Kimi K2 Thinking — Hardware Requirements & GPU Compatibility
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Kimi K2 Thinking is a 1058.1B-parameter open language model from Moonshot AI in the Kimi K2 family. It supports a context window of up to 262,144 tokens. At BF16 it needs about 2120.12 GB of VRAM — see which GPUs and Macs can run it below.
165.0K downloads
1.7K likesSpecifications
- Publisher
- Moonshot AI
- Family
- Kimi K2
- Parameters
- 1058.1B
- Architecture
- DeepseekV3ForCausalLM
- Context Length
- 262,144 tokens
- Vocabulary Size
- 163,840
- License
- Other
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HuggingFace
How Much VRAM Does Kimi K2 Thinking Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16 | 16.00 | 2120.1 GB | 2575.0 GB | 2116.24 GB | Brain floating point 16 — preferred for training |
Which GPUs Can Run Kimi K2 Thinking?
BF16 · 2120.1 GBKimi K2 Thinking (BF16) requires 2120.1 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 2757+ GB is recommended. Using the full 262K context window can add up to 454.9 GB, bringing total usage to 2575.0 GB. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Benchmarks
View all 1 →Related Models
Frequently Asked Questions
- How much VRAM does Kimi K2 Thinking need?
Kimi K2 Thinking requires 2120.1 GB of VRAM at BF16. Full 262K context adds up to 454.9 GB (2575.0 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 1058.1B × 16 bits ÷ 8 = 2116.2 GB
KV Cache + Overhead ≈ 3.9 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 458.8 GB (at full 262K context)
VRAM usage by quantization
BF162120.1 GBBF16 + full context2575.0 GB- Can NVIDIA GeForce RTX 5090 run Kimi K2 Thinking?
No — Kimi K2 Thinking requires at least 2120.1 GB at BF16, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- Can I run Kimi K2 Thinking on a Mac?
Kimi K2 Thinking requires at least 2120.1 GB at BF16, which exceeds the unified memory of most consumer Macs. You would need a Mac Studio or Mac Pro with a high-memory configuration.
- Can I run Kimi K2 Thinking locally?
Yes — Kimi K2 Thinking can run locally on consumer hardware. At BF16 quantization it needs 2120.1 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- What's the download size of Kimi K2 Thinking?
At BF16, the download is about 2116.24 GB.
- Which GPUs can run Kimi K2 Thinking?
No single consumer GPU has enough VRAM to run Kimi K2 Thinking at BF16 (2120.1 GB). Multi-GPU or professional hardware is required.
- Which devices can run Kimi K2 Thinking?
Kimi K2 Thinking requires at least 2120.1 GB at BF16, which exceeds the unified memory of most consumer devices. A high-memory Mac Studio, Mac Pro, or multi-GPU desktop setup is recommended.