Family Kimi · 1000B parameters

Kimi K2.5

1T/32B-active multimodal MoE. 'Agent swarm' mode. 595 GB of weights. For serious home labs.

🇨🇳 Moonshot AI·License Modified MIT·Context 250k tokens·Output January 2026← Catalog

01What it can do

Strengths
  • 1 trillion parameters
  • Swarm agent mode
  • 256k ctx
Limitations to know
  • —600 GB in Q4 — serious home lab only
  • —Modified MIT License to verify
Architecture
1T/32B active MoE · multimodal · 'agent swarm' mode · 256k ctx
Training
The largest practical open-weight model.
Ideal for
Home-lab frontierComplex agents

04Install

Install Ollama for your OS. Check the model and its quantization before downloading. Start with 4096 tokens of context, then check placement with ollama ps. A command below is not proof that a test was run on your machine.

$# HuggingFace : moonshotai/Kimi-K2.5
⚠
First download: between 2 and 40 GB depending on the selected quantization. Plan for sufficient disk space; a stable connection is recommended. Subsequent launches are instant.

02Required memory

Approximate GPU VRAM required to run this model, including 4k tokens of context overhead. For a longer context, add ~1 GB per 8k-token increment.

Q4_K_M
The lightest, ~5% loss
600 GB
Q5_K_M
Good quality/size compromise
720 GB
Q8_0
Nearly indistinguishable from FP16
1080 GB
FP16
Full precision — server use
2000 GB
Fallback CPU · If you don't have a GPU, allow 700 GB of RAM minimum to run this model at reduced speed.

What hardware do you need for Kimi K2.5?

To run Kimi K2.5 locally with Q4 quantization, you need about 600 GB of VRAM. An option to compare: BOSGAME M5 128GB / 2TB (Ryzen AI Max+ 395) — this model exceeds this mini-PC's GPU capacity: choose a smaller model or suitable infrastructure.

Current offer: BOSGAME M5 128GB / 2TB (Ryzen AI Max+ 395)
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Why this choice? Our complete guide on BOSGAME M5 128GB / 2TB (Ryzen AI Max+ 395) →

Affiliate links — commission possible at no extra cost to you; independent recommendations. As an Amazon Associate, BestLLMfor earns from qualifying purchases.

This model in your private ChatGPT, without the cloud

Too large for your machine? The kit gives you the model that fits in your VRAM

  • Lifetime online access
  • PDF + files
  • Lifetime updates

03Expected speed

Tokens generated per second in Q4_K_M, 4k context. Beyond 20 t/s, reading is comfortable. Below 10 t/s, that's just for testing.

Entry-level
~1t/s
GTX 1650, RX 6600, MBA M2 8GB
Mid-range
~4t/s
RTX 4060, 4070, MBP M3 Pro
High-end
~12t/s
RTX 4090, M4 Max, Radeon 7900