DeepSeek V3.2 vs GLM 5.3 Flash
GLM 5.3 Flash leads llmrun Score 124.1 to 110.4; neither fits 24 GB.
Run GLM 5.3 Flash in the cloud →
Model A · DeepSeek
DeepSeek V3.2685.4B · 41B active · 160K context · MIT · Dec 2025
Model B · Z.ai
GLM 5.3 Flash321.3B · 18.3B active · 1M context · MIT · Aug 2026
Choose DeepSeek V3.2 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 110.4
Stronger at agents
127.4 vs 108.1
Stronger at reasoning
127.4 vs 112.0
Ahead on the benchmarks
4 of 4 shared boards
Lighter on memory
194.6 vs 415.1 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 V3.2
Doesn't fit
smallest quant needs 189.9 GB
GLM 5.3 Flash
Doesn't fit
smallest quant needs 100.7 GB
12 GB
RTX 3060 12GB · 12 GB tier
DeepSeek V3.2
Doesn't fit
smallest quant needs 189.9 GB
GLM 5.3 Flash
Doesn't fit
smallest quant needs 100.7 GB
16 GB
RTX 5060 Ti 16GB · 16 GB tier
DeepSeek V3.2
Doesn't fit
smallest quant needs 189.9 GB
GLM 5.3 Flash
Doesn't fit
smallest quant needs 100.7 GB
24 GBreference
RTX 4090 · 24 GB tier
DeepSeek V3.2
Doesn't fit
smallest quant needs 189.9 GB
GLM 5.3 Flash
Doesn't fit
smallest quant needs 100.7 GB
32 GB
RTX 5090 · 32 GB tier
DeepSeek V3.2
Doesn't fit
smallest quant needs 189.9 GB
GLM 5.3 Flash
Doesn't fit
smallest quant needs 100.7 GB
48 GB
RTX A6000 · 48 GB tier
DeepSeek V3.2
Doesn't fit
smallest quant needs 189.9 GB
GLM 5.3 Flash
Doesn't fit
smallest quant needs 100.7 GB
Mac 32 GB
Mac Mini M4 · Macs
DeepSeek V3.2
Doesn't fit
smallest quant needs 189.9 GB
GLM 5.3 Flash
Doesn't fit
smallest quant needs 100.7 GB
Mac 64 GB
Mac Studio M4 Max · Macs
DeepSeek V3.2
Doesn't fit
smallest quant needs 189.9 GB
GLM 5.3 Flash
Doesn't fit
smallest quant needs 100.7 GB
Mac 128 GB
Mac Studio M4 Max · Macs
DeepSeek V3.2
Doesn't fit
smallest quant needs 189.9 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 V3.2
GLM 5.3 Flash
Coding
DeepSeek V3.2
no data
GLM 5.3 Flash
Agents
DeepSeek V3.2
GLM 5.3 Flash
Math
DeepSeek V3.2
no data
GLM 5.3 Flash
Science
DeepSeek V3.2
no data
GLM 5.3 Flash
Reasoning
DeepSeek V3.2
GLM 5.3 Flash
DeepSeek V3.2 · #31 of 106 open models · #27 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 V3.2 leads 0, GLM 5.3 Flash leads 4 · Benchmarks imported Nov 2026
DeepSeek V3.2
4.0%#16/22 open
IndependentEpoch AI · Dec 2025
GLM 5.3 Flash
65.8%#3/22 open
IndependentEpoch AI · Aug 2026
DeepSeek V3.2
57.0%#15/22 open
IndependentEpoch AI · Dec 2025
GLM 5.3 Flash
91.0%#4/22 open
IndependentEpoch AI · Aug 2026
DeepSeek V3.2
21.3%#19/20 open
Lab-reportedEpoch AI · Dec 2025
GLM 5.3 Flash
52.8%#4/20 open
Lab-reportedEpoch AI · Aug 2026
DeepSeek V3.2
8.0%#23/31 open
Lab-reportedEpoch AI · Dec 2025
GLM 5.3 Flash
21.0%#14/31 open
Lab-reportedEpoch AI · Aug 2026
37 more boards (other shared and single-model boards)
DeepSeek V3.2
1424.6#31/188 open
ArenaLMArena · Oct 2026
GLM 5.3 Flash
1476.5#4/188 open
ArenaLMArena · Oct 2026
DeepSeek V3.2
1362.5#36/55 open
ArenaLMArena · Oct 2026
GLM 5.3 Flash
1606.6#9/55 open
ArenaLMArena · Oct 2026
Only DeepSeek V3.2 (10)
- SWE-bench Verified70.0%
- Terminal-Bench39.6%
- MMLU-Pro85.0%
- SWE-bench Multilingual59.0%
- SWE-bench Bash Only60.0%
- SWE-bench Lite30.7%
- CL-bench12.4%
- CL-bench Life7.4%
- DTBench85.6%
- LMCA28.8%
Only GLM 5.3 Flash (25)
- GPQA Diamond90.1%
- LiveBench Coding79.0
- LiveBench Reasoning77.6
- AIME 2024/202593.9%
- FrontierMath55.8%
- LiveBench Math81.2
- SciCode51.6%
- FrontierMath Tier 417.1%
- DeepSWE63.4%
- FrontierCode31.8%
- Chess Puzzles21.0%
- CritPt15.4%
- 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
- 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 V3.2
295 GB245.4 GB file
32K 294 GB · 128K 301 GB
GLM 5.3 Flash
138 GB114.2 GB file
32K 161 GB · 128K 234 GB
Q3_K_S
DeepSeek V3.2
304 GB290.4 GB file
32K 302 GB · 128K 309 GB
GLM 5.3 Flash
not listed
Q3_K_M
DeepSeek V3.2
338 GB320.2 GB file
32K 337 GB · 128K 344 GB
GLM 5.3 Flash
158 GB149.1 GB file
32K 181 GB · 128K 254 GB
Q4_0
DeepSeek V3.2
347 GB380.1 GB file
32K 345 GB · 128K 352 GB
GLM 5.3 Flash
not listed
Q4_K_M
DeepSeek V3.2
415 GB405.4 GB file
32K 414 GB · 128K 421 GB
GLM 5.3 Flash
195 GB188.7 GB file
32K 217 GB · 128K 290 GB
Q5_K_M
DeepSeek V3.2
492 GB476.2 GB file
32K 491 GB · 128K 498 GB
GLM 5.3 Flash
231 GB244.7 GB file
32K 253 GB · 128K 326 GB
Q6_K
DeepSeek V3.2
569 GB551.3 GB file
32K 568 GB · 128K 575 GB
GLM 5.3 Flash
267 GB~265.1 GB file
32K 290 GB · 128K 362 GB
Q8_0
DeepSeek V3.2
689 GB713.3 GB file
32K 688 GB · 128K 695 GB
GLM 5.3 Flash
323 GB341.0 GB file
32K 346 GB · 128K 418 GB
13 more quants
IQ2_XXS
DeepSeek V3.2
192 GB217.1 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 V3.2
not listed
GLM 5.3 Flash
98.2 GB92.1 GB file
32K 121 GB · 128K 193 GB
IQ2_S
DeepSeek V3.2
not listed
GLM 5.3 Flash
102 GB113.6 GB file
32K 125 GB · 128K 197 GB
IQ2_M
DeepSeek V3.2
235 GB228.1 GB file
32K 234 GB · 128K 241 GB
GLM 5.3 Flash
not listed
IQ3_XXS
DeepSeek V3.2
269 GB273.1 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 V3.2
not listed
GLM 5.3 Flash
138 GB149.6 GB file
32K 161 GB · 128K 234 GB
IQ3_M
DeepSeek V3.2
not listed
GLM 5.3 Flash
146 GB150.7 GB file
32K 169 GB · 128K 242 GB
IQ4_XS
DeepSeek V3.2
372 GB358.3 GB file
32K 371 GB · 128K 378 GB
GLM 5.3 Flash
175 GB156.8 GB file
32K 197 GB · 128K 270 GB
IQ4_NL
DeepSeek V3.2
389 GB379.1 GB file
32K 388 GB · 128K 395 GB
GLM 5.3 Flash
not listed
Q4_1
DeepSeek V3.2
389 GB420.8 GB file
32K 388 GB · 128K 395 GB
GLM 5.3 Flash
not listed
Q4_K_S
DeepSeek V3.2
389 GB381.1 GB file
32K 388 GB · 128K 395 GB
GLM 5.3 Flash
not listed
Q5_K_S
DeepSeek V3.2
475 GB462.6 GB file
32K 474 GB · 128K 481 GB
GLM 5.3 Flash
not listed
BF16
DeepSeek V3.2
1375 GB1342.3 GB file
32K 1373 GB · 128K 1380 GB
GLM 5.3 Flash
644 GB641.6 GB file
32K 667 GB · 128K 740 GB
DeepSeek V3.2
Ollama · Q4_K_M
ollama run hf.co/unsloth/DeepSeek-V3.2-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 V3.2 | GLM 5.3 Flash |
|---|---|---|
| Publisher | DeepSeek | Z.ai |
| Parameters | 685.4B | 321.3B |
| Active parameters | 41B per token | 18B per token |
| Architecture | DeepseekV32ForCausalLM | Glm5NextForConditionalGeneration |
| Context | 160K tokens | 1M tokens |
| Modalities | Chat | Vision, Function-calling |
| License | MIT | MIT |
| Released | Dec 2025 | Aug 2026 |
Frequently Asked Questions
Which is better, DeepSeek V3.2 or GLM 5.3 Flash?
GLM 5.3 Flash leads llmrun Score 124.1 to 110.4; neither fits 24 GB. Choose DeepSeek V3.2 for also does chat; choose GLM 5.3 Flash for higher llmrun Score and stronger at agents.
Which needs less VRAM, DeepSeek V3.2 or GLM 5.3 Flash?
At Q4_K_M, DeepSeek V3.2 requires 415.1 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 V3.2 or GLM 5.3 Flash on a 16 GB GPU?
DeepSeek V3.2 does not fit (smallest quant needs 189.9 GB); GLM 5.3 Flash does not fit (smallest quant needs 100.7 GB).
Which has a longer context window, DeepSeek V3.2 or GLM 5.3 Flash?
DeepSeek V3.2 supports 163,840 tokens and GLM 5.3 Flash supports 1,048,576 tokens.