DeepSeek V3.1 Terminus vs Qwen3.8 27B
Qwen3.8 27B leads llmrun Score 121.5 to 107.7; only Qwen3.8 27B fits 24 GB (Q4_K_M); DeepSeek V3.1 Terminus needs 189.7 GB even at its smallest quant.
Model A · DeepSeek
DeepSeek V3.1 Terminus684.5B · 40.1B active · 160K context · MIT · Sep 2025
Model B · Alibaba
Qwen3.8 27B27.8B · 256K context · Apache 2.0 · Aug 2026
Choose DeepSeek V3.1 Terminus if you want…
Also does chat
Qwen3.8 27B doesn't list it
Choose Qwen3.8 27B if you want…
Higher llmrun Score
121.5 vs 107.7
Stronger at reasoning
124.1 vs 107.6
Stronger at science
112.0 vs 102.8
Ahead on the benchmarks
5 of 5 shared boards
Fits a 12 GB GPU
IQ3_XXS · 12 GB; DeepSeek V3.1 Terminus needs 189.7 GB at its smallest quant
Fits a Mac 32 GB
Q4_K_M · 17.9 GB; DeepSeek V3.1 Terminus needs 189.7 GB at its smallest quant
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 V3.1 Terminus
Doesn't fit
smallest quant needs 189.7 GB
Qwen3.8 27B
Doesn't fit
smallest quant needs 8.8 GB
12 GB
RTX 3060 12GB · 12 GB tier
DeepSeek V3.1 Terminus
Doesn't fit
smallest quant needs 189.7 GB
Qwen3.8 27B
IQ3_XXS · ~20 tok/s
12 GB · up to 16Kfits
16 GB
RTX 5060 Ti 16GB · 16 GB tier
DeepSeek V3.1 Terminus
Doesn't fit
smallest quant needs 189.7 GB
Qwen3.8 27B
Q3_K_L · ~19 tok/s
15.4 GB · up to 16Kfits
24 GBreference
RTX 4090 · 24 GB tier
DeepSeek V3.1 Terminus
Doesn't fit
smallest quant needs 189.7 GB
Qwen3.8 27B
Q4_K_M · ~38 tok/s
17.9 GB · up to 64Kfits
32 GB
RTX 5090 · 32 GB tier
DeepSeek V3.1 Terminus
Doesn't fit
smallest quant needs 189.7 GB
Qwen3.8 27B
Q4_K_M · ~67 tok/s
17.9 GB · up to 256Kfits
48 GB
RTX A6000 · 48 GB tier
DeepSeek V3.1 Terminus
Doesn't fit
smallest quant needs 189.7 GB
Qwen3.8 27B
Q4_K_M · ~29 tok/s
17.9 GB · up to 256Kfits
Mac 32 GB
Mac Mini M4 · Macs
DeepSeek V3.1 Terminus
Doesn't fit
smallest quant needs 189.7 GB
Qwen3.8 27B
Q4_K_M · ~5 tok/s
17.9 GB · up to 128Kfits
Mac 64 GB
Mac Studio M4 Max · Macs
DeepSeek V3.1 Terminus
Doesn't fit
smallest quant needs 189.7 GB
Qwen3.8 27B
Q4_K_M · ~22 tok/s
17.9 GB · up to 256Kfits
Mac 128 GB
Mac Studio M4 Max · Macs
DeepSeek V3.1 Terminus
Doesn't fit
smallest quant needs 189.7 GB
Qwen3.8 27B
Q4_K_M · ~22 tok/s
17.9 GB · up to 256Kfits
Reference GPU: RTX 4090. Tinted cell = the better pick on that machine (fits, more headroom, or at least 10% faster).
Overall
DeepSeek V3.1 Terminus
Qwen3.8 27B
Coding
DeepSeek V3.1 Terminus
Qwen3.8 27B
Math
DeepSeek V3.1 Terminus
no data
Qwen3.8 27B
Science
DeepSeek V3.1 Terminus
Qwen3.8 27B
Reasoning
DeepSeek V3.1 Terminus
Qwen3.8 27B
DeepSeek V3.1 Terminus · #32 of 92 open models · #29 of 88 that fit ≤512 GB
Qwen3.8 27B · #10 of 92 open models · #1 of 34 that fit 24 GB
Benchmarks
5 shared boards: DeepSeek V3.1 Terminus leads 0, Qwen3.8 27B leads 5 · Benchmarks imported Oct 2026
DeepSeek V3.1 Terminus
1416.0#38/186 open
ArenaLMArena · Oct 2026
Qwen3.8 27B
1438.1#22/186 open
ArenaLMArena · Oct 2026
DeepSeek V3.1 Terminus
40.6%#28/65 open
Lab-reportedEpoch AI · Sep 2025
Qwen3.8 27B
46.6%#19/65 open
Lab-reportedEpoch AI · Aug 2026
DeepSeek V3.1 Terminus
1.7%#27/65 open
Lab-reportedEpoch AI · Sep 2025
Qwen3.8 27B
5.4%#15/65 open
Lab-reportedEpoch AI · Aug 2026
DeepSeek V3.1 Terminus
81.3%#21/68 open
Lab-reportedEpoch AI · Sep 2025
Qwen3.8 27B
88.0%#9/68 open
Lab-reportedEpoch AI · Aug 2026
DeepSeek V3.1 Terminus
28.6%#26/54 open
Lab-reportedEpoch AI · Sep 2025
Qwen3.8 27B
41.4%#7/54 open
Lab-reportedEpoch AI · Aug 2026
10 more boards (other shared and single-model boards)
Only DeepSeek V3.1 Terminus (1)
- ALE-Bench745.2
Only Qwen3.8 27B (9)
- LiveBench Coding75.7
- LiveBench Reasoning80.0
- LMArena WebDev1592.8
- LiveBench Math86.2
- ARC-AGI-242.4%
- ARC-AGI87.5%
- APEX-Agents47.5%
- Surface Evolver Bench45.0%
- ProofBench16.0%
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 V3.1 Terminus
295 GB245.7 GB file
32K 294 GB · 128K 300 GB
Qwen3.8 27B
12.6 GB10.8 GB file
32K 13.9 GB · 128K 19.3 GB
Q3_K_S
DeepSeek V3.1 Terminus
303 GB290.4 GB file
32K 302 GB · 128K 309 GB
Qwen3.8 27B
12.9 GB12.7 GB file
32K 14.2 GB · 128K 19.6 GB
Q3_K_M
DeepSeek V3.1 Terminus
338 GB320.5 GB file
32K 336 GB · 128K 343 GB
Qwen3.8 27B
14.3 GB13.4 GB file
32K 15.6 GB · 128K 21.0 GB
Q4_0
DeepSeek V3.1 Terminus
346 GB380.1 GB file
32K 345 GB · 128K 352 GB
Qwen3.8 27B
14.6 GB~13.9 GB file
32K 16.0 GB · 128K 21.4 GB
Q4_K_M
DeepSeek V3.1 Terminus
415 GB405.4 GB file
32K 413 GB · 128K 420 GB
Qwen3.8 27B
17.4 GB16.5 GB file
32K 18.8 GB · 128K 24.1 GB
Q5_K_M
DeepSeek V3.1 Terminus
492 GB476.2 GB file
32K 490 GB · 128K 497 GB
Qwen3.8 27B
20.5 GB19.8 GB file
32K 21.9 GB · 128K 27.3 GB
Q6_K
DeepSeek V3.1 Terminus
569 GB551.3 GB file
32K 567 GB · 128K 574 GB
Qwen3.8 27B
23.7 GB22.0 GB file
32K 25.0 GB · 128K 30.4 GB
Q8_0
DeepSeek V3.1 Terminus
688 GB713.3 GB file
32K 687 GB · 128K 694 GB
Qwen3.8 27B
28.5 GB29.0 GB file
32K 29.9 GB · 128K 35.2 GB
17 more quants
IQ2_XXS
DeepSeek V3.1 Terminus
192 GB217.1 GB file
32K 191 GB · 128K 198 GB
Qwen3.8 27B
8.4 GB7.3 GB file
32K 9.7 GB · 128K 15.1 GB
IQ2_XS
DeepSeek V3.1 Terminus
209 GB188.4 GB file
32K 208 GB · 128K 215 GB
Qwen3.8 27B
9.1 GB9.1 GB file
32K 10.4 GB · 128K 15.8 GB
IQ2_S
DeepSeek V3.1 Terminus
218 GB189.6 GB file
32K 217 GB · 128K 223 GB
Qwen3.8 27B
9.4 GB8.4 GB file
32K 10.8 GB · 128K 16.1 GB
IQ2_M
DeepSeek V3.1 Terminus
235 GB228.9 GB file
32K 234 GB · 128K 241 GB
Qwen3.8 27B
10.1 GB10.5 GB file
32K 11.5 GB · 128K 16.8 GB
IQ3_XXS
DeepSeek V3.1 Terminus
269 GB273.5 GB file
32K 268 GB · 128K 275 GB
Qwen3.8 27B
11.5 GB10.9 GB file
32K 12.9 GB · 128K 18.2 GB
IQ3_XS
DeepSeek V3.1 Terminus
286 GB277.1 GB file
32K 285 GB · 128K 292 GB
Qwen3.8 27B
12.2 GB10.4 GB file
32K 13.6 GB · 128K 18.9 GB
IQ3_S
DeepSeek V3.1 Terminus
not listed
Qwen3.8 27B
12.6 GB12.0 GB file
32K 13.9 GB · 128K 19.3 GB
IQ3_M
DeepSeek V3.1 Terminus
312 GB307.9 GB file
32K 311 GB · 128K 318 GB
Qwen3.8 27B
13.3 GB14.9 GB file
32K 14.6 GB · 128K 20.0 GB
Q3_K_L
DeepSeek V3.1 Terminus
355 GB319.7 GB file
32K 353 GB · 128K 360 GB
Qwen3.8 27B
15.0 GB14.1 GB file
32K 16.3 GB · 128K 21.7 GB
IQ4_XS
DeepSeek V3.1 Terminus
372 GB358.3 GB file
32K 371 GB · 128K 377 GB
Qwen3.8 27B
15.7 GB14.3 GB file
32K 17.0 GB · 128K 22.4 GB
IQ4_NL
DeepSeek V3.1 Terminus
389 GB379.1 GB file
32K 388 GB · 128K 395 GB
Qwen3.8 27B
16.4 GB17.4 GB file
32K 17.7 GB · 128K 23.1 GB
Q4_1
DeepSeek V3.1 Terminus
389 GB420.8 GB file
32K 388 GB · 128K 395 GB
Qwen3.8 27B
16.4 GB17.5 GB file
32K 17.7 GB · 128K 23.1 GB
Q4_K_S
DeepSeek V3.1 Terminus
389 GB381.1 GB file
32K 388 GB · 128K 395 GB
Qwen3.8 27B
16.4 GB15.4 GB file
32K 17.7 GB · 128K 23.1 GB
Q4_K_L
DeepSeek V3.1 Terminus
not listed
Qwen3.8 27B
17.8 GB18.8 GB file
32K 19.1 GB · 128K 24.5 GB
Q5_K_S
DeepSeek V3.1 Terminus
475 GB462.6 GB file
32K 473 GB · 128K 480 GB
Qwen3.8 27B
19.9 GB18.7 GB file
32K 21.2 GB · 128K 26.6 GB
Q5_K_L
DeepSeek V3.1 Terminus
not listed
Qwen3.8 27B
20.9 GB21.5 GB file
32K 22.2 GB · 128K 27.6 GB
BF16
DeepSeek V3.1 Terminus
1373 GB1342.3 GB file
32K 1372 GB · 128K 1379 GB
Qwen3.8 27B
56.3 GB54.7 GB file
32K 57.7 GB · 128K 63.0 GB
DeepSeek V3.1 Terminus
Ollama · Q4_K_M
ollama run hf.co/unsloth/DeepSeek-V3.1-Terminus-GGUF:Q4_K_MQwen3.8 27B
Ollama · Q4_K_M
ollama run hf.co/unsloth/Qwen3.8-27B-GGUF:Q4_K_M| Spec | DeepSeek V3.1 Terminus | Qwen3.8 27B |
|---|---|---|
| Publisher | DeepSeek | Alibaba |
| Parameters | 684.5B | 27.8B |
| Active parameters | 40B per token | — |
| Architecture | DeepseekV3ForCausalLM | Qwen3_5ForConditionalGeneration |
| Context | 160K tokens | 256K tokens |
| Modalities | Chat, Function-calling | Vision, Function-calling |
| License | MIT | Apache 2.0 |
| Released | Sep 2025 | Aug 2026 |
Frequently Asked Questions
Which is better, DeepSeek V3.1 Terminus or Qwen3.8 27B?
Qwen3.8 27B leads llmrun Score 121.5 to 107.7; only Qwen3.8 27B fits 24 GB (Q4_K_M); DeepSeek V3.1 Terminus needs 189.7 GB even at its smallest quant. Choose DeepSeek V3.1 Terminus for also does chat; choose Qwen3.8 27B for higher llmrun Score and stronger at reasoning.
Which needs less VRAM, DeepSeek V3.1 Terminus or Qwen3.8 27B?
At Q4_K_M, DeepSeek V3.1 Terminus requires 414.6 GB while Qwen3.8 27B needs 17.4 GB, making Qwen3.8 27B the easier model to run on your local setup.
Can I run DeepSeek V3.1 Terminus or Qwen3.8 27B on a 16 GB GPU?
DeepSeek V3.1 Terminus does not fit (smallest quant needs 189.7 GB); Qwen3.8 27B fits at Q3_K_L.
Which has a longer context window, DeepSeek V3.1 Terminus or Qwen3.8 27B?
DeepSeek V3.1 Terminus supports 163,840 tokens and Qwen3.8 27B supports 262,144 tokens.