2025
Model B · Z.ai
GLM 5.3 Flash321.3B · 18.3B active · 1M context · MIT · Aug 2026
Choose DeepSeek v3 0324 if you want…
Also does chat
GLM 5.3 Flash doesn't list it
Choose GLM 5.3 Flash if you want…
Higher llmrun Score
124.1 vs 93.9
Stronger at reasoning
127.4 vs 87.8
Stronger at science
123.5 vs 97.9
Ahead on the benchmarks
4 of 4 shared boards
Lighter on memory
194.6 vs 414.6 GB at Q4_K_M
Longer context window
1M vs 160K tokens
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 Flash
Doesn't fit
smallest quant needs 100.7 GB
12 GB
RTX 3060 12GB · 12 GB tier
DeepSeek v3 0324
Doesn't fit
smallest quant needs 189.7 GB
GLM 5.3 Flash
Doesn't fit
smallest quant needs 100.7 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 Flash
Doesn't fit
smallest quant needs 100.7 GB
24 GBreference
RTX 4090 · 24 GB tier
DeepSeek v3 0324
Doesn't fit
smallest quant needs 189.7 GB
GLM 5.3 Flash
Doesn't fit
smallest quant needs 100.7 GB
32 GB
RTX 5090 · 32 GB tier
DeepSeek v3 0324
Doesn't fit
smallest quant needs 189.7 GB
GLM 5.3 Flash
Doesn't fit
smallest quant needs 100.7 GB
48 GB
RTX A6000 · 48 GB tier
DeepSeek v3 0324
Doesn't fit
smallest quant needs 189.7 GB
GLM 5.3 Flash
Doesn't fit
smallest quant needs 100.7 GB
Mac 32 GB
Mac Mini M4 · Macs
DeepSeek v3 0324
Doesn't fit
smallest quant needs 189.7 GB
GLM 5.3 Flash
Doesn't fit
smallest quant needs 100.7 GB
Mac 64 GB
Mac Studio M4 Max · Macs
DeepSeek v3 0324
Doesn't fit
smallest quant needs 189.7 GB
GLM 5.3 Flash
Doesn't fit
smallest quant needs 100.7 GB
Mac 128 GB
Mac Studio M4 Max · Macs
DeepSeek v3 0324
Doesn't fit
smallest quant needs 189.7 GB
GLM 5.3 Flash
IQ2_S · ~41 tok/s
112.8 GB · up to 16Kfits
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 Flash
Coding
DeepSeek v3 0324
GLM 5.3 Flash
Agents
DeepSeek v3 0324
no data
GLM 5.3 Flash
Math
DeepSeek v3 0324
no data
GLM 5.3 Flash
Science
DeepSeek v3 0324
GLM 5.3 Flash
Reasoning
DeepSeek v3 0324
GLM 5.3 Flash
DeepSeek v3 0324 · #72 of 106 open models · #68 of 102 that fit ≤512 GB
GLM 5.3 Flash · #12 of 106 open models · #6 of 89 that fit ≤256 GB
Benchmarks
4 shared boards: DeepSeek v3 0324 leads 0, GLM 5.3 Flash leads 4 · Benchmarks imported Nov 2026
DeepSeek v3 0324
67.6%#37/100 open
IndependentEpoch AI · Mar 2025
GLM 5.3 Flash
90.1%#11/100 open
IndependentEpoch AI · Aug 2026
DeepSeek v3 0324
37.8%#50/88 open
IndependentEpoch AI · Mar 2025
GLM 5.3 Flash
93.9%#11/88 open
IndependentEpoch AI · Aug 2026
DeepSeek v3 0324
39.0%#39/72 open
Lab-reportedEpoch AI · Mar 2025
GLM 5.3 Flash
51.6%#11/72 open
Lab-reportedEpoch AI · Aug 2026
DeepSeek v3 0324
0.0%#55/84 open
Lab-reportedEpoch AI · Mar 2025
GLM 5.3 Flash
15.4%#10/84 open
Lab-reportedEpoch AI · Aug 2026
37 more boards (other shared and single-model boards)
DeepSeek v3 0324
1395.2#53/188 open
ArenaLMArena · Oct 2026
GLM 5.3 Flash
1476.5#4/188 open
ArenaLMArena · Oct 2026
Only DeepSeek v3 0324 (10)
- SWE-bench Verified42.0%
- MMLU-Pro81.3%
- Aider Polyglot55.1%
- SimpleBench27.2%
- MATH Level 575.5%
- WeirdML36.1%
- DTBench64.8%
- Fiction.LiveBench50.0%
- LMCA15.5%
- METR Time Horizons49.6%
Only GLM 5.3 Flash (26)
- LiveBench Coding79.0
- LiveBench Reasoning77.6
- FrontierMath55.8%
- LMArena WebDev1606.6
- LiveBench Math81.2
- ARC-AGI-265.8%
- ARC-AGI91.0%
- FrontierMath Tier 417.1%
- DeepSWE63.4%
- FrontierCode31.8%
- APEX-Agents52.8%
- Chess Puzzles21.0%
- LiveBench 2026 Reasoning77.6
- Mystery Game Puzzles8.0%
- GDP.pdf14.0%
- LiveBench 2026 Browser84.0
- LiveBench 2026 Data Analysis76.4
- ALE-Bench303.6
- CursorBench36.8%
- FrontierSWE18.1%
- LiveBench 2026 Coding80.6
- LiveBench 2026 Long-Horizon28.4
- Surface Evolver Bench52.5%
- LiveBench 2026 Design77.2
- ProofBench21.0%
- LiveBench 2026 Research70.1
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 Flash
138 GB114.2 GB file
32K 161 GB · 128K 234 GB
Q3_K_S
DeepSeek v3 0324
303 GB289.1 GB file
32K 302 GB · 128K 309 GB
GLM 5.3 Flash
not listed
Q3_K_M
DeepSeek v3 0324
338 GB319.2 GB file
32K 336 GB · 128K 343 GB
GLM 5.3 Flash
158 GB149.1 GB file
32K 181 GB · 128K 254 GB
Q4_0
DeepSeek v3 0324
346 GB379.0 GB file
32K 345 GB · 128K 352 GB
GLM 5.3 Flash
not listed
Q4_K_M
DeepSeek v3 0324
415 GB404.4 GB file
32K 413 GB · 128K 420 GB
GLM 5.3 Flash
195 GB188.7 GB file
32K 217 GB · 128K 290 GB
Q5_K_M
DeepSeek v3 0324
492 GB475.4 GB file
32K 490 GB · 128K 497 GB
GLM 5.3 Flash
231 GB244.7 GB file
32K 253 GB · 128K 326 GB
Q6_K
DeepSeek v3 0324
569 GB550.8 GB file
32K 567 GB · 128K 574 GB
GLM 5.3 Flash
267 GB~265.1 GB file
32K 290 GB · 128K 362 GB
Q8_0
DeepSeek v3 0324
688 GB713.3 GB file
32K 687 GB · 128K 694 GB
GLM 5.3 Flash
323 GB341.0 GB file
32K 346 GB · 128K 418 GB
14 more quants
IQ2_XXS
DeepSeek v3 0324
192 GB218.7 GB file
32K 191 GB · 128K 198 GB
GLM 5.3 Flash
90.2 GB101.8 GB file
32K 113 GB · 128K 185 GB
IQ2_XS
DeepSeek v3 0324
not listed
GLM 5.3 Flash
98.2 GB92.1 GB file
32K 121 GB · 128K 193 GB
IQ2_S
DeepSeek v3 0324
218 GB197.0 GB file
32K 217 GB · 128K 223 GB
GLM 5.3 Flash
102 GB113.6 GB file
32K 125 GB · 128K 197 GB
IQ2_M
DeepSeek v3 0324
235 GB217.4 GB file
32K 234 GB · 128K 241 GB
GLM 5.3 Flash
not listed
IQ3_XXS
DeepSeek v3 0324
269 GB257.9 GB file
32K 268 GB · 128K 275 GB
GLM 5.3 Flash
126 GB120.4 GB file
32K 149 GB · 128K 221 GB
IQ3_S
DeepSeek v3 0324
not listed
GLM 5.3 Flash
138 GB149.6 GB file
32K 161 GB · 128K 234 GB
IQ3_M
DeepSeek v3 0324
not listed
GLM 5.3 Flash
146 GB150.7 GB file
32K 169 GB · 128K 242 GB
Q3_K_L
DeepSeek v3 0324
355 GB347.4 GB file
32K 353 GB · 128K 360 GB
GLM 5.3 Flash
not listed
IQ4_XS
DeepSeek v3 0324
372 GB357.1 GB file
32K 371 GB · 128K 377 GB
GLM 5.3 Flash
175 GB156.8 GB file
32K 197 GB · 128K 270 GB
IQ4_NL
DeepSeek v3 0324
389 GB378.1 GB file
32K 388 GB · 128K 395 GB
GLM 5.3 Flash
not listed
Q4_1
DeepSeek v3 0324
389 GB419.9 GB file
32K 388 GB · 128K 395 GB
GLM 5.3 Flash
not listed
Q4_K_S
DeepSeek v3 0324
389 GB380.0 GB file
32K 388 GB · 128K 395 GB
GLM 5.3 Flash
not listed
Q5_K_S
DeepSeek v3 0324
475 GB461.8 GB file
32K 473 GB · 128K 480 GB
GLM 5.3 Flash
not listed
BF16
DeepSeek v3 0324
1373 GB1342.3 GB file
32K 1372 GB · 128K 1379 GB
GLM 5.3 Flash
644 GB641.6 GB file
32K 667 GB · 128K 740 GB
DeepSeek v3 0324
Ollama · Q4_K_M
ollama run hf.co/unsloth/DeepSeek-V3-0324-GGUF:Q4_K_MGLM 5.3 Flash
Ollama · Q4_K_M
ollama run hf.co/batiai/GLM-5.3-Flash-GGUF:Q4_K_M| Spec | DeepSeek v3 0324 | GLM 5.3 Flash |
|---|---|---|
| Publisher | DeepSeek | Z.ai |
| Parameters | 684.5B | 321.3B |
| Active parameters | 40B per token | 18B per token |
| Architecture | DeepseekV3ForCausalLM | Glm5NextForConditionalGeneration |
| Context | 160K tokens | 1M tokens |
| Modalities | Chat, Function-calling | Vision, Function-calling |
| License | MIT | MIT |
| Released | Mar 2025 | Aug 2026 |
Frequently Asked Questions
Which is better, DeepSeek v3 0324 or GLM 5.3 Flash?
GLM 5.3 Flash leads llmrun Score 124.1 to 93.9; neither fits 24 GB. Choose DeepSeek v3 0324 for also does chat; choose GLM 5.3 Flash for higher llmrun Score and stronger at reasoning.
Which needs less VRAM, DeepSeek v3 0324 or GLM 5.3 Flash?
At Q4_K_M, DeepSeek v3 0324 requires 414.6 GB while GLM 5.3 Flash needs 194.6 GB, making GLM 5.3 Flash the easier model to run on your local setup.
Can I run DeepSeek v3 0324 or GLM 5.3 Flash on a 16 GB GPU?
DeepSeek v3 0324 does not fit (smallest quant needs 189.7 GB); GLM 5.3 Flash does not fit (smallest quant needs 100.7 GB).
Which has a longer context window, DeepSeek v3 0324 or GLM 5.3 Flash?
DeepSeek v3 0324 supports 163,840 tokens and GLM 5.3 Flash supports 1,048,576 tokens.