Mistral 3 Large 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
818 cards we hold specifications for
Which GPUs can run Mistral 3 Large?
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.
0 cards match
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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
- Mistral AI
- Organisation type
- Industry
- Country
- France
- Published
- 2 December 2025
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Language
- Task
- Language modeling/generation
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
- 675B
- Training data
- tokens
"Mistral Large 3 – our most capable model to date – a sparse mixture-of-experts trained with 41B active and 675B total parameters."
The training run
What it physically took to train: which chips, how many, for how long, and what that drew from the wall.
- Training hardware
- NVIDIA H200
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 (restricted use)
- Hugging Face
- mistralai
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Record confidence
- Likely
Sources
Where this record came from and when it was last checked.
- Reference
- Introducing Mistral 3
- Last updated
- 8 April 2026
What the numbers mean
Hardware requirements in practice
At 675B parameters, Mistral 3 Large 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.
Where it came from
Mistral 3 Large was published by Mistral AI, in France, in December 2025. industry is the category the publisher falls under.
It works in Language, and is recorded as doing language modeling/generation.
Published weights mean the model runs on your machine rather than someone else's, which is what makes the hardware question below answerable at all. It is published under the mistralai organisation on Hugging Face.
Step by step
How to choose a GPU for Mistral 3 Large
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 Mistral 3 Large. Capacity is the gate — a card either holds it or it does not.
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02
Set the context length you will work at
The conversation occupies memory too, and grows as it goes. Set the slider to the length you expect: at long context Mistral 3 Large can slip off a card that handles short questions easily.
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03
Set a quality floor
Each card runs the least-compressed copy it can hold. Setting a floor drops the cards that only manage Mistral 3 Large by squeezing it further than you would want.
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04
Rank by throughput rather than spec sheet
Ranking by tokens per second for Mistral 3 Large follows memory bandwidth, not core counts.
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05
Read the fit column last
A tight fit runs Mistral 3 Large but leaves nothing spare for a longer conversation; comfortable has headroom. If you expect to grow the context, buy for comfortable.
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06
Check the card from the other side
Each card page repeats this sweep for every model we hold. It answers what else the hardware is good for, beyond Mistral 3 Large.
Answers
Mistral 3 Large — common questions
Would two GPUs run Mistral 3 Large faster?
A second card roughly doubles the memory available but not the generation rate. With 0 cards already able to run Mistral 3 Large alone, the case for pairing is weak.
Why does the quantisation differ between cards for Mistral 3 Large?
A larger card holds a more accurate copy. Across the cards that run Mistral 3 Large, 1 compression levels are used; the floor control above pins it to one.
How accurate are these Mistral 3 Large speed estimates?
These are estimates with real error bars. The fastest result here, the range beneath each figure, could reasonably land anywhere in its published range depending on which runtime you use.
Is Mistral 3 Large open source?
Its weights are published, so Mistral 3 Large 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 Mistral 3 Large have?
Mistral 3 Large has 675B parameters. "Mistral Large 3 – our most capable model to date – a sparse mixture-of-experts trained with 41B active and 675B total 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 Mistral 3 Large?
Mistral 3 Large was published by Mistral AI, based in France, categorised as industry.
When was Mistral 3 Large released?
Mistral 3 Large was published in December 2025.
What is Mistral 3 Large used for?
Mistral 3 Large 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.
Where can I download Mistral 3 Large?
Its weights are published under the mistralai organisation on Hugging Face. We do not host model files — this site calculates what hardware is needed to run them.
Can I run Mistral 3 Large if it does not fit in my GPU?
Partly. Layers that do not fit sit in system memory and run at a fraction of the speed, so a mostly-offloaded Mistral 3 Large is rarely worth using — the nearest miss we calculate is short by 106.1 GB. Every figure here assumes the whole model is on the card.
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.