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inception/mercury
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Mercury

Mercury is the first diffusion large language model (dLLM). Applying a breakthrough discrete diffusion approach, the model runs 5-10x faster than even speed optimized models like GPT-4.1 Nano and Claude 3.5 Haiku while matching their performance. Mercury's speed enables developers to provide responsive user experiences, including with voice agents, search interfaces, and chatbots. Read more in the [blog post] (https://www.inceptionlabs.ai/blog/introducing-mercury) here.

6/26/2025
128,000 tokens
#254 Text (Coding)

Specifications

Modalities

Input
text
Output
text

Supported Parameters

frequency_penalty
max_tokens
presence_penalty
response_format
stop
structured_outputs
temperature
tool_choice
tools
top_k
top_p

Max Output Tokens

16,384

Data policy

Prompt retention
Unknown — we could not confirm
Training
Unknown — not declared

"Unknown" does not mean "safe". It means we could not confirm it.

Whether a provider trains on prompts is a declared value from our terms with them. Retention is determined from the upstream listing for every host this model can reach. Neither is guessed.

Frequently asked questions

Is Mercury available on FastMetal?
Not at the moment. Mercury 2.5, from the same lab, is available on the FastMetal API today.
What is the context window of Mercury?
128,000 tokens, shared between the prompt and the response.
How does Mercury rank?
#282 on the public arena's Overall board (ELO 1,306). Ranks move as the leaderboard is updated.

Leaderboard

Text
CodingELO: 1,365
#254
Creative WritingELO: 1,220
#317
Instruction FollowingELO: 1,271
#298
Hard PromptsELO: 1,319
#275
Multi-TurnELO: 1,299
#272
OverallELO: 1,306
#282
EnglishELO: 1,322
#283

Rankings: LMArena leaderboard dataset (lmarena-ai/leaderboard-dataset), CC BY 4.0, snapshot 2026-10-22; category names mapped and ratings rounded by FastMetal.