DeepSeek V4.1 Flash 1017 vs Kimi K2.5
DeepSeek V4.1 Flash 1017 leads llmrun Score 134.4 to 113.9; 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 · Moonshot AI
Kimi K2.51026.9B · 33.3B active · 256K context · Other · Jan 2026
Choose DeepSeek V4.1 Flash 1017 if you want…
Higher llmrun Score
134.4 vs 113.9
Stronger at agents
135.7 vs 110.4
Stronger at coding
135.1 vs 110.4
Ahead on the benchmarks
8 of 8 shared boards
Lighter on memory
458.3 vs 620.0 GB at Q4_K_M
Longer context window
1M vs 256K tokens
Choose Kimi K2.5 if you want…
Also does 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
Kimi K2.5
Doesn't fit
smallest quant needs 283.8 GB
12 GB
RTX 3060 12GB · 12 GB tier
DeepSeek V4.1 Flash 1017
Doesn't fit
smallest quant needs 210.4 GB
Kimi K2.5
Doesn't fit
smallest quant needs 283.8 GB
16 GB
RTX 5060 Ti 16GB · 16 GB tier
DeepSeek V4.1 Flash 1017
Doesn't fit
smallest quant needs 210.4 GB
Kimi K2.5
Doesn't fit
smallest quant needs 283.8 GB
24 GBreference
RTX 4090 · 24 GB tier
DeepSeek V4.1 Flash 1017
Doesn't fit
smallest quant needs 210.4 GB
Kimi K2.5
Doesn't fit
smallest quant needs 283.8 GB
32 GB
RTX 5090 · 32 GB tier
DeepSeek V4.1 Flash 1017
Doesn't fit
smallest quant needs 210.4 GB
Kimi K2.5
Doesn't fit
smallest quant needs 283.8 GB
48 GB
RTX A6000 · 48 GB tier
DeepSeek V4.1 Flash 1017
Doesn't fit
smallest quant needs 210.4 GB
Kimi K2.5
Doesn't fit
smallest quant needs 283.8 GB
Mac 32 GB
Mac Mini M4 · Macs
DeepSeek V4.1 Flash 1017
Doesn't fit
smallest quant needs 210.4 GB
Kimi K2.5
Doesn't fit
smallest quant needs 283.8 GB
Mac 64 GB
Mac Studio M4 Max · Macs
DeepSeek V4.1 Flash 1017
Doesn't fit
smallest quant needs 210.4 GB
Kimi K2.5
Doesn't fit
smallest quant needs 283.8 GB
Mac 128 GB
Mac Studio M4 Max · Macs
DeepSeek V4.1 Flash 1017
Doesn't fit
smallest quant needs 210.4 GB
Kimi K2.5
Doesn't fit
smallest quant needs 283.8 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
Kimi K2.5
Coding
DeepSeek V4.1 Flash 1017
Kimi K2.5
Agents
DeepSeek V4.1 Flash 1017
Kimi K2.5
Math
DeepSeek V4.1 Flash 1017
Kimi K2.5
no data
Science
DeepSeek V4.1 Flash 1017
Kimi K2.5
Reasoning
DeepSeek V4.1 Flash 1017
Kimi K2.5
DeepSeek V4.1 Flash 1017 · #2 of 106 open models · #1 of 102 that fit ≤512 GB
Kimi K2.5 · #25 of 106 open models · #21 of 102 that fit ≤640 GB
Benchmarks
8 shared boards: DeepSeek V4.1 Flash 1017 leads 8, Kimi K2.5 leads 0 · Benchmarks imported Nov 2026
DeepSeek V4.1 Flash 1017
93.2%#1/100 open
IndependentEpoch AI · Oct 2026
Kimi K2.5
87.6%#19/100 open
IndependentEpoch AI · Jan 2026
DeepSeek V4.1 Flash 1017
99.4%#1/88 open
IndependentEpoch AI · Oct 2026
Kimi K2.5
92.2%#13/88 open
IndependentEpoch AI · Jan 2026
DeepSeek V4.1 Flash 1017
78.1%#1/22 open
IndependentEpoch AI · Oct 2026
Kimi K2.5
11.8%#13/22 open
IndependentEpoch AI · Jan 2026
DeepSeek V4.1 Flash 1017
55.9%#7/72 open
Lab-reportedEpoch AI · Oct 2026
Kimi K2.5
49.0%#20/72 open
Lab-reportedEpoch AI · Jan 2026
DeepSeek V4.1 Flash 1017
94.5%#2/22 open
IndependentEpoch AI · Oct 2026
Kimi K2.5
65.3%#13/22 open
IndependentEpoch AI · Jan 2026
DeepSeek V4.1 Flash 1017
42.5%#6/19 open
IndependentEpoch AI · Oct 2026
Kimi K2.5
34.3%#12/19 open
IndependentEpoch AI · Jan 2026
DeepSeek V4.1 Flash 1017
1622.0#2/48 open
Lab-reportedEpoch AI · Oct 2026
Kimi K2.5
821.6#21/48 open
Lab-reportedEpoch AI · Jan 2026
DeepSeek V4.1 Flash 1017
24.0%#3/84 open
Lab-reportedEpoch AI · Oct 2026
Kimi K2.5
3.1%#27/84 open
Lab-reportedEpoch AI · Jan 2026
27 more boards (other shared and single-model boards)
DeepSeek V4.1 Flash 1017
1665.0#1/55 open
ArenaLMArena · Oct 2026
Kimi K2.5
1436.2#24/55 open
ArenaLMArena · Oct 2026
Only DeepSeek V4.1 Flash 1017 (14)
- FrontierMath71.2%
- 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
- CursorBench47.7%
- LiveBench 2026 Coding96.0
- LiveBench 2026 Long-Horizon50.9
- LiveBench 2026 Design83.4
- WeirdML v39.2%
- LiveBench 2026 Research79.5
Only Kimi K2.5 (12)
- SWE-bench Verified70.8%
- LMArena Text1449.7
- Terminal-Bench43.2%
- Humanity's Last Exam24.4%
- MMLU-Pro87.1%
- SWE-bench Multilingual67.3%
- SimpleBench46.8%
- WeirdML45.6%
- CL-bench19.3%
- CL-bench Life13.2%
- Fiction.LiveBench86.1%
- Vending-Bench 21198.5
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
Kimi K2.5
440 GB373.8 GB file
32K 439 GB · 128K 446 GB
Q3_K_S
DeepSeek V4.1 Flash 1017
not listed
Kimi K2.5
453 GB443.2 GB file
32K 452 GB · 128K 459 GB
Q3_K_M
DeepSeek V4.1 Flash 1017
372 GB347.3 GB file
32K 373 GB · 128K 374 GB
Kimi K2.5
504 GB489.8 GB file
32K 503 GB · 128K 510 GB
Q4_0
DeepSeek V4.1 Flash 1017
not listed
Kimi K2.5
517 GB581.2 GB file
32K 516 GB · 128K 523 GB
Q4_K_M
DeepSeek V4.1 Flash 1017
458 GB444.7 GB file
32K 459 GB · 128K 460 GB
Kimi K2.5
620 GB621.2 GB file
32K 619 GB · 128K 626 GB
Q5_K_M
DeepSeek V4.1 Flash 1017
544 GB~543.8 GB file
32K 545 GB · 128K 546 GB
Kimi K2.5
736 GB728.7 GB file
32K 734 GB · 128K 741 GB
Q6_K
DeepSeek V4.1 Flash 1017
630 GB~629.6 GB file
32K 630 GB · 128K 632 GB
Kimi K2.5
851 GB842.9 GB file
32K 850 GB · 128K 857 GB
Q8_0
DeepSeek V4.1 Flash 1017
764 GB~763.2 GB file
32K 764 GB · 128K 765 GB
Kimi K2.5
1031 GB1091.1 GB file
32K 1029 GB · 128K 1036 GB
16 more quants
IQ2_XXS
DeepSeek V4.1 Flash 1017
210 GB300.5 GB file
32K 211 GB · 128K 212 GB
Kimi K2.5
286 GB326.7 GB file
32K 285 GB · 128K 292 GB
IQ2_XS
DeepSeek V4.1 Flash 1017
229 GB~229.0 GB file
32K 230 GB · 128K 231 GB
Kimi K2.5
312 GB283.1 GB file
32K 311 GB · 128K 318 GB
IQ2_S
DeepSeek V4.1 Flash 1017
not listed
Kimi K2.5
325 GB283.8 GB file
32K 324 GB · 128K 330 GB
IQ2_M
DeepSeek V4.1 Flash 1017
not listed
Kimi K2.5
350 GB345.2 GB file
32K 349 GB · 128K 356 GB
IQ3_XXS
DeepSeek V4.1 Flash 1017
296 GB394.7 GB file
32K 296 GB · 128K 298 GB
Kimi K2.5
402 GB414.8 GB file
32K 401 GB · 128K 407 GB
IQ3_XS
DeepSeek V4.1 Flash 1017
not listed
Kimi K2.5
427 GB420.1 GB file
32K 426 GB · 128K 433 GB
IQ3_S
DeepSeek V4.1 Flash 1017
325 GB423.6 GB file
32K 325 GB · 128K 326 GB
Kimi K2.5
440 GB405.3 GB file
32K 439 GB · 128K 446 GB
IQ3_M
DeepSeek V4.1 Flash 1017
not listed
Kimi K2.5
466 GB466.9 GB file
32K 465 GB · 128K 472 GB
Q3_K_L
DeepSeek V4.1 Flash 1017
not listed
Kimi K2.5
530 GB487.5 GB file
32K 529 GB · 128K 536 GB
IQ4_XS
DeepSeek V4.1 Flash 1017
not listed
Kimi K2.5
556 GB547.2 GB file
32K 555 GB · 128K 561 GB
IQ4_NL
DeepSeek V4.1 Flash 1017
not listed
Kimi K2.5
582 GB579.1 GB file
32K 580 GB · 128K 587 GB
Q4_1
DeepSeek V4.1 Flash 1017
not listed
Kimi K2.5
582 GB642.9 GB file
32K 580 GB · 128K 587 GB
Q4_K_S
DeepSeek V4.1 Flash 1017
not listed
Kimi K2.5
582 GB583.3 GB file
32K 580 GB · 128K 587 GB
Q4_K_L
DeepSeek V4.1 Flash 1017
not listed
Kimi K2.5
633 GB581.2 GB file
32K 632 GB · 128K 638 GB
Q5_K_S
DeepSeek V4.1 Flash 1017
not listed
Kimi K2.5
710 GB707.0 GB file
32K 709 GB · 128K 715 GB
BF16
DeepSeek V4.1 Flash 1017
1527 GB~1526.4 GB file
32K 1527 GB · 128K 1528 GB
Kimi K2.5
2058 GB2053.2 GB file
32K 2056 GB · 128K 2063 GB
DeepSeek V4.1 Flash 1017
Ollama · Q4_K_M
ollama run hf.co/mrfakename/DeepSeek-V4.1-Flash-1017-GGUF:Q4_K_MKimi K2.5
Ollama · Q4_K_M
ollama run hf.co/unsloth/Kimi-K2.5-GGUF:Q4_K_M| Spec | DeepSeek V4.1 Flash 1017 | Kimi K2.5 |
|---|---|---|
| Publisher | DeepSeek | Moonshot AI |
| Parameters | 763.2B | 1026.9B |
| Active parameters | 16B per token | 33B per token |
| Architecture | DeepseekV41ForCausalLM | KimiK25ForConditionalGeneration |
| Context | 1M tokens | 256K tokens |
| Modalities | Vision | Vision, Function-calling |
| License | MIT | Other |
| Released | Oct 2026 | Jan 2026 |
Frequently Asked Questions
Which is better, DeepSeek V4.1 Flash 1017 or Kimi K2.5?
DeepSeek V4.1 Flash 1017 leads llmrun Score 134.4 to 113.9; neither fits 24 GB. Choose DeepSeek V4.1 Flash 1017 for higher llmrun Score and stronger at agents; choose Kimi K2.5 for also does function-calling.
Which needs less VRAM, DeepSeek V4.1 Flash 1017 or Kimi K2.5?
At Q4_K_M, DeepSeek V4.1 Flash 1017 requires 458.3 GB while Kimi K2.5 needs 620.0 GB, making DeepSeek V4.1 Flash 1017 the easier model to run on your local setup.
Can I run DeepSeek V4.1 Flash 1017 or Kimi K2.5 on a 16 GB GPU?
DeepSeek V4.1 Flash 1017 does not fit (smallest quant needs 210.4 GB); Kimi K2.5 does not fit (smallest quant needs 283.8 GB).
Which has a longer context window, DeepSeek V4.1 Flash 1017 or Kimi K2.5?
DeepSeek V4.1 Flash 1017 supports 1,048,576 tokens and Kimi K2.5 supports 262,144 tokens.