Mercury
No estimate
No hardware requirements for this model
The weights for this model have not been published, so it cannot be downloaded or run on your own hardware at any size. It is reachable only through its provider, and no graphics card changes that.
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
- Inception Labs
- Organisation type
- Industry
- Country
- United States of America
- Published
- 27 February 2025
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Language
- Task
- Code 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.
- 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
- Closed — provider access only
- Model access
- API access
- Training code
- Unreleased
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
- SOTA improvement
- Record confidence
- Unknown
“When evaluated on standard coding benchmarks, Mercury Coder achieves excellent quality across numerous benchmarks, often surpassing the performance of speed-optimized autoregressive models like GPT-4o Mini and Claude 3.5 Haiku while being up to 10x faster.” "When benchmarked on Copilot Arena, Mercury Coder Mini is tied for second place, surpassing the performance of speed-optimized models like GPT-4o Mini and Gemini-1.5-Flash and even of larger models like GPT-4o. At the same time, it is the f…
Sources
Where this record came from and when it was last checked.
- Reference
- Is the Mercury LLM the first of a new Generation of LLMs?
- Last updated
- 28 November 2025
What the numbers mean
Where it came from
Mercury was published by Inception Labs, in United States of America, in February 2025. It comes out of industry.
It works in Language, and is recorded as doing code generation.
Because the weights are not available, none of the hardware figures elsewhere on this site apply to it.
What went into building it
It is tracked in the underlying dataset for one reason in particular: sOTA improvement.
Answers
Mercury — common questions
Is Mercury open source?
No. Mercury has not had its weights published, so it exists only as a service controlled by its owner.
How many parameters does Mercury have?
No parameter count has been published for Mercury, which is why no memory or speed figure appears on this page.
Who created Mercury?
Mercury was published by Inception Labs, based in United States of America, categorised as industry.
When was Mercury released?
Mercury was published in February 2025.
What is Mercury used for?
Mercury works in Language, and is recorded as handling code generation. A model can carry several of each, so these are the areas it was built for rather than a limit on what it will attempt.
What GPU do I need to run Mercury?
None. Mercury is a closed model — its weights were never published, so it cannot be downloaded or run on your own hardware at any price. It is reachable only through its provider.
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.