whatmodel.sh / Mercury

Mercury

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Mercury is a closed-weights language model from Inception. Licence: proprietary.

Catalogue identity notes

Exact Arena entry 'mercury' in the October 2026 pinned dataset. Comparison identity; no public run route inferred from leaderboard inclusion.

54.2±3.3comparison only: no current run option verifiedfrom 1 benchmark result across 1 source* thinly tested, treat the rank as provisional

$ how it compares

The LLMs ranked either side of Mercury, out of 1132 with a score, then more from Inception.

#modelscorewhereRAMreleased
447Nova Premier Amazon54±2api $5.00/M2025-04
448Devstral Medium 1.0 (2507) Mistral54±3comparison only2025-07
449Mercury Inception54±3comparison only
450Nanbeige4-3B-Thinking-2511 Nanbeige54±3local~3.7GB2025-11
451Mellum2 12B-A2.5B Thinking JetBrains54±1local~8.6GB2026-05
more from Inception
321Mercury 2 Inception59±2comparison only

see all LLMs · find the ones that fit your machine

$ what it's good at

chat & writing▁▁▁▃▅▅▆█▆▆▆▂ #306 of 579 * · 95% of its score · 1 test

Beats Granite 4.2 8B, Mistral Small 4 (119B-A6.5B), Olmo 3.1 32B Think here, though they rank higher overall. Trails LFM2.5 1.2B Instruct, Granite 4.0 H Micro 3B, Gemma 3n E4B here, though they rank lower overall.

testresultvs the others in its rundifficultycountswhy
LMArena (text)1305.2 ✎▁▁▁▂▃▃▃▆▆▇█▃ beats 133/379avg 1268▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 95%blunt

$ where to run it

No verified API or download recorded yet · add one

$ how the score was worked out · LMArena leaderboard dataset 95%

Each result implies a score on its own, after adjusting for how hard its test is and who ran it. The score is their weighted average, with a small pull toward the middle for thinly tested models. Each test's weight is its counts column above; here it's added up by who ran the tests. How it works

sourceresultsshare of the scorelicence
LMArena leaderboard dataset1▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 95%CC BY 4.0
prior · pull toward the middle▇ 5%
weighted average= 54.2

$ improve this page

Update model informationAdd a place to run itAdd a test resultPropose a benchmarkCorrect a benchmark scoreEdit data on GitHub

Use a short GitHub form or edit the data through a pull request. Every number needs a source; here's which ones we can use.

data updated · sources and licences · json