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Gemini 4 Argon

Multimodal
Google

Gemini 4 Argon is Google DeepMind's frontier Gemini 4 model for long-horizon software engineering, enterprise knowledge work in legal and finance, cybersecurity defense, and multimodal understanding of charts and video. It raises the output token limit to 1M, up from 64K. As of early October 2026 it is rolling out only to trusted cyber defenders through Google's Fairwind Program, with paid API customers and Google AI Ultra subscribers planned next and no public Gemini API or Vertex model id yet. Google's launch blog announces introductory pricing of $2 per million input and $10 per million output tokens with cached input 95% off, rising to $4/$20 after an introductory period. No first-party provider price row is stored yet, so it cannot enter ZeroEval. Catalog scores are self-reported from Google's launch blog and the DeepMind evals methodology page.

Key Specifications

Parameters
-
Context
-
Release Date
September 30, 2026
Average Score
67.3%

Timeline

Key dates in the model's history
Announcement
September 30, 2026
Last Update
October 8, 2026
Today
October 11, 2026

Technical Specifications

Parameters
-
Training Tokens
-
Knowledge Cutoff
-
Family
-
Capabilities
MultimodalZeroEval

Benchmark Results

Model performance metrics across various tests and benchmarks

Other Tests

Specialized benchmarks
Agents' Last Exam
Binary pass rate; default ALE-Claw harness; 5-hour window; safety filters enabled; self-computed. • Self-reported
39.5%
AutomationBench
Private set; sourced from the official Zapier public leaderboard. • Self-reported
51.3%
Chartography (no tools)
Without tools; sourced from the official Surge public leaderboard. • Self-reported
71.6%
CWE-Bench
CWE-bench v1 (not v0); pass@1 from the official public leaderboard (ties broken by pass@4). Stored on unversioned catalog id cwe-bench alongside older v0 rows. • Self-reported
68.0%
DeepSWE 1.1
DeepSWE v1.1; mini-swe agent harness; self-computed by Google at highest thinking settings. • Self-reported
77.9%
FrontierSWE V2
Sourced from Proximal's official FrontierSWE public leaderboard. • Self-reported
55.0%
Graphwalks BFS <128k
Up to 128k subset (650 items); BFS (F1); self-computed. • Self-reported
99.7%
Graphwalks BFS >128k
256k to 1M subset (200 items); BFS (F1); self-computed. • Self-reported
84.2%
Harvey's Legal Agent Benchmark
Legal research and drafting; sourced from Vals AI. • Self-reported
19.6%
LABBench2
Biology real-world research tasks with Linux terminal, bioinformatics tools, Python, R, and internet access; self-computed. • Self-reported
88.8%
LVBench
Long video understanding; self-computed without tools; 1 FPS for Gemini. • Self-reported
91.7%
OSWorld 2.0
Offline subset partial score; maxed over 3 runs; single attempt per run; Gemini CUA harness with parallel batch tool calling; self-computed. • Self-reported
69.2%
PostTrainBench
PostTrainBench v1.1 with OpenCode harness; 10-hour budget on a single NVIDIA H100; weighted aggregate across four base models and seven benchmarks; self-computed. • Self-reported
45.3%
RiemannBench
Sourced from the official Surge public leaderboard. • Self-reported
76.0%
Terminal-Bench 4.0
Self-computed by Google at highest thinking settings; peer scores from the official public leaderboard. • Self-reported
57.4%
Terminal-Bench-Science 0.1
Self-computed by Google with 6x verifier timeout to address verification timeouts. • Self-reported
57.6%
Vals Finance Agent v2
Financial analyst tasks; sourced from Vals AI. • Self-reported
65.4%
Vals Index
Knowledge work; sourced from Vals AI public results. • Self-reported
68.9%
Vibe Code Bench
Sourced from the official Vals AI public leaderboard. • Self-reported
91.9%

License & Metadata

License
proprietary
Announcement Date
September 30, 2026
Last Updated
October 8, 2026

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