DeepSeek V4.1 Flash vs MiMo V2.5 Pro

DeepSeek V4.1 Flash leads llmrun Score 129.5 to 116.4; neither fits 24 GB.

Model A · DeepSeek

DeepSeek V4.1 Flash

129.5llmrun Score

763.2B · 188B active · 1M context · MIT · Sep 2026

VisionFunctions

Model B · Xiaomi

MiMo V2.5 Pro

116.4llmrun Score

1023.2B · 43.9B active · 1M context · MIT · Apr 2026

ChatFunctionsCode

Which should you choose?

Choose DeepSeek V4.1 Flash if you want…

Higher llmrun Score
129.5 vs 116.4
Stronger at reasoning
134.0 vs 110.8
Stronger at science
122.9 vs 114.6
Ahead on the benchmarks
6 of 6 shared boards
Lighter on memory
458.3 vs 614.5 GB at Q4_K_M
Also does vision
MiMo V2.5 Pro doesn't list it

Choose MiMo V2.5 Pro if you want…

Also does chat, code
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%.

MemoryDeepSeek V4.1 FlashMiMo V2.5 Pro

8 GB

RTX 4060 · 8 GB tier

DeepSeek V4.1 Flash

Doesn't fit

smallest quant needs 210.4 GB

MiMo V2.5 Pro

Doesn't fit

smallest quant needs 283.5 GB

12 GB

RTX 3060 12GB · 12 GB tier

DeepSeek V4.1 Flash

Doesn't fit

smallest quant needs 210.4 GB

MiMo V2.5 Pro

Doesn't fit

smallest quant needs 283.5 GB

16 GB

RTX 5060 Ti 16GB · 16 GB tier

DeepSeek V4.1 Flash

Doesn't fit

smallest quant needs 210.4 GB

MiMo V2.5 Pro

Doesn't fit

smallest quant needs 283.5 GB

24 GBreference

RTX 4090 · 24 GB tier

DeepSeek V4.1 Flash

Doesn't fit

smallest quant needs 210.4 GB

MiMo V2.5 Pro

Doesn't fit

smallest quant needs 283.5 GB

32 GB

RTX 5090 · 32 GB tier

DeepSeek V4.1 Flash

Doesn't fit

smallest quant needs 210.4 GB

MiMo V2.5 Pro

Doesn't fit

smallest quant needs 283.5 GB

48 GB

RTX A6000 · 48 GB tier

DeepSeek V4.1 Flash

Doesn't fit

smallest quant needs 210.4 GB

MiMo V2.5 Pro

Doesn't fit

smallest quant needs 283.5 GB

Mac 32 GB

Mac Mini M4 · Macs

DeepSeek V4.1 Flash

Doesn't fit

smallest quant needs 210.4 GB

MiMo V2.5 Pro

Doesn't fit

smallest quant needs 283.5 GB

Mac 64 GB

Mac Studio M4 Max · Macs

DeepSeek V4.1 Flash

Doesn't fit

smallest quant needs 210.4 GB

MiMo V2.5 Pro

Doesn't fit

smallest quant needs 283.5 GB

Mac 128 GB

Mac Studio M4 Max · Macs

DeepSeek V4.1 Flash

Doesn't fit

smallest quant needs 210.4 GB

MiMo V2.5 Pro

Doesn't fit

smallest quant needs 283.5 GB

Reference GPU: RTX 4090. Tinted cell = the better pick on that machine (fits, more headroom, or at least 10% faster).

llmrun Score

with its 90% range · bars share one scale

DeepSeek V4.1 Flash MiMo V2.5 Pro

Overall

DeepSeek V4.1 Flash

129.5128–131

MiMo V2.5 Pro

116.4111–122

Coding

DeepSeek V4.1 Flash

122.2118–127

MiMo V2.5 Pro

115.6106–126

Agents

DeepSeek V4.1 Flash

127.9123–133

MiMo V2.5 Pro

no data

Math

DeepSeek V4.1 Flash

129.0127–132

MiMo V2.5 Pro

no data

Science

DeepSeek V4.1 Flash

122.9111–135

MiMo V2.5 Pro

114.697–133

Reasoning

DeepSeek V4.1 Flash

134.0130–138

MiMo V2.5 Pro

110.8102–120

DeepSeek V4.1 Flash · #5 of 100 open models · #4 of 96 that fit ≤512 GB

MiMo V2.5 Pro · #17 of 100 open models · #14 of 96 that fit ≤640 GB

Benchmarks

6 shared boards: DeepSeek V4.1 Flash leads 6, MiMo V2.5 Pro leads 0 · Benchmarks imported Oct 2026

BoardDeepSeek V4.1 FlashMiMo V2.5 Pro

SciCode

DeepSeek V4.1 Flash

51.8%#5/66 open

Lab-reportedEpoch AI · Sep 2026

MiMo V2.5 Pro

50.2%#10/66 open

Lab-reportedEpoch AI

ALE-Bench

DeepSeek V4.1 Flash

1092.3#8/43 open

Lab-reportedEpoch AI · Sep 2026

MiMo V2.5 Pro

899.8#14/43 open

Lab-reportedEpoch AI

CritPt

DeepSeek V4.1 Flash

14.3%#8/66 open

Lab-reportedEpoch AI · Sep 2026

MiMo V2.5 Pro

4.0%#18/66 open

Lab-reportedEpoch AI

DTBench

DeepSeek V4.1 Flash

89.9%#8/68 open

Lab-reportedEpoch AI · Sep 2026

MiMo V2.5 Pro

84.5%#16/68 open

Lab-reportedEpoch AI

LMCA

DeepSeek V4.1 Flash

47.0%#3/54 open

Lab-reportedEpoch AI · Sep 2026

MiMo V2.5 Pro

29.5%#21/54 open

Lab-reportedEpoch AI

ProofBench

DeepSeek V4.1 Flash

54.0%#6/26 open

Lab-reportedEpoch AI · Sep 2026

MiMo V2.5 Pro

22.0%#11/26 open

Lab-reportedEpoch AI

25 more boards (other shared and single-model boards)

LMArena Text

DeepSeek V4.1 Flash

1474.6#5/187 open

ArenaLMArena · Oct 2026

MiMo V2.5 Pro

1467.3#7/187 open

ArenaLMArena · Oct 2026

LMArena WebDev

DeepSeek V4.1 Flash

1618.4#7/52 open

ArenaLMArena · Oct 2026

MiMo V2.5 Pro

1481.3#18/52 open

ArenaLMArena · Oct 2026

Only DeepSeek V4.1 Flash (23)

VRAM by quantization

Memory to load the model and 2K context; below it, the total at 32K and 128K context. Lighter side in bold.

QuantDeepSeek V4.1 FlashMiMo V2.5 Pro

Q2_K

DeepSeek V4.1 Flash

325 GB264.5 GB file

32K 325 GB · 128K 326 GB

MiMo V2.5 Pro

435 GB~434.9 GB file

32K 439 GB · 128K 449 GB

Q3_K_M

DeepSeek V4.1 Flash

372 GB347.3 GB file

32K 373 GB · 128K 374 GB

MiMo V2.5 Pro

499 GB459.7 GB file

32K 503 GB · 128K 513 GB

Q4_K_M

DeepSeek V4.1 Flash

458 GB444.7 GB file

32K 459 GB · 128K 460 GB

MiMo V2.5 Pro

614 GB629.6 GB file

32K 618 GB · 128K 628 GB

Q5_K_M

DeepSeek V4.1 Flash

544 GB~543.8 GB file

32K 545 GB · 128K 546 GB

MiMo V2.5 Pro

730 GB758.0 GB file

32K 733 GB · 128K 743 GB

Q6_K

DeepSeek V4.1 Flash

630 GB~629.6 GB file

32K 630 GB · 128K 632 GB

MiMo V2.5 Pro

845 GB846.6 GB file

32K 848 GB · 128K 859 GB

Q8_0

DeepSeek V4.1 Flash

764 GB508.0 GB file

32K 764 GB · 128K 765 GB

MiMo V2.5 Pro

1024 GB1087.6 GB file

32K 1027 GB · 128K 1038 GB

11 more quants

IQ2_XXS

DeepSeek V4.1 Flash

210 GB~209.9 GB file

32K 211 GB · 128K 212 GB

MiMo V2.5 Pro

282 GB317.2 GB file

32K 285 GB · 128K 296 GB

IQ2_S

DeepSeek V4.1 Flash

not listed

MiMo V2.5 Pro

320 GB319.4 GB file

32K 324 GB · 128K 334 GB

IQ2_M

DeepSeek V4.1 Flash

not listed

MiMo V2.5 Pro

346 GB317.3 GB file

32K 349 GB · 128K 360 GB

IQ3_XXS

DeepSeek V4.1 Flash

not listed

MiMo V2.5 Pro

397 GB412.7 GB file

32K 400 GB · 128K 411 GB

IQ3_XS

DeepSeek V4.1 Flash

315 GB434.0 GB file

32K 316 GB · 128K 317 GB

MiMo V2.5 Pro

not listed

IQ3_S

DeepSeek V4.1 Flash

not listed

MiMo V2.5 Pro

435 GB377.9 GB file

32K 439 GB · 128K 449 GB

IQ4_XS

DeepSeek V4.1 Flash

not listed

MiMo V2.5 Pro

551 GB490.7 GB file

32K 554 GB · 128K 564 GB

IQ4_NL

DeepSeek V4.1 Flash

not listed

MiMo V2.5 Pro

576 GB501.3 GB file

32K 579 GB · 128K 590 GB

Q4_K_S

DeepSeek V4.1 Flash

not listed

MiMo V2.5 Pro

576 GB588.5 GB file

32K 579 GB · 128K 590 GB

Q5_K_S

DeepSeek V4.1 Flash

not listed

MiMo V2.5 Pro

704 GB713.2 GB file

32K 707 GB · 128K 718 GB

BF16

DeepSeek V4.1 Flash

1527 GB~1526.4 GB file

32K 1527 GB · 128K 1528 GB

MiMo V2.5 Pro

2047 GB2046.7 GB file

32K 2050 GB · 128K 2061 GB

How to run each

DeepSeek V4.1 Flash

Ollama · Q4_K_M

$ollama run hf.co/vcruz305/DeepSeek-V4.1-Flash-GGUF:Q4_K_M

All ways to run DeepSeek V4.1 Flash →

MiMo V2.5 Pro

Ollama · Q4_K_M

$ollama run hf.co/unsloth/MiMo-V2.5-Pro-GGUF:Q4_K_M

All ways to run MiMo V2.5 Pro →

Specifications

Specifications of DeepSeek V4.1 Flash and MiMo V2.5 Pro
Spec	DeepSeek V4.1 Flash	MiMo V2.5 Pro
Publisher	DeepSeek	Xiaomi
Parameters	763.2B	1023.2B
Active parameters	188B per token	44B per token
Architecture	DeepseekV41ForCausalLM	MiMoV2ForCausalLM
Context	1M tokens	1M tokens
Modalities	Vision, Function-calling	Chat, Function-calling, Code
License	MIT	MIT
Released	Sep 2026	Apr 2026

Frequently Asked Questions

Which is better, DeepSeek V4.1 Flash or MiMo V2.5 Pro?

DeepSeek V4.1 Flash leads llmrun Score 129.5 to 116.4; neither fits 24 GB. Choose DeepSeek V4.1 Flash for higher llmrun Score and stronger at reasoning; choose MiMo V2.5 Pro for also does chat, code.

Which needs less VRAM, DeepSeek V4.1 Flash or MiMo V2.5 Pro?

At Q4_K_M, DeepSeek V4.1 Flash requires 458.3 GB while MiMo V2.5 Pro needs 614.5 GB, making DeepSeek V4.1 Flash the easier model to run on your local setup.

Can I run DeepSeek V4.1 Flash or MiMo V2.5 Pro on a 16 GB GPU?

DeepSeek V4.1 Flash does not fit (smallest quant needs 210.4 GB); MiMo V2.5 Pro does not fit (smallest quant needs 283.5 GB).

Which has a longer context window, DeepSeek V4.1 Flash or MiMo V2.5 Pro?

DeepSeek V4.1 Flash supports 1,048,576 tokens and MiMo V2.5 Pro supports 1,048,576 tokens.