Kimi K2 Base — Hardware Requirements & GPU Compatibility
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Kimi K2 Base is a 1026.5B-parameter open language model from Moonshot AI in the Kimi K2 family. It supports a context window of up to 131,072 tokens. At Q4_K_M it needs about 619.76 GB of VRAM — see which GPUs and Macs can run it below.
Kimi K2 Base runs on a multi-GPU server
Q4_K_M needs ~617.3 GB · about 5× H200 SXM 141 GB · or Mac Studio (M3 Ultra, 512GB) at Q3_K_M (~25 tok/s)
Macs from 512 GB (Q3_K_M · ~25 tok/s)
Other
Not set up for it?
Reference GPU · RTX 4090 24 GB
Estimates, ±20% · how we estimate
Run Kimi K2 Base
One recommended way. Every other method, OS and quant is in the step-by-step guide.
Recommended
vllm serve moonshotai/Kimi-K2-Base --max-model-len 16384 --tensor-parallel-size 8Size the nodes from the table above
Download: Weights on Hugging Face
Other ways
each opens step-by-stepRun in cloud
Rent 5× H200 SXM · Q4_K_M
- Estimated hourly price
- ~$17.95/hr
- est., whole server
- GPUs
- 5 GPUs
- 705 GB of VRAM
How Much VRAM Does Kimi K2 Base Need?
Select a quantization level; the listed hardware adheres to it.
| Quantization | VRAM | +32K | Runs on | |
|---|---|---|---|---|
| 440.1 GB | 438.9 GB | 2-bit · K-quant — 2-bit quantization with K-quant improvements | Runs on 7× H100 SXM 80 GB | |
| 504.3 GB | 503 GB | 3-bit medium — 3-bit medium quantization | Runs on 7× H100 SXM 80 GB | |
| 619.8 GB | 618.5 GB | 4-bit medium — 4-bit medium quantization — most popular sweet spot | Runs on 5× H200 SXM 141 GB | |
| 735.2 GB | 734 GB | 5-bit medium — 5-bit medium quantization — good quality/size tradeoff | Runs on 6× H200 SXM 141 GB | |
| 850.7 GB | 849.4 GB | 6-bit, very good — 6-bit quantization, very good quality | Runs on 7× H200 SXM 141 GB | |
| 1030.3 GB | 1029.1 GB | 8-bit, near-lossless — 8-bit quantization, near-lossless | Runs on 6× B200 192 GB | |
| 2056.8 GB | 2055.5 GB | 16-bit · bfloat — Brain floating point 16 — preferred for training | Runs on 4 nodes of 8× H100 SXM |
Selected Q4_K_M
4-bit medium quantization617.3GBat 16K context
- Weights
- 615.9 GB
- KV cache
- 1.2 GB
- Overhead
- 0.3 GB
Server-class: ~617.3 GB at 16K context · about 5× H200 SXM 141 GB
Which Hardware Can Run Kimi K2 Base?
Q4_K_M · 619.8 GBKimi K2 Base (Q4_K_M) requires 619.8 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 806+ GB is recommended. Using the full 131K context window can add up to 5.6 GB, bringing total usage to 625.4 GB. No consumer GPU has enough memory.
Needs server-class hardware
Kimi K2 Base runs on a multi-GPU server · Q4_K_M needs ~617.3 GB
| Hardware | Quant | Memory | Speed | Context | Hardware page | |
|---|---|---|---|---|---|---|
| Mac 512 GB · Mac Studio (M3 Ultra, 512GB) | Q3_K_M | 501.9 GB | ~25 tok/s | 64K ctx | Mac Studio → | Q3_K_M · 501.9 GB · ~25 tok/s · 64K ctx |
| 8× H100 SXM 80 GB · 640 GB | Q3_K_M | 501.9 GB | — | 128K ctx | H100 SXM → | Q3_K_M · 501.9 GB · 128K ctx |
| 5× H200 SXM 141 GB · 705 GB | Q4_K_M | 617.3 GB | — | 128K ctx | H200 SXM → | Q4_K_M · 617.3 GB · 128K ctx |
| 4× B200 192 GB · 768 GB | Q4_K_M | 617.3 GB | — | 128K ctx | B200 → | Q4_K_M · 617.3 GB · 128K ctx |
Also: NVIDIA DGX A100 640GB · NVIDIA DGX H100
By VRAM tier · typical GPUs and Macs at Q4_K_M
Consumer GPUs (up to 32 GB) and Macs up to 256 GB: too small for this model (needs ≥ 437.7 GB)8 GB tier →12 GB tier →16 GB tier →24 GB tier →Macs →
Alternatives to Kimi K2 Base
Kimi K2 family · 8 models →Similar models
4| Model | Score | VRAM | tok/s | Why it is similar |
|---|---|---|---|---|
| MiMo V2.5 ProXiaomi | 116.4 | 616 GB | —needs > 24 GB | same size |
| InklingThinking Machines | 116.0 | 575.1 GB | —needs > 24 GB | same size |
| MiMo V2.6 Pro MOPDXiaomi | — | 614.1 GB | —needs > 24 GB | same size |
| Ring 2.6 1TInclusion AI | — | 2052.6 GB | —needs > 24 GB | same size |
Specifications
- Publisher
- Moonshot AI
- Family
- Kimi K2
- Parameters
- 1026.5B
- Active parameters
- 32.9B per token
- Architecture
- DeepseekV3ForCausalLM
- Context Length
- 131,072 tokens
- Vocabulary Size
- 163,840
- Release Date
- 2025-07-03
- License
- Other
Frequently Asked Questions
How much VRAM does Kimi K2 Base need?
Kimi K2 Base requires 619.8 GB of VRAM at Q4_K_M, or 2056.8 GB at BF16. Full 131K context adds up to 5.6 GB (625.4 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 1026.5B × 4.8 bits ÷ 8 = 615.9 GB
KV Cache + Overhead ≈ 3.9 GB (at 2K context + ~0.3 GB framework)
Fit ratings and hardware model lists check this model with room for a 16K-token context, which needs a little more memory.
KV Cache + Overhead ≈ 9.5 GB (at full 131K context)
VRAM usage by quantization
Can NVIDIA GeForce RTX 5090 run Kimi K2 Base?
No — Kimi K2 Base requires at least 440.1 GB at Q2_K, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
What's the best quantization for Kimi K2 Base?
For Kimi K2 Base, Q4_K_M (619.8 GB) offers the best balance of quality and VRAM usage. Q5_K_M (735.2 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 440.1 GB.
VRAM requirement by quantization
★ Recommended — best balance of quality and VRAM usage.
Can I run Kimi K2 Base on a Mac?
Yes, but only at lower quantizations. The smallest Mac that can run Kimi K2 Base is Mac Studio (M3 Ultra, 512GB) at Q3_K_M; 1 of the 146 Macs we list can run it at some quantization. For Q4_K_M (619.8 GB) you need a Mac with more unified memory.
Can I run Kimi K2 Base locally?
Yes — Kimi K2 Base can run locally on consumer hardware. Popular tools include Ollama, LM Studio, and llama.cpp.
What's the download size of Kimi K2 Base?
At Q4_K_M, the download is about 615.88 GB. The full-precision BF16 version is 2052.94 GB. The smallest option (Q2_K) is 436.25 GB.
Which GPUs can run Kimi K2 Base?
No single consumer GPU has enough VRAM to run Kimi K2 Base at Q4_K_M (619.8 GB). Multi-GPU or professional hardware is required.
Which devices can run Kimi K2 Base?
Kimi K2 Base requires at least 619.8 GB at Q4_K_M, which exceeds the usable memory of every unified-memory device we list (the largest has 508.5 GB).