Kimi K2.6 TPS calculator
Each card below is assessed against this model at the context length and minimum quality you choose. Speed is an estimate for a single request, calculated from the card's memory bandwidth and the size of the model once compressed.
Calculated for this model
Which GPUs can run Kimi K2.6?
Set the inputs, read the answer
A longer conversation needs more memory, which can push this model off smaller cards.
Hides cards that would only fit the model by compressing it below this point.
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Speeds are estimates for a single request — one conversation at a time — calculated from memory bandwidth, model size and quantisation. Real throughput varies with the inference runtime and its version. Figures published by hardware vendors measure many simultaneous requests and are much higher.
On record
Full specification
Everything on record for this model. Most of it describes how it was trained rather than how it runs — useful context for judging how much work went into it, and how it compares with models built at a different scale.
Origin
Who built this model, where, and when it was published.
- Organisation
- Moonshot
- Organisation type
- Industry
- Country
- China
- Published
- 20 April 2026
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Language
- Task
- Language modeling/generation
- Base model
- Kimi K2.5
Size
How large the model is and how much data it was trained on. Parameters are the figure that decides whether it fits on a given graphics card.
- Parameters
- 1T
- Training data
- tokens
Availability
Whether you can obtain the model and run it on your own hardware, which is what decides if any of the graphics-card figures on this page apply.
- Weights
- Open — downloadable
- Model access
- Open weights (unrestricted)
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Why it is tracked
- Discretionary
- Record confidence
- Confident
Cost-competitive and widely used in the open-weight AI industry
Sources
Where this record came from and when it was last checked.
- Reference
- Kimi K2.6: From Code to Creation, From One to Many
- Last updated
- 13 May 2026
What the numbers mean
What it takes to run this model
At 1T parameters, Kimi K2.6 is beyond what any single graphics card holds. Running it means either splitting it across several cards or renting hardware built for the job — 0 of the cards we track can hold it on their own, and all of them are datacentre parts.
About this model
Kimi K2.6 was published by Moonshot, in China, in April 2026. The organisation is categorised as industry.
It works in Language, and is recorded as doing language modeling/generation.
Its starting point was Kimi K2.5 — most models at this scale are adapted from an existing base rather than built from nothing.
The weights being open is what puts this page in the calculator rather than only in the catalogue: it is a model you can actually hold.
What went into building it
Its inclusion criterion is discretionary.
Step by step
How to choose a GPU for Kimi K2.6
The table above has already assessed every card we hold specifications for against this model. Getting to your answer takes six steps.
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01
Check what it needs before anything else
Every card here has been checked against Kimi K2.6. Capacity is the gate — a card either holds it or it does not.
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02
Match the context to your actual use
Longer conversations cost memory on top of what the weights need. Move the slider to your real working length before trusting any row for Kimi K2.6.
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03
Choose how far you will compress it
The quantisation column varies by card, because a bigger card holds a more accurate copy of Kimi K2.6. Set a floor to hold the comparison at one level.
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04
Sort by speed
The speed ordering for Kimi K2.6 is effectively an ordering by memory bandwidth.
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05
Check the fit verdict before buying
The fit column separates cards that just manage Kimi K2.6 from those with room to spare. Buy for the second if the context might grow.
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06
See what else that card runs
Following a card through to its own page shows every other model it can hold, which is the question that follows once Kimi K2.6 is settled.
Answers
Kimi K2.6 — common questions
Where can I download Kimi K2.6?
The weights for Kimi K2.6 are published, though we do not hold a repository link for it. This site calculates hardware requirements rather than hosting model files.
Can I run Kimi K2.6 if it does not fit in my GPU?
Only by offloading, which is usually a false economy: the part in system memory drags the whole thing down — the nearest miss we calculate is short by 370.7 GB. Our figures for Kimi K2.6 assume it is fully resident.
Would two GPUs run Kimi K2.6 faster?
Capacity adds across cards; throughput does not. Since 0 of the cards we track already hold Kimi K2.6 on their own, a second card is rarely the answer here.
Why does the quantisation differ between cards for Kimi K2.6?
Each card is shown running the least-compressed copy it can hold, and Kimi K2.6 appears at 1 different compression levels across the cards that fit it. Bigger cards get the more accurate version.
How accurate are these Kimi K2.6 speed estimates?
They are calculated from specifications rather than measured, and each carries a range — the range beneath each figure, for instance. The same model and card vary by thirty to fifty per cent depending on the inference software and its version.
Is Kimi K2.6 open source?
Its weights are published, so Kimi K2.6 can be downloaded and run on your own hardware. Note that open weights is not the same as open source in the full sense — it says nothing about the training data, the training code, or the commercial terms attached.
How many parameters does Kimi K2.6 have?
Kimi K2.6 has 1T parameters. That figure is the total, and it is what decides how much memory the model needs — roughly half a gigabyte per billion at the compression most people use.
Who created Kimi K2.6?
Kimi K2.6 was published by Moonshot, based in China, categorised as industry.
When was Kimi K2.6 released?
Kimi K2.6 was published in April 2026.
What is Kimi K2.6 used for?
Kimi K2.6 works in Language, and is recorded as handling language modeling/generation. These are the areas it was designed around; they describe intent rather than a hard boundary.
The other direction
Looking at it from the other side?
This page starts from the model. If you already own a card and want to know everything it will run, start from the hardware instead.