DeepSeek V4 Pro vs MiMo V2.6 Pro RL

MiMo V2.6 Pro RL leads llmrun Score 133.4 to 116.5; neither fits 24 GB.

Model A · DeepSeek

DeepSeek V4 Pro

116.5llmrun Score

1598.8B · 50.7B active · 1M context · MIT · Apr 2026

Chat

Model B · Xiaomi

MiMo V2.6 Pro RL

133.4llmrun Score

1020B · 42B active · 1M context · MIT · Sep 2026

ChatFunctions

Which should you choose?

Choose MiMo V2.6 Pro RL if you want…

Higher llmrun Score
133.4 vs 116.5
Stronger at science
139.8 vs 122.3
Stronger at coding
125.7 vs 110.6
Ahead on the benchmarks
4 of 4 shared boards
Lighter on memory
612.5 vs 959.6 GB at Q4_K_M
Also does function-calling
DeepSeek V4 Pro doesn't list it

DeepSeek V4 Pro: no clear edge over MiMo V2.6 Pro RL in the data we have.

On your hardware

Each model at its default quant (Q4_K_M), a smaller one when it must. Estimates, ±20%.

MemoryDeepSeek V4 ProMiMo V2.6 Pro RL

8 GB

RTX 4060 · 8 GB tier

DeepSeek V4 Pro

Doesn't fit

smallest quant needs 680 GB

MiMo V2.6 Pro RL

Doesn't fit

smallest quant needs 435.6 GB

12 GB

RTX 3060 12GB · 12 GB tier

DeepSeek V4 Pro

Doesn't fit

smallest quant needs 680 GB

MiMo V2.6 Pro RL

Doesn't fit

smallest quant needs 435.6 GB

16 GB

RTX 5060 Ti 16GB · 16 GB tier

DeepSeek V4 Pro

Doesn't fit

smallest quant needs 680 GB

MiMo V2.6 Pro RL

Doesn't fit

smallest quant needs 435.6 GB

24 GBreference

RTX 4090 · 24 GB tier

DeepSeek V4 Pro

Doesn't fit

smallest quant needs 680 GB

MiMo V2.6 Pro RL

Doesn't fit

smallest quant needs 435.6 GB

32 GB

RTX 5090 · 32 GB tier

DeepSeek V4 Pro

Doesn't fit

smallest quant needs 680 GB

MiMo V2.6 Pro RL

Doesn't fit

smallest quant needs 435.6 GB

48 GB

RTX A6000 · 48 GB tier

DeepSeek V4 Pro

Doesn't fit

smallest quant needs 680 GB

MiMo V2.6 Pro RL

Doesn't fit

smallest quant needs 435.6 GB

Mac 32 GB

Mac Mini M4 · Macs

DeepSeek V4 Pro

Doesn't fit

smallest quant needs 680 GB

MiMo V2.6 Pro RL

Doesn't fit

smallest quant needs 435.6 GB

Mac 64 GB

Mac Studio M4 Max · Macs

DeepSeek V4 Pro

Doesn't fit

smallest quant needs 680 GB

MiMo V2.6 Pro RL

Doesn't fit

smallest quant needs 435.6 GB

Mac 128 GB

Mac Studio M4 Max · Macs

DeepSeek V4 Pro

Doesn't fit

smallest quant needs 680 GB

MiMo V2.6 Pro RL

Doesn't fit

smallest quant needs 435.6 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 Pro MiMo V2.6 Pro RL

Overall

DeepSeek V4 Pro

116.5114–119

MiMo V2.6 Pro RL

133.4131–136

Coding

DeepSeek V4 Pro

110.6105–116

MiMo V2.6 Pro RL

125.7119–132

Agents

DeepSeek V4 Pro

no data

MiMo V2.6 Pro RL

132.1127–137

Math

DeepSeek V4 Pro

117.6114–122

MiMo V2.6 Pro RL

no data

Science

DeepSeek V4 Pro

122.3111–134

MiMo V2.6 Pro RL

139.8129–151

Reasoning

DeepSeek V4 Pro

117.0110–124

MiMo V2.6 Pro RL

no data

DeepSeek V4 Pro · #16 of 100 open models · #16 of 99 that fit ≤1 TB

MiMo V2.6 Pro RL · #1 of 100 open models · #1 of 96 that fit ≤640 GB

Benchmarks

4 shared boards: DeepSeek V4 Pro leads 0, MiMo V2.6 Pro RL leads 4 · Benchmarks imported Oct 2026

BoardDeepSeek V4 ProMiMo V2.6 Pro RL

SciCode

DeepSeek V4 Pro

50.0%#12/66 open

Lab-reportedEpoch AI · Apr 2026

MiMo V2.6 Pro RL

60.9%#1/66 open

Lab-reportedEpoch AI · Sep 2026

ALE-Bench

DeepSeek V4 Pro

1006.1#10/43 open

Lab-reportedEpoch AI · Apr 2026

MiMo V2.6 Pro RL

1158.1#6/43 open

Lab-reportedEpoch AI · Sep 2026

CritPt

DeepSeek V4 Pro

12.9%#9/66 open

Lab-reportedEpoch AI · Apr 2026

MiMo V2.6 Pro RL

26.6%#1/66 open

Lab-reportedEpoch AI · Sep 2026

ProofBench

DeepSeek V4 Pro

16.0%#14/26 open

Lab-reportedEpoch AI · Apr 2026

MiMo V2.6 Pro RL

70.0%#3/26 open

Lab-reportedEpoch AI · Sep 2026

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

LMArena Text

DeepSeek V4 Pro

1457.8#11/187 open

ArenaLMArena · Oct 2026

MiMo V2.6 Pro RL

1479.2#2/187 open

ArenaLMArena · Oct 2026

LMArena WebDev

DeepSeek V4 Pro

1464.2#20/52 open

ArenaLMArena · Oct 2026

MiMo V2.6 Pro RL

1624.8#5/52 open

ArenaLMArena · Oct 2026

Only DeepSeek V4 Pro (18)

Only MiMo V2.6 Pro RL (8)

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 ProMiMo V2.6 Pro RL

Q2_K

DeepSeek V4 Pro

680 GB574.1 GB file

32K 680 GB · 128K 682 GB

MiMo V2.6 Pro RL

434 GB418.8 GB file

32K 437 GB · 128K 448 GB

Q3_K_M

DeepSeek V4 Pro

780 GB748.7 GB file

32K 780 GB · 128K 782 GB

MiMo V2.6 Pro RL

498 GB~497.3 GB file

32K 501 GB · 128K 512 GB

Q4_0

DeepSeek V4 Pro

not listed

MiMo V2.6 Pro RL

511 GB~510.0 GB file

32K 514 GB · 128K 524 GB

Q4_K_M

DeepSeek V4 Pro

960 GB954.6 GB file

32K 960 GB · 128K 961 GB

MiMo V2.6 Pro RL

613 GB~612.0 GB file

32K 616 GB · 128K 626 GB

Q5_K_M

DeepSeek V4 Pro

1140 GB~1139.2 GB file

32K 1140 GB · 128K 1141 GB

MiMo V2.6 Pro RL

727 GB~726.8 GB file

32K 731 GB · 128K 741 GB

Q6_K

DeepSeek V4 Pro

1319 GB~1319.0 GB file

32K 1320 GB · 128K 1321 GB

MiMo V2.6 Pro RL

842 GB~841.5 GB file

32K 845 GB · 128K 856 GB

Q8_0

DeepSeek V4 Pro

1599 GB1671.8 GB file

32K 1600 GB · 128K 1601 GB

MiMo V2.6 Pro RL

1021 GB~1020.0 GB file

32K 1024 GB · 128K 1034 GB

1 more quant

BF16

DeepSeek V4 Pro

3198 GB~3197.7 GB file

32K 3198 GB · 128K 3200 GB

MiMo V2.6 Pro RL

2041 GB~2040.0 GB file

32K 2044 GB · 128K 2054 GB

How to run each

DeepSeek V4 Pro

Ollama · Q4_K_M

$ollama run hf.co/teamblobfish/DeepSeek-V4-Pro-GGUF:Q4_K_M

All ways to run DeepSeek V4 Pro →

MiMo V2.6 Pro RL

Ollama · Q4_K_M

$ollama run hf.co/ggml-org/MiMo-V2.6-Pro-RL-GGUF

All ways to run MiMo V2.6 Pro RL →

Specifications

Specifications of DeepSeek V4 Pro and MiMo V2.6 Pro RL
Spec	DeepSeek V4 Pro	MiMo V2.6 Pro RL
Publisher	DeepSeek	Xiaomi
Parameters	1598.8B	1020B
Active parameters	51B per token	42B per token
Architecture	DeepseekV4ForCausalLM	MiMoV2ForCausalLM
Context	1M tokens	1M tokens
Modalities	Chat	Chat, Function-calling
License	MIT	MIT
Released	Apr 2026	Sep 2026

Frequently Asked Questions

Which is better, DeepSeek V4 Pro or MiMo V2.6 Pro RL?

MiMo V2.6 Pro RL leads llmrun Score 133.4 to 116.5; neither fits 24 GB. Choose MiMo V2.6 Pro RL for higher llmrun Score and stronger at science.

Which needs less VRAM, DeepSeek V4 Pro or MiMo V2.6 Pro RL?

At Q4_K_M, DeepSeek V4 Pro requires 959.6 GB while MiMo V2.6 Pro RL needs 612.5 GB, making MiMo V2.6 Pro RL the easier model to run on your local setup.

Can I run DeepSeek V4 Pro or MiMo V2.6 Pro RL on a 16 GB GPU?

DeepSeek V4 Pro does not fit (smallest quant needs 680 GB); MiMo V2.6 Pro RL does not fit (smallest quant needs 435.6 GB).

Which has a longer context window, DeepSeek V4 Pro or MiMo V2.6 Pro RL?

DeepSeek V4 Pro supports 1,048,576 tokens and MiMo V2.6 Pro RL supports 1,048,576 tokens.