DeepSeek V4.1 Flash vs Kimi K2 Thinking
DeepSeek V4.1 Flash leads llmrun Score 129.5 to 108.6; neither fits 24 GB.
Model A · DeepSeek
DeepSeek V4.1 Flash763.2B · 188B active · 1M context · MIT · Sep 2026
Model B · Moonshot AI
Kimi K2 Thinking1026.4B · 32.9B active · 256K context · Other · Nov 2025
Choose DeepSeek V4.1 Flash if you want…
Higher llmrun Score
129.5 vs 108.6
Stronger at agents
127.9 vs 107.8
Stronger at coding
122.2 vs 103.3
Ahead on the benchmarks
3 of 3 shared boards
Lighter on memory
458.3 vs 619.7 GB at Q4_K_M
Longer context window
1M vs 256K tokens
Choose Kimi K2 Thinking if you want…
Also does chat
DeepSeek V4.1 Flash 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
Doesn't fit
smallest quant needs 210.4 GB
Kimi K2 Thinking
Doesn't fit
smallest quant needs 283.7 GB
12 GB
RTX 3060 12GB · 12 GB tier
DeepSeek V4.1 Flash
Doesn't fit
smallest quant needs 210.4 GB
Kimi K2 Thinking
Doesn't fit
smallest quant needs 283.7 GB
16 GB
RTX 5060 Ti 16GB · 16 GB tier
DeepSeek V4.1 Flash
Doesn't fit
smallest quant needs 210.4 GB
Kimi K2 Thinking
Doesn't fit
smallest quant needs 283.7 GB
24 GBreference
RTX 4090 · 24 GB tier
DeepSeek V4.1 Flash
Doesn't fit
smallest quant needs 210.4 GB
Kimi K2 Thinking
Doesn't fit
smallest quant needs 283.7 GB
32 GB
RTX 5090 · 32 GB tier
DeepSeek V4.1 Flash
Doesn't fit
smallest quant needs 210.4 GB
Kimi K2 Thinking
Doesn't fit
smallest quant needs 283.7 GB
48 GB
RTX A6000 · 48 GB tier
DeepSeek V4.1 Flash
Doesn't fit
smallest quant needs 210.4 GB
Kimi K2 Thinking
Doesn't fit
smallest quant needs 283.7 GB
Mac 32 GB
Mac Mini M4 · Macs
DeepSeek V4.1 Flash
Doesn't fit
smallest quant needs 210.4 GB
Kimi K2 Thinking
Doesn't fit
smallest quant needs 283.7 GB
Mac 64 GB
Mac Studio M4 Max · Macs
DeepSeek V4.1 Flash
Doesn't fit
smallest quant needs 210.4 GB
Kimi K2 Thinking
Doesn't fit
smallest quant needs 283.7 GB
Mac 128 GB
Mac Studio M4 Max · Macs
DeepSeek V4.1 Flash
Doesn't fit
smallest quant needs 210.4 GB
Kimi K2 Thinking
Doesn't fit
smallest quant needs 283.7 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
Kimi K2 Thinking
Coding
DeepSeek V4.1 Flash
Kimi K2 Thinking
Agents
DeepSeek V4.1 Flash
Kimi K2 Thinking
Math
DeepSeek V4.1 Flash
Kimi K2 Thinking
no data
Science
DeepSeek V4.1 Flash
Kimi K2 Thinking
no data
Reasoning
DeepSeek V4.1 Flash
Kimi K2 Thinking
no data
DeepSeek V4.1 Flash · #5 of 100 open models · #4 of 96 that fit ≤512 GB
Kimi K2 Thinking · #31 of 100 open models · #28 of 96 that fit ≤640 GB
Benchmarks
3 shared boards: DeepSeek V4.1 Flash leads 3, Kimi K2 Thinking leads 0 · Benchmarks imported Oct 2026
DeepSeek V4.1 Flash
89.8%#11/98 open
IndependentEpoch AI · Sep 2026
Kimi K2 Thinking
84.2%#22/98 open
IndependentEpoch AI · Nov 2025
DeepSeek V4.1 Flash
98.3%#2/86 open
IndependentEpoch AI · Sep 2026
Kimi K2 Thinking
83.1%#23/86 open
IndependentEpoch AI · Nov 2025
DeepSeek V4.1 Flash
1092.3#8/43 open
Lab-reportedEpoch AI · Sep 2026
Kimi K2 Thinking
597.5#28/43 open
Lab-reportedEpoch AI · Nov 2025
34 more boards (other shared and single-model boards)
DeepSeek V4.1 Flash
1474.6#5/187 open
ArenaLMArena · Oct 2026
Kimi K2 Thinking
1430.1#25/187 open
ArenaLMArena · Oct 2026
DeepSeek V4.1 Flash
1618.4#7/52 open
ArenaLMArena · Oct 2026
Kimi K2 Thinking
1322.1#42/52 open
ArenaLMArena · Oct 2026
Only DeepSeek V4.1 Flash (26)
- LiveBench Coding80.0
- LiveBench Reasoning86.7
- FrontierMath67.4%
- LiveBench Math93.3
- ARC-AGI-272.9%
- SciCode51.8%
- ARC-AGI94.5%
- SimpleQA42.9%
- FrontierMath Tier 426.8%
- FrontierCode43.9%
- APEX-Agents39.5%
- Chess Puzzles48.0%
- CritPt14.3%
- DTBench89.9%
- Furniture Assembly34.2%
- LiveBench 2026 Reasoning86.7
- LMCA47.0%
- Mystery Game Puzzles43.0%
- LiveBench 2026 Browser80.0
- LiveBench 2026 Data Analysis79.3
- LiveBench 2026 Coding85.4
- LiveBench 2026 Long-Horizon43.8
- Surface Evolver Bench46.3%
- LiveBench 2026 Design77.0
- ProofBench54.0%
- LiveBench 2026 Research85.3
Only Kimi K2 Thinking (6)
- SWE-bench Verified63.4%
- Terminal-Bench35.7%
- SWE-bench Bash Only63.4%
- WeirdML42.8%
- CL-bench17.6%
- METR Time Horizons59.2%
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
325 GB264.5 GB file
32K 325 GB · 128K 326 GB
Kimi K2 Thinking
440 GB374.1 GB file
32K 439 GB · 128K 446 GB
Q3_K_S
DeepSeek V4.1 Flash
not listed
Kimi K2 Thinking
453 GB443.2 GB file
32K 452 GB · 128K 459 GB
Q3_K_M
DeepSeek V4.1 Flash
372 GB347.3 GB file
32K 373 GB · 128K 374 GB
Kimi K2 Thinking
504 GB490.0 GB file
32K 503 GB · 128K 510 GB
Q4_0
DeepSeek V4.1 Flash
not listed
Kimi K2 Thinking
517 GB581.2 GB file
32K 516 GB · 128K 523 GB
Q4_K_M
DeepSeek V4.1 Flash
458 GB444.7 GB file
32K 459 GB · 128K 460 GB
Kimi K2 Thinking
620 GB621.2 GB file
32K 618 GB · 128K 625 GB
Q5_K_M
DeepSeek V4.1 Flash
544 GB~543.8 GB file
32K 545 GB · 128K 546 GB
Kimi K2 Thinking
735 GB728.7 GB file
32K 734 GB · 128K 741 GB
Q6_K
DeepSeek V4.1 Flash
630 GB~629.6 GB file
32K 630 GB · 128K 632 GB
Kimi K2 Thinking
851 GB842.9 GB file
32K 849 GB · 128K 856 GB
Q8_0
DeepSeek V4.1 Flash
764 GB508.0 GB file
32K 764 GB · 128K 765 GB
Kimi K2 Thinking
1030 GB1091.1 GB file
32K 1029 GB · 128K 1036 GB
14 more quants
IQ2_XXS
DeepSeek V4.1 Flash
210 GB~209.9 GB file
32K 211 GB · 128K 212 GB
Kimi K2 Thinking
286 GB335.2 GB file
32K 285 GB · 128K 292 GB
IQ2_XS
DeepSeek V4.1 Flash
not listed
Kimi K2 Thinking
312 GB283.4 GB file
32K 311 GB · 128K 317 GB
IQ2_S
DeepSeek V4.1 Flash
not listed
Kimi K2 Thinking
325 GB284.1 GB file
32K 323 GB · 128K 330 GB
IQ2_M
DeepSeek V4.1 Flash
not listed
Kimi K2 Thinking
350 GB353.6 GB file
32K 349 GB · 128K 356 GB
IQ3_XXS
DeepSeek V4.1 Flash
not listed
Kimi K2 Thinking
402 GB421.7 GB file
32K 400 GB · 128K 407 GB
IQ3_XS
DeepSeek V4.1 Flash
315 GB434.0 GB file
32K 316 GB · 128K 317 GB
Kimi K2 Thinking
427 GB420.7 GB file
32K 426 GB · 128K 433 GB
IQ3_M
DeepSeek V4.1 Flash
not listed
Kimi K2 Thinking
466 GB467.5 GB file
32K 464 GB · 128K 471 GB
Q3_K_L
DeepSeek V4.1 Flash
not listed
Kimi K2 Thinking
530 GB487.7 GB file
32K 529 GB · 128K 536 GB
IQ4_XS
DeepSeek V4.1 Flash
not listed
Kimi K2 Thinking
556 GB547.2 GB file
32K 554 GB · 128K 561 GB
IQ4_NL
DeepSeek V4.1 Flash
not listed
Kimi K2 Thinking
581 GB579.1 GB file
32K 580 GB · 128K 587 GB
Q4_1
DeepSeek V4.1 Flash
not listed
Kimi K2 Thinking
581 GB642.9 GB file
32K 580 GB · 128K 587 GB
Q4_K_S
DeepSeek V4.1 Flash
not listed
Kimi K2 Thinking
581 GB583.3 GB file
32K 580 GB · 128K 587 GB
Q5_K_S
DeepSeek V4.1 Flash
not listed
Kimi K2 Thinking
710 GB707.0 GB file
32K 708 GB · 128K 715 GB
BF16
DeepSeek V4.1 Flash
1527 GB~1526.4 GB file
32K 1527 GB · 128K 1528 GB
Kimi K2 Thinking
2057 GB2053.2 GB file
32K 2055 GB · 128K 2062 GB
DeepSeek V4.1 Flash
Ollama · Q4_K_M
ollama run hf.co/vcruz305/DeepSeek-V4.1-Flash-GGUF:Q4_K_MKimi K2 Thinking
Ollama · Q4_K_M
ollama run hf.co/unsloth/Kimi-K2-Thinking-GGUF:Q4_K_M| Spec | DeepSeek V4.1 Flash | Kimi K2 Thinking |
|---|---|---|
| Publisher | DeepSeek | Moonshot AI |
| Parameters | 763.2B | 1026.4B |
| Active parameters | 188B per token | 33B per token |
| Architecture | DeepseekV41ForCausalLM | DeepseekV3ForCausalLM |
| Context | 1M tokens | 256K tokens |
| Modalities | Vision, Function-calling | Chat, Function-calling |
| License | MIT | Other |
| Released | Sep 2026 | Nov 2025 |
Frequently Asked Questions
Which is better, DeepSeek V4.1 Flash or Kimi K2 Thinking?
DeepSeek V4.1 Flash leads llmrun Score 129.5 to 108.6; neither fits 24 GB. Choose DeepSeek V4.1 Flash for higher llmrun Score and stronger at agents; choose Kimi K2 Thinking for also does chat.
Which needs less VRAM, DeepSeek V4.1 Flash or Kimi K2 Thinking?
At Q4_K_M, DeepSeek V4.1 Flash requires 458.3 GB while Kimi K2 Thinking needs 619.7 GB, making DeepSeek V4.1 Flash the easier model to run on your local setup.
Can I run DeepSeek V4.1 Flash or Kimi K2 Thinking on a 16 GB GPU?
DeepSeek V4.1 Flash does not fit (smallest quant needs 210.4 GB); Kimi K2 Thinking does not fit (smallest quant needs 283.7 GB).
Which has a longer context window, DeepSeek V4.1 Flash or Kimi K2 Thinking?
DeepSeek V4.1 Flash supports 1,048,576 tokens and Kimi K2 Thinking supports 262,144 tokens.