Kimi K3.1 Pro: VRAM requirements by quant
Key facts
Kimi K3.1 Pro needs at least 1,680.8 GB at standard quality (Q4, estimate).
Checked . model card.
Kimi K3.1 Pro is a very large open AI model. It needs at least 1681 GB of memory at standard quality, more than any PC or Mac we track. Models this size usually run on rented servers.
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Open full 8-model playground ↗Before the open weights for Kimi K3.1 Pro land on 4 November 2026 (2.8T sparse mixture of experts; a flat 4-bit file is about 1.4 TB, a multi-node cluster), you can test 10 open LLMs free in your browser at https://localllmrig.com/ with no login and 0 GB of local VRAM. The prompts below run Recursive Flint and Gemma 4 31B. Kimi K3.1 Pro is already on the pass at $2 per million input tokens and $10 per million output tokens, so trying it in the chat needs a pass.
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Memory needed
At least 1681 GB
At standard quality, for the model alone. The conversation needs more on top.
Cheapest machine that runs it
None of ours
It needs more than any PC or Mac we track.
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Can a PC or Mac run Kimi K3.1 Pro?
None of the PCs or Macs we track can hold Kimi K3.1 Pro: it needs at least 1681 GB. Models this size usually run on rented servers. What renting costs
Speeds and memory are our estimate from the hardware specs, not a measured test. Prices are dated and may change. How we calculate
Memory at each quality level
A lower quality level makes the model smaller, so it fits on a smaller machine. Standard (Q4) is what most people run.
| Quality | Memory needed |
|---|---|
| Q4 · standard (smallest that keeps quality) | 1,680.8 GB |
| Q5 · a bit sharper, a bit bigger | 1,988.8 GB |
| Q8 · near full quality, almost twice Q4 | 2,996.8 GB |
| FP16 · full quality, over three times Q4 | 5,600.8 GB |
These figures leave out the conversation. We cannot estimate how much memory it takes for this model's design, so real use needs more.
Sources and method
At standard quality: 1,680.0 GB for the model itself, the conversation not estimated, and 0.8 GB for the software.
Size source: openrouter.ai/moonshotai/kimi-k3.1-pro. The published size is rounded, so ours is an estimate.
Moonshot AI's sparse mixture of experts, stated as 2.8T total parameters, the same total class as Kimi K3. This row has no counted weight file and no config: on 26 Oct 2026 the OpenRouter models API listed no Hugging Face repo. A flat 4 bits per weight is 0.5 bytes per parameter, so 2.8T weights are 1,400 GB (1.4 TB). This site's Q4 estimate uses 0.60 bytes per parameter, 1,680.0 GB of weights plus 0.80 GB of working space (1,680.8 GB). Layer count, KV heads and the active-parameter count are not published, so conversation memory is not counted. Moonshot says the open-weight GGUF and FP8 checkpoints arrive on 4 November 2026. Until then the model is API-live as moonshotai/kimi-k3.1-pro. The default Moonshot endpoint is MXFP4 at $2 per million input tokens and $10 per million output tokens, and a cached input read is $0.20 per million. A file this size is a multi-node cluster. You can test it with a pass, or compare it with open models, at https://localllmrig.com/.
Licence
Commercial use: check licence
Licence not confirmed. Read the model card before commercial use.
Licence: Not published yet · checked 26 Oct 2026
Our reading of the licence, not legal advice.
Will Kimi K3.1 Pro run on my graphics card?
Common questions
- How much memory does Kimi K3.1 Pro need?
- About 1,680.8 GB at standard quality (Q4) with a conversation of 8,192 tokens: 1,680.0 GB for the model itself and 0.8 GB for the software. We cannot estimate the memory the conversation takes for this model's design, so real use needs more.
- Does Kimi K3.1 Pro fit on a single 24 GB graphics card?
- Not in full. It needs about 1,680.8 GB, and a 24 GB card leaves about 23.4 GB usable.
- Are the speeds measured?
- We do not show a speed for this model. It is a mixture-of-experts model, and our estimate would not be reliable for that design.