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ModelTape / Models / Gemini 4 Argon
Google · API-only (closed weights)

Gemini 4 Argon

Gemini 4 Argon is an API-only (closed weights) language model from Google, released September 30, 2026. The context window is 1M tokens. On the Epoch Capabilities Index it scores 166.5, rank 9 of 256 rated models. API price: $2 input / $10 output per million tokens.

Gemini 4 Argon delivers frontier performance in complex workflows across real-world software engineering, enterprise knowledge work like legal and finance, and cybersecurity defense.

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Lab
Google
Released
September 30, 2026
Weights
API-only (closed weights)
Parameters
–
Context
1M
Price / M tokens
$2 / $10 in / out
Epoch ECI
166.5 #9

Strengths by category

ModelTape's 0–100 fit on Epoch AI benchmark results.

CategoryScoreBased on
Reasoning46.0Chess Puzzles, SimpleBench, Mystery Game Puzzles
Math77.5ProofBench, OTIS Mock AIME 2024-2025, FrontierMath-Tiers-1-3-v2-Private, FrontierMath-Tier-4-v2-Private
Coding71.3MirrorCode, FrontierSWE
Knowledge84.4GPQA diamond, SimpleQA Verified

Benchmark results

Benchmark (Epoch AI)Score
OTIS Mock AIME100.0%
GPQA Diamond99.2%
ProofBench99.0%
FrontierMath (Tiers 1–3)90.5%
SimpleBench90.0%
FrontierMath-Tier-4-v2-Private78.0%
SimpleQA Verified76.0%
EBR-bench64.8%
Furniture Assembly60.7%
Mystery Game Puzzles60.3%
MirrorCode58.9%
Chess Puzzles56.9%
FrontierSWE55.0%
Remote Labor Index17.1%

Links

Announcement · Epoch AI benchmarks

Models with a similar score

Gemini 4 Carbon · GPT-6 Astra · Claude Opus 5.5 · GPT-6.1 Sol · GPT-6.1 Terra · Claude Fable 5.1 · Claude Sonnet 5.5 · Claude Opus 5

More from Google

Gemini 4 Carbon · Gemini 3.8 Flash · Gemini 3.7 Flash · Gemini 3.6 Flash · Gemini 3.5 Flash-Lite · Gemini 3.5 Flash Cyber · Gemma 4 E4B · Gemma 4 E2B

Data updated Thu, 12 Nov 2026 09:42 UTC. Benchmarks, Capabilities Index and model announcements: Epoch AI, “Capabilities & benchmarking” and “Data on AI models” (CC BY 4.0); category scores are ModelTape's own fit on Epoch's results. Releases and prices: models.dev (MIT). Sizes and quantizations: Hugging Face. “Runs on” figures are estimates from model size, quantization and memory bandwidth (±30–50%).
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