DeepSeek V4.1 Flash 1017 vs GLM 5
DeepSeek V4.1 Flash 1017 leads llmrun Score 134.4 to 111.8; neither fits 24 GB.
Run DeepSeek V4.1 Flash 1017 in the cloud →
Model A · DeepSeek
DeepSeek V4.1 Flash 1017763.2B · 16B active · 1M context · MIT · Oct 2026
Model B · Z.ai
GLM 5753.9B · 42.4B active · 198K context · MIT · Feb 2026
Choose DeepSeek V4.1 Flash 1017 if you want…
Higher llmrun Score
134.4 vs 111.8
Stronger at reasoning
137.1 vs 109.7
Stronger at coding
135.1 vs 110.2
Ahead on the benchmarks
5 of 5 shared boards
Longer context window
1M vs 198K tokens
Also does vision
GLM 5 doesn't list it
Choose GLM 5 if you want…
Also does chat, function-calling
DeepSeek V4.1 Flash 1017 doesn't list it
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 V4.1 Flash 1017
Doesn't fit
smallest quant needs 210.4 GB
GLM 5
Doesn't fit
smallest quant needs 209.1 GB
12 GB
RTX 3060 12GB · 12 GB tier
DeepSeek V4.1 Flash 1017
Doesn't fit
smallest quant needs 210.4 GB
GLM 5
Doesn't fit
smallest quant needs 209.1 GB
16 GB
RTX 5060 Ti 16GB · 16 GB tier
DeepSeek V4.1 Flash 1017
Doesn't fit
smallest quant needs 210.4 GB
GLM 5
Doesn't fit
smallest quant needs 209.1 GB
24 GBreference
RTX 4090 · 24 GB tier
DeepSeek V4.1 Flash 1017
Doesn't fit
smallest quant needs 210.4 GB
GLM 5
Doesn't fit
smallest quant needs 209.1 GB
32 GB
RTX 5090 · 32 GB tier
DeepSeek V4.1 Flash 1017
Doesn't fit
smallest quant needs 210.4 GB
GLM 5
Doesn't fit
smallest quant needs 209.1 GB
48 GB
RTX A6000 · 48 GB tier
DeepSeek V4.1 Flash 1017
Doesn't fit
smallest quant needs 210.4 GB
GLM 5
Doesn't fit
smallest quant needs 209.1 GB
Mac 32 GB
Mac Mini M4 · Macs
DeepSeek V4.1 Flash 1017
Doesn't fit
smallest quant needs 210.4 GB
GLM 5
Doesn't fit
smallest quant needs 209.1 GB
Mac 64 GB
Mac Studio M4 Max · Macs
DeepSeek V4.1 Flash 1017
Doesn't fit
smallest quant needs 210.4 GB
GLM 5
Doesn't fit
smallest quant needs 209.1 GB
Mac 128 GB
Mac Studio M4 Max · Macs
DeepSeek V4.1 Flash 1017
Doesn't fit
smallest quant needs 210.4 GB
GLM 5
Doesn't fit
smallest quant needs 209.1 GB
Reference GPU: RTX 4090. Tinted cell = the better pick on that machine (fits, more headroom, or at least 10% faster).
Overall
DeepSeek V4.1 Flash 1017
GLM 5
Coding
DeepSeek V4.1 Flash 1017
GLM 5
Agents
DeepSeek V4.1 Flash 1017
GLM 5
Math
DeepSeek V4.1 Flash 1017
GLM 5
no data
Science
DeepSeek V4.1 Flash 1017
GLM 5
no data
Reasoning
DeepSeek V4.1 Flash 1017
GLM 5
DeepSeek V4.1 Flash 1017 · #2 of 106 open models · #1 of 102 that fit ≤512 GB
GLM 5 · #29 of 106 open models · #25 of 102 that fit ≤512 GB
Benchmarks
5 shared boards: DeepSeek V4.1 Flash 1017 leads 5, GLM 5 leads 0 · Benchmarks imported Nov 2026
DeepSeek V4.1 Flash 1017
93.2%#1/100 open
IndependentEpoch AI · Oct 2026
GLM 5
87.8%#18/100 open
IndependentEpoch AI · Feb 2026
DeepSeek V4.1 Flash 1017
99.4%#1/88 open
IndependentEpoch AI · Oct 2026
GLM 5
80.0%#27/88 open
IndependentEpoch AI · Feb 2026
DeepSeek V4.1 Flash 1017
78.1%#1/22 open
IndependentEpoch AI · Oct 2026
GLM 5
4.9%#15/22 open
IndependentEpoch AI · Feb 2026
DeepSeek V4.1 Flash 1017
94.5%#2/22 open
IndependentEpoch AI · Oct 2026
GLM 5
44.7%#16/22 open
IndependentEpoch AI · Feb 2026
DeepSeek V4.1 Flash 1017
1622.0#2/48 open
Lab-reportedEpoch AI · Oct 2026
GLM 5
765.6#23/48 open
Lab-reportedEpoch AI · Feb 2026
28 more boards (other shared and single-model boards)
DeepSeek V4.1 Flash 1017
1665.0#1/55 open
ArenaLMArena · Oct 2026
GLM 5
1435.6#26/55 open
ArenaLMArena · Oct 2026
Only DeepSeek V4.1 Flash 1017 (17)
- FrontierMath71.2%
- SciCode55.9%
- SimpleQA42.5%
- FrontierMath Tier 446.3%
- APEX-Agents69.8%
- Chess Puzzles46.0%
- CritPt24.0%
- LiveBench 2026 Reasoning89.1
- Mystery Game Puzzles49.0%
- LiveBench 2026 Browser76.0
- LiveBench 2026 Data Analysis79.5
- CursorBench47.7%
- LiveBench 2026 Coding96.0
- LiveBench 2026 Long-Horizon50.9
- LiveBench 2026 Design83.4
- WeirdML v39.2%
- LiveBench 2026 Research79.5
Only GLM 5 (10)
- SWE-bench Verified72.8%
- LMArena Text1457.2
- Terminal-Bench52.4%
- MMLU-Pro86.0%
- SWE-bench Multilingual69.7%
- SimpleBench53.2%
- WeirdML48.2%
- CL-bench18.7%
- ForecastBench63.7
- Vending-Bench 24432.1
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 V4.1 Flash 1017
325 GB264.5 GB file
32K 325 GB · 128K 326 GB
GLM 5
325 GB276.0 GB file
32K 324 GB · 128K 332 GB
Q3_K_S
DeepSeek V4.1 Flash 1017
not listed
GLM 5
334 GB326.3 GB file
32K 333 GB · 128K 342 GB
Q3_K_M
DeepSeek V4.1 Flash 1017
372 GB347.3 GB file
32K 373 GB · 128K 374 GB
GLM 5
372 GB360.3 GB file
32K 371 GB · 128K 380 GB
Q4_0
DeepSeek V4.1 Flash 1017
not listed
GLM 5
381 GB427.1 GB file
32K 380 GB · 128K 389 GB
Q4_K_M
DeepSeek V4.1 Flash 1017
458 GB444.7 GB file
32K 459 GB · 128K 460 GB
GLM 5
457 GB455.9 GB file
32K 456 GB · 128K 464 GB
Q5_K_M
DeepSeek V4.1 Flash 1017
544 GB~543.8 GB file
32K 545 GB · 128K 546 GB
GLM 5
541 GB535.2 GB file
32K 540 GB · 128K 549 GB
Q6_K
DeepSeek V4.1 Flash 1017
630 GB~629.6 GB file
32K 630 GB · 128K 632 GB
GLM 5
626 GB619.4 GB file
32K 625 GB · 128K 634 GB
Q8_0
DeepSeek V4.1 Flash 1017
764 GB~763.2 GB file
32K 764 GB · 128K 765 GB
GLM 5
758 GB801.3 GB file
32K 757 GB · 128K 766 GB
11 more quants
IQ2_XXS
DeepSeek V4.1 Flash 1017
210 GB300.5 GB file
32K 211 GB · 128K 212 GB
GLM 5
212 GB241.1 GB file
32K 211 GB · 128K 219 GB
IQ2_XS
DeepSeek V4.1 Flash 1017
229 GB~229.0 GB file
32K 230 GB · 128K 231 GB
GLM 5
not listed
IQ2_M
DeepSeek V4.1 Flash 1017
not listed
GLM 5
259 GB254.8 GB file
32K 258 GB · 128K 267 GB
IQ3_XXS
DeepSeek V4.1 Flash 1017
296 GB394.7 GB file
32K 296 GB · 128K 298 GB
GLM 5
296 GB304.5 GB file
32K 295 GB · 128K 304 GB
IQ3_S
DeepSeek V4.1 Flash 1017
325 GB423.6 GB file
32K 325 GB · 128K 326 GB
GLM 5
not listed
IQ4_XS
DeepSeek V4.1 Flash 1017
not listed
GLM 5
409 GB402.9 GB file
32K 408 GB · 128K 417 GB
IQ4_NL
DeepSeek V4.1 Flash 1017
not listed
GLM 5
428 GB425.9 GB file
32K 427 GB · 128K 436 GB
Q4_1
DeepSeek V4.1 Flash 1017
not listed
GLM 5
428 GB472.7 GB file
32K 427 GB · 128K 436 GB
Q4_K_S
DeepSeek V4.1 Flash 1017
not listed
GLM 5
428 GB428.4 GB file
32K 427 GB · 128K 436 GB
Q5_K_S
DeepSeek V4.1 Flash 1017
not listed
GLM 5
523 GB519.7 GB file
32K 522 GB · 128K 530 GB
BF16
DeepSeek V4.1 Flash 1017
1527 GB~1526.4 GB file
32K 1527 GB · 128K 1528 GB
GLM 5
1512 GB1508.0 GB file
32K 1511 GB · 128K 1520 GB
DeepSeek V4.1 Flash 1017
Ollama · Q4_K_M
ollama run hf.co/mrfakename/DeepSeek-V4.1-Flash-1017-GGUF:Q4_K_MGLM 5
Ollama · Q4_K_M
ollama run hf.co/unsloth/GLM-5-GGUF:Q4_K_M| Spec | DeepSeek V4.1 Flash 1017 | GLM 5 |
|---|---|---|
| Publisher | DeepSeek | Z.ai |
| Parameters | 763.2B | 753.9B |
| Active parameters | 16B per token | 42B per token |
| Architecture | DeepseekV41ForCausalLM | GlmMoeDsaForCausalLM |
| Context | 1M tokens | 198K tokens |
| Modalities | Vision | Chat, Function-calling |
| License | MIT | MIT |
| Released | Oct 2026 | Feb 2026 |
Frequently Asked Questions
Which is better, DeepSeek V4.1 Flash 1017 or GLM 5?
DeepSeek V4.1 Flash 1017 leads llmrun Score 134.4 to 111.8; neither fits 24 GB. Choose DeepSeek V4.1 Flash 1017 for higher llmrun Score and stronger at reasoning; choose GLM 5 for also does chat, function-calling.
Which needs less VRAM, DeepSeek V4.1 Flash 1017 or GLM 5?
At Q4_K_M, DeepSeek V4.1 Flash 1017 requires 458.3 GB while GLM 5 needs 456.5 GB, making GLM 5 the easier model to run on your local setup.
Can I run DeepSeek V4.1 Flash 1017 or GLM 5 on a 16 GB GPU?
DeepSeek V4.1 Flash 1017 does not fit (smallest quant needs 210.4 GB); GLM 5 does not fit (smallest quant needs 209.1 GB).
Which has a longer context window, DeepSeek V4.1 Flash 1017 or GLM 5?
DeepSeek V4.1 Flash 1017 supports 1,048,576 tokens and GLM 5 supports 202,752 tokens.