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Inkling

MoEVision

TThinking Machines Lab · 952.4B (41B active) · Mixture of experts

Inkling is a 952.4B model from Thinking Machines Lab with a 1M-token context. At Q4_K_M with an 8K context it needs about 534 GB; 669 GB leaves room for longer chats.

Hugging Face GGUF

Mixture of experts

Parameters: 952.4B · Active: 41B

All 952.4B parameters load into memory, but only 41B work on each token, so it runs at the speed of a much smaller model.

Quantization options

QuantMemoryOn your hardware
Q2_K—…
Q3_K_M—…
Q4_K_M—…
Q5_K_M—…
Q6_K—…
Q8_0—…
F16—…

Memory by context length

At Q4_K_M. The context cache grows with every token the model keeps in mind.

ContextContext cacheTotal
4K0.4 GB533.9 GB
8K0.6 GB534 GB
32K1.6 GB535.1 GB
128K5.7 GB539.2 GB
256K11.2 GB544.7 GB

Share a measured speed

Run one of these and paste the whole output below (or just the tokens per second):

llama-bench -m model.gguf
ollama run model --verbose

Published anonymously and kept. We store no account or address, only a daily-changing hash for a limit of ten submissions a day.

Next steps

Least hardware that runs it well

Desktop devices with the least memory that give Inkling grade A or S at Q4_K_M.

No desktop device in our catalog runs it at grade A or better.

Can I run Inkling locally?

Can I run Inkling locally?

Yes, if your GPU or Mac has about 534 GB free for it at Q4_K_M. Open this page on that computer to see the grade for your exact hardware, then start it with llama.cpp, Ollama or LM Studio.

How much memory does Inkling need?

About 534 GB at Q4_K_M with an 8K context and 798.8 GB at Q8_0. Lower quantizations fit smaller cards with some loss in quality; longer contexts add to the total.