DeepSeek V4 Pro 0813 vs MiMo V2.6 Pro RL

MiMo V2.6 Pro RL leads llmrun Score 133.4 to 129.2 (ranges overlap); neither fits 24 GB.

Model A · DeepSeek

DeepSeek V4 Pro 0813

129.2llmrun Score

1650.5B · 102.3B active · 1M context · MIT · Aug 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 129.2, ranges overlap
Stronger at science
139.8 vs 126.3
Ahead on the benchmarks
4 of 5 shared boards
Lighter on memory
612.5 vs 990.6 GB at Q4_K_M
Also does function-calling
DeepSeek V4 Pro 0813 doesn't list it

DeepSeek V4 Pro 0813: 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 Pro 0813MiMo V2.6 Pro RL

8 GB

RTX 4060 · 8 GB tier

DeepSeek V4 Pro 0813

Doesn't fit

smallest quant needs 640.1 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 0813

Doesn't fit

smallest quant needs 640.1 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 0813

Doesn't fit

smallest quant needs 640.1 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 0813

Doesn't fit

smallest quant needs 640.1 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 0813

Doesn't fit

smallest quant needs 640.1 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 0813

Doesn't fit

smallest quant needs 640.1 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 0813

Doesn't fit

smallest quant needs 640.1 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 0813

Doesn't fit

smallest quant needs 640.1 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 0813

Doesn't fit

smallest quant needs 640.1 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 0813 MiMo V2.6 Pro RL

Overall

DeepSeek V4 Pro 0813

129.2127–131

MiMo V2.6 Pro RL

133.4131–136

Coding

DeepSeek V4 Pro 0813

125.2119–132

MiMo V2.6 Pro RL

125.7119–132

Agents

DeepSeek V4 Pro 0813

no data

MiMo V2.6 Pro RL

132.1127–137

Math

DeepSeek V4 Pro 0813

128.3126–131

MiMo V2.6 Pro RL

no data

Science

DeepSeek V4 Pro 0813

126.3114–138

MiMo V2.6 Pro RL

139.8129–151

Reasoning

DeepSeek V4 Pro 0813

131.1128–134

MiMo V2.6 Pro RL

no data

DeepSeek V4 Pro 0813 · #6 of 100 open models · #6 of 99 that fit ≤1 TB

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

Benchmarks

5 shared boards: DeepSeek V4 Pro 0813 leads 1, MiMo V2.6 Pro RL leads 4 · Benchmarks imported Oct 2026

BoardDeepSeek V4 Pro 0813MiMo V2.6 Pro RL

SciCode

DeepSeek V4 Pro 0813

51.0%#9/66 open

Lab-reportedEpoch AI · Aug 2026

MiMo V2.6 Pro RL

60.9%#1/66 open

Lab-reportedEpoch AI · Sep 2026

ALE-Bench

DeepSeek V4 Pro 0813

1403.2#2/43 open

Lab-reportedEpoch AI · Aug 2026

MiMo V2.6 Pro RL

1158.1#6/43 open

Lab-reportedEpoch AI · Sep 2026

APEX-Agents

DeepSeek V4 Pro 0813

47.3%#6/16 open

Lab-reportedEpoch AI · Aug 2026

MiMo V2.6 Pro RL

59.5%#1/16 open

Lab-reportedEpoch AI · Sep 2026

CritPt

DeepSeek V4 Pro 0813

18.0%#5/66 open

Lab-reportedEpoch AI · Aug 2026

MiMo V2.6 Pro RL

26.6%#1/66 open

Lab-reportedEpoch AI · Sep 2026

ProofBench

DeepSeek V4 Pro 0813

50.0%#7/26 open

Lab-reportedEpoch AI · Aug 2026

MiMo V2.6 Pro RL

70.0%#3/26 open

Lab-reportedEpoch AI · Sep 2026

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

LMArena Text

DeepSeek V4 Pro 0813

1464.6#9/187 open

ArenaLMArena · Oct 2026

MiMo V2.6 Pro RL

1479.2#2/187 open

ArenaLMArena · Oct 2026

LMArena WebDev

DeepSeek V4 Pro 0813

1582.0#11/52 open

ArenaLMArena · Oct 2026

MiMo V2.6 Pro RL

1624.8#5/52 open

ArenaLMArena · Oct 2026

Only DeepSeek V4 Pro 0813 (16)

Only MiMo V2.6 Pro RL (7)

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 Pro 0813MiMo V2.6 Pro RL

Q2_K

DeepSeek V4 Pro 0813

702 GB587.3 GB file

32K 702 GB · 128K 704 GB

MiMo V2.6 Pro RL

434 GB418.8 GB file

32K 437 GB · 128K 448 GB

Q3_K_M

DeepSeek V4 Pro 0813

805 GB763.7 GB file

32K 805 GB · 128K 807 GB

MiMo V2.6 Pro RL

498 GB~497.3 GB file

32K 501 GB · 128K 512 GB

Q4_0

DeepSeek V4 Pro 0813

826 GB885.3 GB file

32K 826 GB · 128K 827 GB

MiMo V2.6 Pro RL

511 GB~510.0 GB file

32K 514 GB · 128K 524 GB

Q4_K_M

DeepSeek V4 Pro 0813

991 GB~990.3 GB file

32K 991 GB · 128K 992 GB

MiMo V2.6 Pro RL

613 GB~612.0 GB file

32K 616 GB · 128K 626 GB

Q5_K_M

DeepSeek V4 Pro 0813

1176 GB~1176.0 GB file

32K 1177 GB · 128K 1178 GB

MiMo V2.6 Pro RL

727 GB~726.8 GB file

32K 731 GB · 128K 741 GB

Q6_K

DeepSeek V4 Pro 0813

1362 GB~1361.7 GB file

32K 1362 GB · 128K 1364 GB

MiMo V2.6 Pro RL

842 GB~841.5 GB file

32K 845 GB · 128K 856 GB

Q8_0

DeepSeek V4 Pro 0813

1651 GB~1650.5 GB file

32K 1651 GB · 128K 1653 GB

MiMo V2.6 Pro RL

1021 GB~1020.0 GB file

32K 1024 GB · 128K 1034 GB

3 more quants

IQ3_XXS

DeepSeek V4 Pro 0813

640 GB619.5 GB file

32K 640 GB · 128K 642 GB

MiMo V2.6 Pro RL

not listed

Q4_1

DeepSeek V4 Pro 0813

929 GB983.6 GB file

32K 929 GB · 128K 930 GB

MiMo V2.6 Pro RL

not listed

BF16

DeepSeek V4 Pro 0813

3301 GB~3301.0 GB file

32K 3302 GB · 128K 3303 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 0813

Ollama · Q4_K_M

$ollama run hf.co/unsloth/DeepSeek-V4-Pro-0813-GGUF

All ways to run DeepSeek V4 Pro 0813 →

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 0813 and MiMo V2.6 Pro RL
Spec	DeepSeek V4 Pro 0813	MiMo V2.6 Pro RL
Publisher	DeepSeek	Xiaomi
Parameters	1650.5B	1020B
Active parameters	102B per token	42B per token
Architecture	DeepseekV4ForCausalLM	MiMoV2ForCausalLM
Context	1M tokens	1M tokens
Modalities	Chat	Chat, Function-calling
License	MIT	MIT
Released	Aug 2026	Sep 2026

Frequently Asked Questions

Which is better, DeepSeek V4 Pro 0813 or MiMo V2.6 Pro RL?

MiMo V2.6 Pro RL leads llmrun Score 133.4 to 129.2 (ranges overlap); 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 0813 or MiMo V2.6 Pro RL?

At Q4_K_M, DeepSeek V4 Pro 0813 requires 990.6 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 0813 or MiMo V2.6 Pro RL on a 16 GB GPU?

DeepSeek V4 Pro 0813 does not fit (smallest quant needs 640.1 GB); MiMo V2.6 Pro RL does not fit (smallest quant needs 435.6 GB).

Which has a longer context window, DeepSeek V4 Pro 0813 or MiMo V2.6 Pro RL?

DeepSeek V4 Pro 0813 supports 1,048,576 tokens and MiMo V2.6 Pro RL supports 1,048,576 tokens.