DeepSeek V4.1 Flash 1017 vs Llama 3.1 405B Instruct
DeepSeek V4.1 Flash 1017 leads llmrun Score 134.4 to 83.5; 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 · Meta
Llama 3.1 405B Instruct405.9B · Llama 3.1 Community · Jul 2024
Choose DeepSeek V4.1 Flash 1017 if you want…
Higher llmrun Score
134.4 vs 83.5
Stronger at reasoning
137.1 vs 86.4
Stronger at science
134.3 vs 84.6
Ahead on the benchmarks
3 of 3 shared boards
Also does vision
Llama 3.1 405B Instruct doesn't list it
More permissive license
MIT vs Llama 3.1 Community
Choose Llama 3.1 405B Instruct if you want…
Lighter on memory
267.9 vs 458.3 GB at Q4_K_M
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
Llama 3.1 405B Instruct
Doesn't fit
smallest quant needs 197.4 GB
12 GB
RTX 3060 12GB · 12 GB tier
DeepSeek V4.1 Flash 1017
Doesn't fit
smallest quant needs 210.4 GB
Llama 3.1 405B Instruct
Doesn't fit
smallest quant needs 197.4 GB
16 GB
RTX 5060 Ti 16GB · 16 GB tier
DeepSeek V4.1 Flash 1017
Doesn't fit
smallest quant needs 210.4 GB
Llama 3.1 405B Instruct
Doesn't fit
smallest quant needs 197.4 GB
24 GBreference
RTX 4090 · 24 GB tier
DeepSeek V4.1 Flash 1017
Doesn't fit
smallest quant needs 210.4 GB
Llama 3.1 405B Instruct
Doesn't fit
smallest quant needs 197.4 GB
32 GB
RTX 5090 · 32 GB tier
DeepSeek V4.1 Flash 1017
Doesn't fit
smallest quant needs 210.4 GB
Llama 3.1 405B Instruct
Doesn't fit
smallest quant needs 197.4 GB
48 GB
RTX A6000 · 48 GB tier
DeepSeek V4.1 Flash 1017
Doesn't fit
smallest quant needs 210.4 GB
Llama 3.1 405B Instruct
Doesn't fit
smallest quant needs 197.4 GB
Mac 32 GB
Mac Mini M4 · Macs
DeepSeek V4.1 Flash 1017
Doesn't fit
smallest quant needs 210.4 GB
Llama 3.1 405B Instruct
Doesn't fit
smallest quant needs 197.4 GB
Mac 64 GB
Mac Studio M4 Max · Macs
DeepSeek V4.1 Flash 1017
Doesn't fit
smallest quant needs 210.4 GB
Llama 3.1 405B Instruct
Doesn't fit
smallest quant needs 197.4 GB
Mac 128 GB
Mac Studio M4 Max · Macs
DeepSeek V4.1 Flash 1017
Doesn't fit
smallest quant needs 210.4 GB
Llama 3.1 405B Instruct
Doesn't fit
smallest quant needs 197.4 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
Llama 3.1 405B Instruct
Coding
DeepSeek V4.1 Flash 1017
Llama 3.1 405B Instruct
no data
Agents
DeepSeek V4.1 Flash 1017
Llama 3.1 405B Instruct
no data
Math
DeepSeek V4.1 Flash 1017
Llama 3.1 405B Instruct
no data
Science
DeepSeek V4.1 Flash 1017
Llama 3.1 405B Instruct
Reasoning
DeepSeek V4.1 Flash 1017
Llama 3.1 405B Instruct
DeepSeek V4.1 Flash 1017 · #2 of 106 open models · #1 of 102 that fit ≤512 GB
Llama 3.1 405B Instruct · #82 of 106 open models · #78 of 102 that fit ≤512 GB
Benchmarks
3 shared boards: DeepSeek V4.1 Flash 1017 leads 3, Llama 3.1 405B Instruct leads 0 · Benchmarks imported Nov 2026
DeepSeek V4.1 Flash 1017
93.2%#1/100 open
IndependentEpoch AI · Oct 2026
Llama 3.1 405B Instruct
50.9%#55/100 open
IndependentEpoch AI · Jul 2024
DeepSeek V4.1 Flash 1017
99.4%#1/88 open
IndependentEpoch AI · Oct 2026
Llama 3.1 405B Instruct
9.7%#60/88 open
IndependentEpoch AI · Jul 2024
DeepSeek V4.1 Flash 1017
24.0%#3/84 open
Lab-reportedEpoch AI · Oct 2026
Llama 3.1 405B Instruct
0.0%#63/84 open
Lab-reportedEpoch AI · Jul 2024
29 more boards (other shared and single-model boards)
Only DeepSeek V4.1 Flash 1017 (20)
- FrontierMath71.2%
- LMArena WebDev1665.0
- ARC-AGI-278.1%
- SciCode55.9%
- ARC-AGI94.5%
- SimpleQA42.5%
- FrontierMath Tier 446.3%
- APEX-Agents69.8%
- Chess Puzzles46.0%
- LiveBench 2026 Reasoning89.1
- Mystery Game Puzzles49.0%
- LiveBench 2026 Browser76.0
- LiveBench 2026 Data Analysis79.5
- ALE-Bench1622.0
- CursorBench47.7%
- LiveBench 2026 Coding96.0
- LiveBench 2026 Long-Horizon50.9
- LiveBench 2026 Design83.4
- WeirdML v39.2%
- LiveBench 2026 Research79.5
Only Llama 3.1 405B Instruct (9)
- LMArena Text1335.5
- MMLU-Pro73.3%
- SimpleBench23.0%
- MATH Level 549.8%
- MMLU84.5%
- WeirdML21.4%
- DTBench61.4%
- ForecastBench62.6
- WinoGrande82.2%
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 V4.1 Flash 1017
325 GB264.5 GB file
32K 325 GB · 128K 326 GB
Llama 3.1 405B Instruct
190 GB151.2 GB file
32K 206 GB · 128K 259 GB
Q3_K_S
DeepSeek V4.1 Flash 1017
not listed
Llama 3.1 405B Instruct
195 GB177.1 GB file
32K 212 GB · 128K 265 GB
Q3_K_M
DeepSeek V4.1 Flash 1017
372 GB347.3 GB file
32K 373 GB · 128K 374 GB
Llama 3.1 405B Instruct
218 GB~197.8 GB file
32K 234 GB · 128K 287 GB
Q4_K_M
DeepSeek V4.1 Flash 1017
458 GB444.7 GB file
32K 459 GB · 128K 460 GB
Llama 3.1 405B Instruct
268 GB~243.5 GB file
32K 284 GB · 128K 337 GB
Q5_K_M
DeepSeek V4.1 Flash 1017
544 GB~543.8 GB file
32K 545 GB · 128K 546 GB
Llama 3.1 405B Instruct
318 GB~289.2 GB file
32K 335 GB · 128K 387 GB
Q6_K
DeepSeek V4.1 Flash 1017
630 GB~629.6 GB file
32K 630 GB · 128K 632 GB
Llama 3.1 405B Instruct
368 GB~334.8 GB file
32K 385 GB · 128K 438 GB
Q8_0
DeepSeek V4.1 Flash 1017
764 GB~763.2 GB file
32K 764 GB · 128K 765 GB
Llama 3.1 405B Instruct
446 GB~405.9 GB file
32K 463 GB · 128K 516 GB
5 more quants
IQ2_XXS
DeepSeek V4.1 Flash 1017
210 GB300.5 GB file
32K 211 GB · 128K 212 GB
Llama 3.1 405B Instruct
not listed
IQ2_XS
DeepSeek V4.1 Flash 1017
229 GB~229.0 GB file
32K 230 GB · 128K 231 GB
Llama 3.1 405B Instruct
not listed
IQ3_XXS
DeepSeek V4.1 Flash 1017
296 GB394.7 GB file
32K 296 GB · 128K 298 GB
Llama 3.1 405B Instruct
not listed
IQ3_S
DeepSeek V4.1 Flash 1017
325 GB423.6 GB file
32K 325 GB · 128K 326 GB
Llama 3.1 405B Instruct
not listed
BF16
DeepSeek V4.1 Flash 1017
1527 GB~1526.4 GB file
32K 1527 GB · 128K 1528 GB
Llama 3.1 405B Instruct
893 GB~811.7 GB file
32K 909 GB · 128K 962 GB
DeepSeek V4.1 Flash 1017
Ollama · Q4_K_M
ollama run hf.co/mrfakename/DeepSeek-V4.1-Flash-1017-GGUF:Q4_K_MLlama 3.1 405B Instruct
Ollama · Q4_K_M
ollama run hf.co/MaziyarPanahi/Meta-Llama-3.1-405B-Instruct-GGUF| Spec | DeepSeek V4.1 Flash 1017 | Llama 3.1 405B Instruct |
|---|---|---|
| Publisher | DeepSeek | Meta |
| Parameters | 763.2B | 405.9B |
| Active parameters | 16B per token | — |
| Architecture | DeepseekV41ForCausalLM | — |
| Context | 1M tokens | — |
| Modalities | Vision | Chat, Function-calling |
| License | MIT | Llama 3.1 Community |
| Released | Oct 2026 | Jul 2024 |
Frequently Asked Questions
Which is better, DeepSeek V4.1 Flash 1017 or Llama 3.1 405B Instruct?
DeepSeek V4.1 Flash 1017 leads llmrun Score 134.4 to 83.5; neither fits 24 GB. Choose DeepSeek V4.1 Flash 1017 for higher llmrun Score and stronger at reasoning; choose Llama 3.1 405B Instruct for lighter on memory and also does chat, function-calling.
Which needs less VRAM, DeepSeek V4.1 Flash 1017 or Llama 3.1 405B Instruct?
At Q4_K_M, DeepSeek V4.1 Flash 1017 requires 458.3 GB while Llama 3.1 405B Instruct needs 267.9 GB, making Llama 3.1 405B Instruct the easier model to run on your local setup.
Can I run DeepSeek V4.1 Flash 1017 or Llama 3.1 405B Instruct on a 16 GB GPU?
DeepSeek V4.1 Flash 1017 does not fit (smallest quant needs 210.4 GB); Llama 3.1 405B Instruct does not fit (smallest quant needs 197.4 GB).