WHAT NEW IN X10.30 FRI

AI collections from X · 22 collections · 60,637 posts

gemini-4IMAGE

Gemini 4 Argon tops APEX-Agents leaderboard

Gemini 4 Argon ranks first on Mercor's APEX-Agents benchmark with 82.2% Pass@1, the first model to pass 80%, and leads in consulting, investment banking and corporate law.

Mercor
@mercorArchived 28 days agoOriginally posted 2026.10.01
Gemini 4 Argon tops APEX-Agents leaderboard
Mercor @mercorOriginally posted 2026.10.01
Open original on X

Gemini 4 Argon is the new #1 on APEX-Agents. 82.2% Pass@1 (#1) 87.9% Mean score (#1) It is the first model to exceed 80% Pass@1. It is +6.7 pts over the prior #1, Sonnet 5.5, and +14.4 pts over the best prior model from DeepMind, Gemini 3.7 Flash (67.8%). #𝟭 𝗶𝗻 𝗮𝗹𝗹 𝗔𝗣𝗘𝗫-𝗔𝗴𝗲𝗻𝘁𝘀 𝗱𝗼𝗺𝗮𝗶𝗻𝘀 Google says Argon delivers frontier performance in "enterprise knowledge work like legal and finance." On APEX-Agents, Gemini 4 Argon ranks first in every professional domain. Management consulting: 90.3% (#1) Investment banking: 80.9% (#1) Corporate law: 75.3% (#1) Consulting appears to be Argon's strongest domain, scoring 10.3 pts ahead of Opus 5.5. It is also the first model to score above 90% on any APEX-Agents leaderboard. 𝗧𝗼𝗸𝗲𝗻 𝘂𝘀𝗮𝗴𝗲 𝗯𝘆 𝗔𝗣𝗘𝗫-𝗔𝗴𝗲𝗻𝘁𝘀 𝗱𝗼𝗺𝗮𝗶𝗻 Argon used 2.6M tokens per attempt on average. The median attempt used 1.75M. Investment banking: 3.5M per attempt Corporate law: 2.7M Management consulting: 1.7M Almost all Gemini 4 Argon’s token usage comes from input. It used 2.61M input tokens per attempt compared with only 28.5K output tokens per attempt. That is about 90 input tokens for every output token. The agent reads a lot of files before composing a short answer. Congrats to @Google and @GoogleDeepMind. See full leaderboard: https://www.mercor.com/apex/apex-agents-leaderboard/

x.com/mercor/status/2105417021248966784Archived 2026.10.01 10:02