DeepSeek V4 Pro vs MiMo V2.5 Pro
DeepSeek V4 Pro and MiMo V2.5 Pro match in llmrun Score, with values of 116.5 versus 116.4; neither fits 24 GB.
Model A · DeepSeek
DeepSeek V4 Pro1598.8B · 50.7B active · 1M context · MIT · Apr 2026
Model B · Xiaomi
MiMo V2.5 Pro1023.2B · 43.9B active · 1M context · MIT · Apr 2026
Choose DeepSeek V4 Pro if you want…
Stronger at science
122.3 vs 114.6
Stronger at reasoning
117.0 vs 110.8
Ahead on the benchmarks
4 of 6 shared boards
Choose MiMo V2.5 Pro if you want…
Lighter on memory
614.5 vs 959.6 GB at Q4_K_M
Also does function-calling, code
DeepSeek V4 Pro 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 Pro
Doesn't fit
smallest quant needs 680 GB
MiMo V2.5 Pro
Doesn't fit
smallest quant needs 283.5 GB
12 GB
RTX 3060 12GB · 12 GB tier
DeepSeek V4 Pro
Doesn't fit
smallest quant needs 680 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 Pro
Doesn't fit
smallest quant needs 680 GB
MiMo V2.5 Pro
Doesn't fit
smallest quant needs 283.5 GB
24 GBreference
RTX 4090 · 24 GB tier
DeepSeek V4 Pro
Doesn't fit
smallest quant needs 680 GB
MiMo V2.5 Pro
Doesn't fit
smallest quant needs 283.5 GB
32 GB
RTX 5090 · 32 GB tier
DeepSeek V4 Pro
Doesn't fit
smallest quant needs 680 GB
MiMo V2.5 Pro
Doesn't fit
smallest quant needs 283.5 GB
48 GB
RTX A6000 · 48 GB tier
DeepSeek V4 Pro
Doesn't fit
smallest quant needs 680 GB
MiMo V2.5 Pro
Doesn't fit
smallest quant needs 283.5 GB
Mac 32 GB
Mac Mini M4 · Macs
DeepSeek V4 Pro
Doesn't fit
smallest quant needs 680 GB
MiMo V2.5 Pro
Doesn't fit
smallest quant needs 283.5 GB
Mac 64 GB
Mac Studio M4 Max · Macs
DeepSeek V4 Pro
Doesn't fit
smallest quant needs 680 GB
MiMo V2.5 Pro
Doesn't fit
smallest quant needs 283.5 GB
Mac 128 GB
Mac Studio M4 Max · Macs
DeepSeek V4 Pro
Doesn't fit
smallest quant needs 680 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).
Overall
DeepSeek V4 Pro
MiMo V2.5 Pro
Coding
DeepSeek V4 Pro
MiMo V2.5 Pro
Math
DeepSeek V4 Pro
MiMo V2.5 Pro
no data
Science
DeepSeek V4 Pro
MiMo V2.5 Pro
Reasoning
DeepSeek V4 Pro
MiMo V2.5 Pro
DeepSeek V4 Pro · #16 of 100 open models · #16 of 99 that fit ≤1 TB
MiMo V2.5 Pro · #17 of 100 open models · #14 of 96 that fit ≤640 GB
Benchmarks
6 shared boards: DeepSeek V4 Pro leads 4, MiMo V2.5 Pro leads 1 · Benchmarks imported Oct 2026
DeepSeek V4 Pro
50.0%#12/66 open
Lab-reportedEpoch AI · Apr 2026
MiMo V2.5 Pro
50.2%#10/66 open
Lab-reportedEpoch AI
DeepSeek V4 Pro
1006.1#10/43 open
Lab-reportedEpoch AI · Apr 2026
MiMo V2.5 Pro
899.8#14/43 open
Lab-reportedEpoch AI
DeepSeek V4 Pro
12.9%#9/66 open
Lab-reportedEpoch AI · Apr 2026
MiMo V2.5 Pro
4.0%#18/66 open
Lab-reportedEpoch AI
DeepSeek V4 Pro
90.7%#6/68 open
Lab-reportedEpoch AI · Apr 2026
MiMo V2.5 Pro
84.5%#16/68 open
Lab-reportedEpoch AI
DeepSeek V4 Pro
41.2%#8/54 open
Lab-reportedEpoch AI · Apr 2026
MiMo V2.5 Pro
29.5%#21/54 open
Lab-reportedEpoch AI
DeepSeek V4 Pro
16.0%#14/26 open
Lab-reportedEpoch AI · Apr 2026
MiMo V2.5 Pro
22.0%#11/26 open
Lab-reportedEpoch AI
18 more boards (other shared and single-model boards)
DeepSeek V4 Pro
1457.8#11/187 open
ArenaLMArena · Oct 2026
MiMo V2.5 Pro
1467.3#7/187 open
ArenaLMArena · Oct 2026
DeepSeek V4 Pro
1464.2#20/52 open
ArenaLMArena · Oct 2026
MiMo V2.5 Pro
1481.3#18/52 open
ArenaLMArena · Oct 2026
Only DeepSeek V4 Pro (16)
- GPQA Diamond90.9%
- LiveBench Coding70.0
- LiveBench Reasoning82.7
- AIME 2024/202596.7%
- FrontierMath45.3%
- LiveBench Math90.7
- SimpleQA47.0%
- FrontierMath Tier 42.4%
- WeirdML48.9%
- FrontierCode17.6%
- Chess Puzzles19.0%
- CL-bench Life13.5%
- ForecastBench55.6
- Mystery Game Puzzles17.0%
- Vending-Bench 23284.5
- Surface Evolver Bench40.0%
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 Pro
680 GB574.1 GB file
32K 680 GB · 128K 682 GB
MiMo V2.5 Pro
435 GB~434.9 GB file
32K 439 GB · 128K 449 GB
Q3_K_M
DeepSeek V4 Pro
780 GB748.7 GB file
32K 780 GB · 128K 782 GB
MiMo V2.5 Pro
499 GB459.7 GB file
32K 503 GB · 128K 513 GB
Q4_K_M
DeepSeek V4 Pro
960 GB954.6 GB file
32K 960 GB · 128K 961 GB
MiMo V2.5 Pro
614 GB629.6 GB file
32K 618 GB · 128K 628 GB
Q5_K_M
DeepSeek V4 Pro
1140 GB~1139.2 GB file
32K 1140 GB · 128K 1141 GB
MiMo V2.5 Pro
730 GB758.0 GB file
32K 733 GB · 128K 743 GB
Q6_K
DeepSeek V4 Pro
1319 GB~1319.0 GB file
32K 1320 GB · 128K 1321 GB
MiMo V2.5 Pro
845 GB846.6 GB file
32K 848 GB · 128K 859 GB
Q8_0
DeepSeek V4 Pro
1599 GB1671.8 GB file
32K 1600 GB · 128K 1601 GB
MiMo V2.5 Pro
1024 GB1087.6 GB file
32K 1027 GB · 128K 1038 GB
10 more quants
IQ2_XXS
DeepSeek V4 Pro
not listed
MiMo V2.5 Pro
282 GB317.2 GB file
32K 285 GB · 128K 296 GB
IQ2_S
DeepSeek V4 Pro
not listed
MiMo V2.5 Pro
320 GB319.4 GB file
32K 324 GB · 128K 334 GB
IQ2_M
DeepSeek V4 Pro
not listed
MiMo V2.5 Pro
346 GB317.3 GB file
32K 349 GB · 128K 360 GB
IQ3_XXS
DeepSeek V4 Pro
not listed
MiMo V2.5 Pro
397 GB412.7 GB file
32K 400 GB · 128K 411 GB
IQ3_S
DeepSeek V4 Pro
not listed
MiMo V2.5 Pro
435 GB377.9 GB file
32K 439 GB · 128K 449 GB
IQ4_XS
DeepSeek V4 Pro
not listed
MiMo V2.5 Pro
551 GB490.7 GB file
32K 554 GB · 128K 564 GB
IQ4_NL
DeepSeek V4 Pro
not listed
MiMo V2.5 Pro
576 GB501.3 GB file
32K 579 GB · 128K 590 GB
Q4_K_S
DeepSeek V4 Pro
not listed
MiMo V2.5 Pro
576 GB588.5 GB file
32K 579 GB · 128K 590 GB
Q5_K_S
DeepSeek V4 Pro
not listed
MiMo V2.5 Pro
704 GB713.2 GB file
32K 707 GB · 128K 718 GB
BF16
DeepSeek V4 Pro
3198 GB~3197.7 GB file
32K 3198 GB · 128K 3200 GB
MiMo V2.5 Pro
2047 GB2046.7 GB file
32K 2050 GB · 128K 2061 GB
DeepSeek V4 Pro
Ollama · Q4_K_M
ollama run hf.co/teamblobfish/DeepSeek-V4-Pro-GGUF:Q4_K_MMiMo V2.5 Pro
Ollama · Q4_K_M
ollama run hf.co/unsloth/MiMo-V2.5-Pro-GGUF:Q4_K_M| Spec | DeepSeek V4 Pro | MiMo V2.5 Pro |
|---|---|---|
| Publisher | DeepSeek | Xiaomi |
| Parameters | 1598.8B | 1023.2B |
| Active parameters | 51B per token | 44B per token |
| Architecture | DeepseekV4ForCausalLM | MiMoV2ForCausalLM |
| Context | 1M tokens | 1M tokens |
| Modalities | Chat | Chat, Function-calling, Code |
| License | MIT | MIT |
| Released | Apr 2026 | Apr 2026 |
Frequently Asked Questions
Which is better, DeepSeek V4 Pro or MiMo V2.5 Pro?
DeepSeek V4 Pro and MiMo V2.5 Pro match in llmrun Score, with values of 116.5 versus 116.4; neither fits 24 GB. Choose DeepSeek V4 Pro for stronger at science and stronger at reasoning; choose MiMo V2.5 Pro for lighter on memory and also does function-calling, code.
Which needs less VRAM, DeepSeek V4 Pro or MiMo V2.5 Pro?
At Q4_K_M, DeepSeek V4 Pro requires 959.6 GB while MiMo V2.5 Pro needs 614.5 GB, making MiMo V2.5 Pro the easier model to run on your local setup.
Can I run DeepSeek V4 Pro or MiMo V2.5 Pro on a 16 GB GPU?
DeepSeek V4 Pro does not fit (smallest quant needs 680 GB); MiMo V2.5 Pro does not fit (smallest quant needs 283.5 GB).
Which has a longer context window, DeepSeek V4 Pro or MiMo V2.5 Pro?
DeepSeek V4 Pro supports 1,048,576 tokens and MiMo V2.5 Pro supports 1,048,576 tokens.