DeepSeek V4 Pro vs Kimi K3.1 Pro

Kimi K3.1 Pro leads llmrun Score 142.8 to 116.7; neither fits 24 GB.

Run Kimi K3.1 Pro in the cloud →

Model A · DeepSeek

DeepSeek V4 Pro

116.7llmrun Score

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

Chat

Model B · Moonshot AI

Kimi K3.1 Pro

142.8llmrun Score

2780.1B · 106B active · 1M context · Other · Nov 2026

VisionChat

Which should you choose?

Choose DeepSeek V4 Pro if you want…

Lighter on memory
959.6 vs 1673.8 GB at Q4_K_M
More permissive license
MIT vs Other

Choose Kimi K3.1 Pro if you want…

Higher llmrun Score
142.8 vs 116.7
Stronger at coding
140.7 vs 110.6
Stronger at science
138.0 vs 122.2
Ahead on the benchmarks
4 of 4 shared boards
Also does vision
DeepSeek V4 Pro doesn't list it
Newer release
Nov 2026 vs Apr 2026

On your hardware

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

MemoryDeepSeek V4 ProKimi K3.1 Pro

8 GB

RTX 4060 · 8 GB tier

DeepSeek V4 Pro

Doesn't fit

smallest quant needs 680 GB

Kimi K3.1 Pro

Doesn't fit

smallest quant needs 1225.5 GB

12 GB

RTX 3060 12GB · 12 GB tier

DeepSeek V4 Pro

Doesn't fit

smallest quant needs 680 GB

Kimi K3.1 Pro

Doesn't fit

smallest quant needs 1225.5 GB

16 GB

RTX 5060 Ti 16GB · 16 GB tier

DeepSeek V4 Pro

Doesn't fit

smallest quant needs 680 GB

Kimi K3.1 Pro

Doesn't fit

smallest quant needs 1225.5 GB

24 GBreference

RTX 4090 · 24 GB tier

DeepSeek V4 Pro

Doesn't fit

smallest quant needs 680 GB

Kimi K3.1 Pro

Doesn't fit

smallest quant needs 1225.5 GB

32 GB

RTX 5090 · 32 GB tier

DeepSeek V4 Pro

Doesn't fit

smallest quant needs 680 GB

Kimi K3.1 Pro

Doesn't fit

smallest quant needs 1225.5 GB

48 GB

RTX A6000 · 48 GB tier

DeepSeek V4 Pro

Doesn't fit

smallest quant needs 680 GB

Kimi K3.1 Pro

Doesn't fit

smallest quant needs 1225.5 GB

Mac 32 GB

Mac Mini M4 · Macs

DeepSeek V4 Pro

Doesn't fit

smallest quant needs 680 GB

Kimi K3.1 Pro

Doesn't fit

smallest quant needs 1225.5 GB

Mac 64 GB

Mac Studio M4 Max · Macs

DeepSeek V4 Pro

Doesn't fit

smallest quant needs 680 GB

Kimi K3.1 Pro

Doesn't fit

smallest quant needs 1225.5 GB

Mac 128 GB

Mac Studio M4 Max · Macs

DeepSeek V4 Pro

Doesn't fit

smallest quant needs 680 GB

Kimi K3.1 Pro

Doesn't fit

smallest quant needs 1225.5 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 Pro Kimi K3.1 Pro

Overall

DeepSeek V4 Pro

116.7114–120

Kimi K3.1 Pro

142.8138–148

Coding

DeepSeek V4 Pro

110.6105–116

Kimi K3.1 Pro

140.7131–150

Math

DeepSeek V4 Pro

117.6113–122

Kimi K3.1 Pro

no data

Science

DeepSeek V4 Pro

122.2110–134

Kimi K3.1 Pro

138.0126–150

Reasoning

DeepSeek V4 Pro

118.5112–125

Kimi K3.1 Pro

no data

DeepSeek V4 Pro · #21 of 106 open models · #20 of 105 that fit ≤1 TB

Kimi K3.1 Pro · #1 of 106 open models · #1 of 106 that fit ≤2 TB

Benchmarks

4 shared boards: DeepSeek V4 Pro leads 0, Kimi K3.1 Pro leads 4 · Benchmarks imported Nov 2026

BoardDeepSeek V4 ProKimi K3.1 Pro

SciCode

DeepSeek V4 Pro

50.0%#17/72 open

Lab-reportedEpoch AI · Apr 2026

Kimi K3.1 Pro

60.8%#2/72 open

Lab-reportedEpoch AI · Oct 2026

ALE-Bench

DeepSeek V4 Pro

1006.1#14/48 open

Lab-reportedEpoch AI · Apr 2026

Kimi K3.1 Pro

1932.8#1/48 open

Lab-reportedEpoch AI · Oct 2026

CritPt

DeepSeek V4 Pro

12.9%#13/84 open

Lab-reportedEpoch AI · Apr 2026

Kimi K3.1 Pro

24.6%#2/84 open

Lab-reportedEpoch AI · Oct 2026

ProofBench

DeepSeek V4 Pro

16.0%#17/31 open

Lab-reportedEpoch AI · Apr 2026

Kimi K3.1 Pro

91.0%#1/31 open

Lab-reportedEpoch AI · Oct 2026

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

Only DeepSeek V4 Pro (20)

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 ProKimi K3.1 Pro

Q2_K

DeepSeek V4 Pro

680 GB574.1 GB file

32K 680 GB · 128K 682 GB

Kimi K3.1 Pro

1187 GB~1181.5 GB file

32K 1269 GB · 128K 1531 GB

Q3_K_M

DeepSeek V4 Pro

780 GB748.7 GB file

32K 780 GB · 128K 782 GB

Kimi K3.1 Pro

1361 GB~1355.3 GB file

32K 1443 GB · 128K 1705 GB

Q4_K_M

DeepSeek V4 Pro

960 GB954.6 GB file

32K 960 GB · 128K 961 GB

Kimi K3.1 Pro

1674 GB~1668.1 GB file

32K 1756 GB · 128K 2018 GB

Q5_K_M

DeepSeek V4 Pro

1140 GB~1139.2 GB file

32K 1140 GB · 128K 1141 GB

Kimi K3.1 Pro

1987 GB~1980.8 GB file

32K 2069 GB · 128K 2331 GB

Q6_K

DeepSeek V4 Pro

1319 GB~1319.0 GB file

32K 1320 GB · 128K 1321 GB

Kimi K3.1 Pro

2299 GB~2293.6 GB file

32K 2381 GB · 128K 2643 GB

Q8_0

DeepSeek V4 Pro

1599 GB1671.8 GB file

32K 1600 GB · 128K 1601 GB

Kimi K3.1 Pro

2786 GB~2780.1 GB file

32K 2868 GB · 128K 3130 GB

1 more quant

BF16

DeepSeek V4 Pro

3198 GB~3197.7 GB file

32K 3198 GB · 128K 3200 GB

Kimi K3.1 Pro

5566 GB~5560.2 GB file

32K 5648 GB · 128K 5910 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 →

Kimi K3.1 Pro

No local recipe · Q4_K_M

No GGUF repo entry exists for this model yet.

All ways to run Kimi K3.1 Pro →

Specifications

Specifications of DeepSeek V4 Pro and Kimi K3.1 Pro
Spec	DeepSeek V4 Pro	Kimi K3.1 Pro
Publisher	DeepSeek	Moonshot AI
Parameters	1598.8B	2780.1B
Active parameters	51B per token	106B per token
Architecture	DeepseekV4ForCausalLM	KimiK31ForConditionalGeneration
Context	1M tokens	1M tokens
Modalities	Chat	Vision, Chat
License	MIT	Other
Released	Apr 2026	Nov 2026

Frequently Asked Questions

Which is better, DeepSeek V4 Pro or Kimi K3.1 Pro?

Kimi K3.1 Pro leads llmrun Score 142.8 to 116.7; neither fits 24 GB. Choose DeepSeek V4 Pro for lighter on memory and more permissive license; choose Kimi K3.1 Pro for higher llmrun Score and stronger at coding.

Which needs less VRAM, DeepSeek V4 Pro or Kimi K3.1 Pro?

At Q4_K_M, DeepSeek V4 Pro requires 959.6 GB while Kimi K3.1 Pro needs 1673.8 GB, making DeepSeek V4 Pro the easier model to run on your local setup.

Can I run DeepSeek V4 Pro or Kimi K3.1 Pro on a 16 GB GPU?

DeepSeek V4 Pro does not fit (smallest quant needs 680 GB); Kimi K3.1 Pro does not fit (smallest quant needs 1225.5 GB).

Which has a longer context window, DeepSeek V4 Pro or Kimi K3.1 Pro?

DeepSeek V4 Pro supports 1,048,576 tokens and Kimi K3.1 Pro supports 1,048,576 tokens.