Kimi VL A3B

16.4B total, 3B active · 128k context · MIT · released 2025-04-09

visionagenticchatreasoning

In short

Kimi VL A3B is an open model from Moonshot AI with 16.4B parameters (3B active per token). At mlx-5bit, Kimi VL A3B needs about 12 GB of memory at 8k context and 13 GB at 32k, counting the weights, the KV cache and runtime buffers. The cheapest hardware in Germany that runs Kimi VL A3B fully in memory at 32k context is the NVIDIA Tesla P40, 369 € at eBay, at about 30 tok/s (estimated).

Updated . Speeds are estimates; how they are worked out.

What to run it on in Germany

Fully in memory at 32k context, priced at retailers today.

All hardware that runs it

Everything we price, best value first. Two cards split the model by layers.

HardwareQuantFitsDecodePricetok/s per 1,000
NVIDIA Tesla P40mlx-8bitfits30 tok/s369 €81.6
AMD Radeon RX 9060 XT 16GBmlx-6bitfits30 tok/s550 €54.2
Intel Arc A770 16GBmlx-6bitfits43 tok/s646 €67.2
NVIDIA GeForce RTX 4060 Ti 16GBmlx-6bitfits30 tok/s650 €46.5
NVIDIA GeForce RTX 5060 Ti 16GBmlx-6bitfits47 tok/s739 €63.6
AMD Radeon RX 9070 XTmlx-6bitfits60 tok/s778 €76.5
AMD Radeon RX 7600 XTmlx-6bitfits27 tok/s813 €33.0
AMD Radeon RX 7900 XTmlx-8bitfits62 tok/s855 €72.2
AMD Radeon RX 7800 XTmlx-6bitfits58 tok/s1.002 €57.9
Intel Arc Pro B60mlx-8bitfits29 tok/s1.074 €27.3
NVIDIA GeForce RTX 4080 Supermlx-6bitfits77 tok/s1.100 €70.2
NVIDIA GeForce RTX 5070 Timlx-6bitfits94 tok/s1.149 €81.7
NVIDIA GeForce RTX 4070 Ti Supermlx-6bitfits71 tok/s1.247 €56.5
Mac mini M4 32GBmlx-8bitfits11 tok/s1.400 €7.8
NVIDIA GeForce RTX 5080mlx-6bitfits101 tok/s1.500 €67.1
AMD Radeon RX 7900 XTXmlx-8bitfits74 tok/s1.555 €47.6
NVIDIA GeForce RTX 3090mlx-8bitfits81 tok/s1.850 €44.0
AMD Radeon AI PRO R9700mlx-8bitfits49 tok/s1.867 €26.5
NVIDIA GeForce RTX 3090 Timlx-8bitfits88 tok/s2.500 €35.0
Mac mini M4 Pro 48GBmlx-8bitfits25 tok/s2.699 €9.2
Mac mini M4 Pro 64GBmlx-8bitfits25 tok/s2.799 €8.9
GMKtec EVO-X2 Ryzen AI Max+ 395 128GBmlx-8bitfits20 tok/s3.700 €5.3
NVIDIA GeForce RTX 4090mlx-8bitfits88 tok/s3.955 €22.1
Mac Studio M4 Max 64GBmlx-8bitfits50 tok/s4.183 €11.9
Mac Studio M4 Max 128GBmlx-8bitfits50 tok/s5.800 €8.6
Mac Studio M3 Ultra 96GBmlx-8bitfits75 tok/s5.999 €12.4
NVIDIA GeForce RTX 5090mlx-8bitfits156 tok/s6.028 €25.8
NVIDIA DGX Spark 128GBmlx-8bitfits24 tok/s8.313 €2.9
ASUS Ascent GX10 128GBmlx-8bitfits24 tok/s8.623 €2.7
Mac Studio M3 Ultra 256GBmlx-8bitfits75 tok/s15.555 €4.8
Mac Studio M3 Ultra 512GBmlx-8bitfits75 tok/s18.995 €3.9
NVIDIA RTX PRO 6000 Blackwellmlx-8bitfits156 tok/s19.076 €8.2
Framework Desktop Ryzen AI Max+ 395 128GBmlx-8bitfits20 tok/s––
Framework Desktop Ryzen AI Max+ 395 64GBmlx-8bitfits20 tok/s––
NVIDIA GeForce RTX 3060 12GBmlx-5bitoffload30 tok/s309 €98.4
Intel Arc B580mlx-5bitoffload27 tok/s360 €74.2
NVIDIA GeForce RTX 3080 10GBmlx-5bitoffload27 tok/s500 €54.8
NVIDIA GeForce RTX 5070mlx-5bitoffload43 tok/s699 €61.7
NVIDIA GeForce RTX 4070 Supermlx-5bitoffload37 tok/s707 €52.6

1 other card or machine we price cannot hold it at this context.

Memory needed

Weights, KV cache and runtime buffers at each context length (KV cache at fp16).

QuantFile@8k@32k@64k@128k
mlx-5bitmlx11.0 GB12.0 GB12.9 GB14.0 GB16.3 GB
mlx-6bitmlx12.9 GB13.9 GB14.7 GB15.9 GB18.1 GB
mlx-8bitmlx16.6 GB17.6 GB18.4 GB19.6 GB21.8 GB

Run it

Copy a command for the runtime you use.

  • mlx-5bit
    • LM Studiolms get mlx-community/Kimi-VL-A3B-Thinking-2506-5bit
    • MLXmlx_lm.server --model mlx-community/Kimi-VL-A3B-Thinking-2506-5bit
  • mlx-6bit
    • LM Studiolms get mlx-community/Kimi-VL-A3B-Thinking-2506-6bit
    • MLXmlx_lm.server --model mlx-community/Kimi-VL-A3B-Thinking-2506-6bit
  • mlx-8bit
    • LM Studiolms get mlx-community/Kimi-VL-A3B-Thinking-2506-8bit
    • MLXmlx_lm.server --model mlx-community/Kimi-VL-A3B-Thinking-2506-8bit

Notes

MoE vision-language model with 16B total and about 3B active parameters; it needs trust_remote_code and was developed against transformers 4.48.2. vLLM support needed a branch from an unmerged pull request (#16387) when the card was written.

Questions

How much VRAM does Kimi VL A3B need?
At mlx-5bit, Kimi VL A3B needs about 12 GB of memory at 8k context and 13 GB at 32k, counting the weights, the KV cache and runtime buffers.
What is the best GPU for running Kimi VL A3B locally?
The cheapest hardware in Germany that runs Kimi VL A3B fully in memory at 32k context is the NVIDIA Tesla P40, 369 € at eBay, at about 30 tok/s (estimated). The best value is the NVIDIA GeForce RTX 5070 Ti (about 94 tok/s for 1.149 €). The fastest we price is the NVIDIA GeForce RTX 5090, at about 156 tok/s.
Can I run Kimi VL A3B on a 16 GB GPU?
Yes: at mlx-6bit it fits fully in 16 GB at 32k context. On the NVIDIA GeForce RTX 5080 it runs at about 101 tok/s (estimated).
Can I run Kimi VL A3B on a 24 GB GPU?
Yes: at mlx-8bit it fits fully in 24 GB at 32k context. On the NVIDIA GeForce RTX 3090 Ti it runs at about 88 tok/s (estimated).
What licence is Kimi VL A3B released under?
MIT, which allows commercial use.