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Home › Families › MiniMaxAI

MiniMax-M2 MiniMaxAI

LLMsMoE 1 members 58 derivatives on the Hub Last verified 2026-10-25 RSS

quantized: 39finetune: 15adapter: 2merge: 2

Which ones matter

Picks are rule-based from observed data (score, downloads, size, hosting); they are not quality verdicts.

Members 1

1 rows
# Model Org Role Params Band MoE License ContextProviders Price from Likes Likes 7d Downloads 30d Modified
101 MiniMax-M2 MiniMaxAI Original release (shipped quantized… 229B XXL MoE MiniMax (Modified MIT) (mod… 192K3 $0.26 1.5k +4 117k 2025-12-23

Variants 58 shown of 58

Quantizations, fine-tunes, merges, and adapters of any member, ranked by downloads + likes. Filter by relation, quant family, or size band.

Relation
Quant
Size
58 rows
Variant Of Relation Quant Params Band License Author Likes Downloads
QuantTrio/MiniMax-M2-AWQ MiniMaxAI/MiniMax-M2 quantized AWQ 229B XXL apache-2.0 QuantTrio 10 1.3M
lmstudio-community/MiniMax-M2-MLX-8bit MiniMaxAI/MiniMax-M2 quantized MLX 229B XXL mit lmstudio-community 1 191.9k
lmstudio-community/MiniMax-M2-MLX-4bit MiniMaxAI/MiniMax-M2 quantized MLX 229B XXL mit lmstudio-community 0 176k
lmstudio-community/MiniMax-M2-MLX-6bit MiniMaxAI/MiniMax-M2 quantized MLX 229B XXL mit lmstudio-community 0 172.6k
unsloth/MiniMax-M2-GGUF MiniMaxAI/MiniMax-M2 quantized GGUF — — mit unsloth 90 157.1k
bartowski/MiniMaxAI_MiniMax-M2-GGUF MiniMaxAI/MiniMax-M2 quantized GGUF — — — bartowski 11 22.4k
lemuralabs/MiniMax-M2-Pruned-25 MiniMaxAI/MiniMax-M2 finetune — 173B XXL mit lemuralabs 36 20.8k
mlx-community/MiniMax-M2-4bit MiniMaxAI/MiniMax-M2 quantized -4bit 229B XXL mit mlx-community 10 18.3k
lmstudio-community/MiniMax-M2-GGUF MiniMaxAI/MiniMax-M2 quantized GGUF — — mit lmstudio-community 1 17.3k
redponike/MiniMax-M2-GGUF MiniMaxAI/MiniMax-M2 quantized GGUF — — mit redponike 2 15.6k
cturan/MiniMax-M2-GGUF MiniMaxAI/MiniMax-M2 quantized GGUF — — mit cturan 15 12.9k
DevQuasar/MiniMaxAI.MiniMax-M2-GGUF MiniMaxAI/MiniMax-M2 quantized GGUF — — — DevQuasar 15 11k
cerebras/MiniMax-M2-REAP-162B-A10B MiniMaxAI/MiniMax-M2 quantized — 162B XXL other cerebras 80 6.4k
OsaurusAI/MiniMax-M2.7-Small-JANGTQ MiniMaxAI/MiniMax-M2 finetune — 12.5B L other OsaurusAI 26 7.6k
ModelCloud/MiniMax-M2-GPTQMODEL-W4A16 MiniMaxAI/MiniMax-M2 quantized GPTQ 229B XXL other ModelCloud 3 8.5k
bullerwins/MiniMax-M2-GGUF MiniMaxAI/MiniMax-M2 quantized GGUF — — mit bullerwins 6 7.7k
tiny-random/minimax-m2 MiniMaxAI/MiniMax-M2 finetune — 3.31M S — tiny-random 0 6.9k
mlx-community/MiniMax-M2-8bit MiniMaxAI/MiniMax-M2 quantized -8bit 229B XXL mit mlx-community 8 4.7k
mlx-community/MiniMax-M2-3bit MiniMaxAI/MiniMax-M2 quantized — 229B XXL mit mlx-community 3 4.4k
cerebras/MiniMax-M2-REAP-139B-A10B MiniMaxAI/MiniMax-M2 quantized — 139B XXL other cerebras 18 3.2k
lukealonso/MiniMax-M2-NVFP4 MiniMaxAI/MiniMax-M2 quantized NVFP4 115B XXL — lukealonso 14 3.2k
cerebras/MiniMax-M2-REAP-172B-A10B MiniMaxAI/MiniMax-M2 quantized — 173B XXL other cerebras 23 2.5k
Intel/MiniMax-M2-gguf-q2ks-mixed-AutoRound MiniMaxAI/MiniMax-M2 quantized gguf — — — Intel 8 2.8k
moxin-org/MiniMax-M2-GGUF MiniMaxAI/MiniMax-M2 quantized GGUF — — mit moxin-org 6 2.8k
cyankiwi/MiniMax-M2-AWQ-4bit MiniMaxAI/MiniMax-M2 quantized AWQ 36.8B XL other cyankiwi 4 2.5k
lemuralabs/MiniMax-M2-Pruned-55 MiniMaxAI/MiniMax-M2 finetune — 106B XXL mit lemuralabs 5 2.3k
mradermacher/MiniMax-M2-i1-GGUF MiniMaxAI/MiniMax-M2 quantized GGUF — — other mradermacher 8 2k
mlx-community/MiniMax-M2-5bit MiniMaxAI/MiniMax-M2 quantized — 229B XXL mit mlx-community 2 2.2k
mlx-community/MiniMax-M2-6bit MiniMaxAI/MiniMax-M2 quantized — 229B XXL mit mlx-community 2 2.2k
ilintar/MiniMax-M2-GGUF MiniMaxAI/MiniMax-M2 quantized GGUF — — mit ilintar 3 1.8k
ModelCloud/MiniMax-M2-BF16 MiniMaxAI/MiniMax-M2 finetune -BF16 229B XXL mit ModelCloud 3 1.6k
yujiepan/minimax-m2-tiny-random MiniMaxAI/MiniMax-M2 finetune — 3.31M S — yujiepan 0 1.4k
anikifoss/MiniMax-M2-HQ4_K MiniMaxAI/MiniMax-M2 quantized GGUF — — mit anikifoss 2 1.1k
turboderp/MiniMax-M2-exl3 MiniMaxAI/MiniMax-M2 quantized exl3 — — mit turboderp 8 213
ArtusDev/MiniMaxAI_MiniMax-M2-EXL3 MiniMaxAI/MiniMax-M2 quantized EXL3 — — mit ArtusDev 5 355
a2s-ai/MiniMax-M2-AWQ MiniMaxAI/MiniMax-M2 quantized AWQ 229B XXL apache-2.0 a2s-ai 0 562
KikoCis/minimax-m2-expert-prune-heal MiniMaxAI/MiniMax-M2 quantized GGUF — — apache-2.0 KikoCis 1 439
gauravmm/MiniMax-M2.5-REAP-139B-A10B-NVFP4 MiniMaxAI/MiniMax-M2 quantized NVFP4 78.8B XL other gauravmm 1 345
avtc/MiniMax-M2-GPTQMODEL-W4A16 MiniMaxAI/MiniMax-M2 quantized GPTQ 229B XXL other avtc 0 388
morriszjm/MiniMax-M2.5-192e MiniMaxAI/MiniMax-M2 quantized — 173B XXL other morriszjm 0 277
Trilogix1/MiniMax-M2-abliterated-GGUF MiniMaxAI/MiniMax-M2 quantized GGUF — — other Trilogix1 0 260
AbteeXAILab/lumynax-frontier-minimax-m2-230b MiniMaxAI/MiniMax-M2 quantized GGUF — — other AbteeXAILab 0 167
Open4bits/MiniMax-M2-GGUF MiniMaxAI/MiniMax-M2 quantized GGUF — — other Open4bits 0 166
morriszjm/MiniMax-M2.5-128e MiniMaxAI/MiniMax-M2 quantized — 116B XXL other morriszjm 0 155
ludovicoYIN/MiniMax-M2-BF16-W4A16 MiniMaxAI/MiniMax-M2 quantized -BF16 33.8B L other ludovicoYIN 0 107
Jonwi0706/Quantumpsychicrealm MiniMaxAI/MiniMax-M2 adapter — — — apache-2.0 Jonwi0706 2 0
Mark227p/Mark MiniMaxAI/MiniMax-M2 merge — — — etalab-2.0 Mark227p 1 0
UNYIL17/MODEL-ONE-1 MiniMaxAI/MiniMax-M2 merge — — — apache-2.0 UNYIL17 1 0
bcharankumar/texttoimage MiniMaxAI/MiniMax-M2 finetune — — — openrail bcharankumar 0 0
hjxkjVCJKv/kuomiko_ai_v1 MiniMaxAI/MiniMax-M2 finetune — — — llama4 hjxkjVCJKv 0 0
Jansimor22/Lalma_2.0 MiniMaxAI/MiniMax-M2 finetune — — — apache-2.0 Jansimor22 0 0
mradermacher/MiniMax-M2-GGUF MiniMaxAI/MiniMax-M2 finetune GGUF — — other mradermacher 0 0
radityasua/R.2.2 MiniMaxAI/MiniMax-M2 finetune — — — — radityasua 0 0
cartiervaclavpol/Minimiosfromarturandminioms MiniMaxAI/MiniMax-M2 finetune — — — — cartiervaclavpol 0 0
princewinter21/catgpt_V2 MiniMaxAI/MiniMax-M2 finetune — — — llama4 princewinter21 0 0
theofdanny/sora2-for-free MiniMaxAI/MiniMax-M2 finetune — — — openrail theofdanny 0 0
emphaticfir25/GPT_6.9 MiniMaxAI/MiniMax-M2 finetune — — — mit emphaticfir25 0 0
Stonesy4444/Stones MiniMaxAI/MiniMax-M2 adapter — — — apache-2.0 Stonesy4444 0 0

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