LLMMiniMaxMIT

MiniMax-M1-80B

MiniMaxAI/MiniMax-M1-80B

MiniMax M1, 80B reasoning model with strong coding benchmarks.

Parameters

80B

Context

128K

Downloads

180K

Likes

900

Architecture

llama

View on HuggingFace

GPU Requirements

VRAM / RAM / disk estimates by quantization and usage scenario

QuantizationMinimumRecommendedProduction
FP1616bit
193.5 GB
RAM 290.2 · Disk 271.5
217.8 GB
RAM 326.7 · Disk 297.5
323.2 GB
RAM 484.9 · Disk 336.5
FP88bit
99.2 GB
RAM 148.8 · Disk 155.2
119.2 GB
RAM 178.9 · Disk 181.2
220.4 GB
RAM 330.6 · Disk 220.2
INT88bit
99.2 GB
RAM 148.8 · Disk 155.2
119.2 GB
RAM 178.9 · Disk 181.2
220.4 GB
RAM 330.6 · Disk 220.2
AWQ4bit
53.8 GB
RAM 80.8 · Disk 99.3
71.8 GB
RAM 107.7 · Disk 125.3
170.9 GB
RAM 256.4 · Disk 164.3
GPTQ4bit
54.4 GB
RAM 81.7 · Disk 100.0
72.4 GB
RAM 108.7 · Disk 126.0
171.6 GB
RAM 257.4 · Disk 165.0
GGUF4bit
55.6 GB
RAM 83.4 · Disk 101.5
73.7 GB
RAM 110.5 · Disk 127.5
172.9 GB
RAM 259.3 · Disk 166.5

GPU Recommendations

Best ValueBEST

1× H200 SXM

141 GB VRAM

$2,555/mo

≈ 124.2 tok/s

Effective production throughput ≈ 86.9 tok/s

score 0.6069

Cheapest

8× Tesla V100

128 GB VRAM

$169/mo

≈ 0 tok/s (N/A — benchmark unavailable)

Effective production throughput ≈ 0 tok/s

score 0.5061

Deploy on vast ↗
Performance

8× H200 SXM

1128 GB VRAM

$20,440/mo

≈ 397.4 tok/s

Effective production throughput ≈ 278.2 tok/s

score 0.2197

Min Complexity

1× A100 80GB

80 GB VRAM

$876/mo

≈ 52.8 tok/s

Effective production throughput ≈ 37 tok/s

score 0.6469

Deploy on vast ↗

💬 Community — real deployment experience

0 Articles · 0 Benchmarks

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GPUs that fit (single card)

A100 80GB

80 GB VRAM

$876

/mo · vast

H100 SXM

80 GB VRAM

$1,170

/mo · vast

H200 SXM

141 GB VRAM

$2,555

/mo · lambda

B200

180 GB VRAM

$3,013

/mo · vast

B200 SXM

180 GB VRAM

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