Google•Rank #8NEW

Gemini 4 Argon

Proprietarygeneralreasoningcodingagent

Leaderboard Score

61.4

Scale: 0 - 100

Throughput Speed

82 tps

Context Window

API Pricing / 1M

$4.00

Parameter Scale

Proprietary

Monthly API Cost Calculator

Gemini 4 Argon rates: $4/1M input • $20/1M output. Pick a workload preset or enter your own token volumes.

Monthly input (M tokens)Monthly output (M tokens)

Same workload on published-rate alternatives

Gemini 4 Carbon (Google)

Claude Opus 5.5 (Anthropic)

Open the comparison engine →

Estimates use listed API rates at time of writing; providers may differ in caching discounts, rate limits, and batching pricing.

Sourced AI Radar & Benchmarks•8 Evaluated Metrics

Capability Radar & Benchmark Scores

Multi-Axis Capability Radar

Comparing Gemini 4 Argon against Frontier Top 10 & Open-Source average

0 - 100 Scale

Gemini 4 Argon

Frontier Top 10 Avg

Open-Source Avg

Performance Vectors

Where Gemini 4 Argon Leads

Coding & SWETop 10: 80% • OS: 51.1%

78.4%-1.6% vs Top 10

Reasoning & MathTop 10: 89.2% • OS: 52.7%

89.2%+0.0% vs Top 10

Agent & Tool AutomationTop 10: 78.3% • OS: 36.4%

74.7%-3.6% vs Top 10

Terminal & CLI ExecutionTop 10: 66.8% • OS: 46.2%

57.1%-9.7% vs Top 10

MMLU & Knowledge QATop 10: 50% • OS: 86.7%

76.8%+26.8% vs Top 10

Cyber & Security ExploitsTop 10: 86.2% • OS: 81.2%

58.3%-27.9% vs Top 10

All Verified Benchmark Evaluations

Direct Pass@1 and resolution rates across standardized evaluations.

OverallCodingReasoningAgenticTerminal

Featured Compute Platform

Run Benchmarks on Dedicated AI Clusters

Zero-cold-start inference endpoints with dedicated GPU instances.

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Executive Analysis & Verdict

Gemini 4 Argon by Google is a high-efficiency frontier reasoning model scoring 61.4 overall and 50 on the Artificial Analysis Intelligence Index v5.0, demonstrating high-precision tool chaining on AutomationBench (51.3%), Chartography (71.6%), and SEC-bench Pro (83.4%).

Key Strengths & Highlights

•High-fidelity enterprise agent performance with 69.2% on Vals Index v2.2 and 51.3% on AutomationBench Zapier
•Balanced multi-modal diagram and technical schematic comprehension with 71.6% on Chartography and 54.4% on Blueprint-Bench 2
•Strong long-horizon retrieval with 84.2% on GraphWalks 1M BFS across a 1,048,576 token native context window
•Calibrated cybersecurity analysis scoring 83.4% on SEC-bench Pro and 68.0% on CWE-bench

Limitations & Considerations

•Throughput of 82.4 tps sits slightly below specialized low-latency flash tiers

Recommended Workflows

Enterprise workflow orchestration, technical document analysis, automated scripting, cybersecurity audits, and full-context repository navigation

Architectural Overview & Capability Profile

Gemini 4 Argon is developed by Google DeepMind as a focused reasoning workhorse in the Gemini 4 lineup. Engineered to deliver high reliability on multi-step API automation, document comprehension, and long-context reasoning, Gemini 4 Argon balances deep analytical reasoning with accessible production pricing. On the comprehensive RankLLMs composite evaluation index, Gemini 4 Argon scores an overall rating of 61.4 / 100 (Rank #6).

Operating under a Proprietary license structure, Gemini 4 Argon is served via Google Cloud Vertex AI and Google AI Studio endpoints with a full 1-million-token context window and prompt caching discounts.

Benchmark Performance & Real-World Utility

In standardized evaluations verified by Google DeepMind and independent tracking by Artificial Analysis, Gemini 4 Argon demonstrates robust proficiency across multiple real-world evaluation matrices:

Artificial Analysis Intelligence Index v5.0 (50): Ranks comfortably in the frontier tier, scoring above the class median across knowledge work, coding, and science.
Vals Index v2.2 (69.2%): Validates high execution consistency across complex professional enterprise tasks.
Agentic Coding & Terminal Automation:
- FrontierSWE 2 (55.0%): Solid performance in resolving complex multi-file engineering problems.
- Terminal-Bench 4.0 (57.1%): Dependable execution in shell scripting, CLI tools, and automated DevOps environments.
Computer Use & Autonomous Tooling:
- Agents’ Last Exam v1.1 (69.0%): Strong multi-tool chaining and web-agent reasoning.
- OSWorld-2.1 Offline Subset (74.7%): Accurate desktop GUI navigation and multi-application coordination.
- AutomationBench Zapier (51.3%): Exceptional enterprise API integration, trailing only Gemini 4 Carbon.
- Vending-Bench 2 ($13,718): Sound long-horizon resource allocation.
Long Context & Multimodal Synthesis:
- GraphWalks BFS 256K-1M (84.2%): High-accuracy needle retrieval and multi-hop reasoning over 1 million continuous tokens.
- Chartography (71.6%): High visual fidelity in interpreting charts, graphs, and UI layouts.
Science & Cybersecurity:
- RiemannBench (76.0%): Advanced formal logic and scientific derivation.
- SEC-bench Pro (83.4%) & CWE-bench (68.0%): High-reliability software vulnerability detection.

Official evaluation methodology: deepmind.google/models/evals-methodology/gemini-4-carbon.

Inference Latency & Cost Architecture

Token Context Window: 1,048,576 tokens native context window.
Inference Speed: Average throughput measures 82.4 tokens/second.
Commercial Pricing: API consumption is priced at $4.00 per 1M input tokens and $20.00 per 1M output tokens, with cache-hit reads reduced to $0.20 per 1M tokens.

Strengths, Limitations & Ideal Workflows

Primary Strengths

High-fidelity enterprise agent performance with 69.2% on Vals Index v2.2 and 51.3% on AutomationBench Zapier
Balanced multi-modal diagram and technical schematic comprehension with 71.6% on Chartography and 54.4% on Blueprint-Bench 2
Strong long-horizon retrieval with 84.2% on GraphWalks 1M BFS across a 1M native context window
Calibrated cybersecurity analysis scoring 83.4% on SEC-bench Pro and 68.0% on CWE-bench

Known Considerations

Throughput of 82.4 tps sits slightly below specialized low-latency flash tiers.

Recommended Use Cases

Enterprise workflow orchestration, technical document analysis, automated scripting, cybersecurity audits, and full-context repository navigation.

Compare with alternatives in the Model Comparison Engine
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Explore top coding models in our Best LLM for Coding Guide

Frequently Asked Questions About Gemini 4 Argon

What is Gemini 4 Argon and who developed it?↓

Gemini 4 Argon is a proprietary large language model developed by Google. It ranks #8 on the RankLLMs composite leaderboard, ahead of 93% of the 95 models we track, with an overall score of 61.4 / 100.

Can Gemini 4 Argon handle very long documents and codebases?↓

Gemini 4 Argon supports a 1.0M-token input context window and generates about 82 tps tokens per second in our reference measurements and which is enough to hold entire repositories, long transcripts, or multi-document research sets in a single session..

Why does Gemini 4 Argon cost more than most alternatives?↓

Gemini 4 Argon sits in the premium tier at $4.00 per 1M tokens - cheaper than only 88% of priced models we track. That pricing buys frontier-tier benchmark results; the cost-per-solved-task math in our best-coding-LLM guide shows when it pays off.

What is Gemini 4 Argon best at?↓

Gemini 4 Argon is strongest in High-fidelity enterprise agent performance with 69.2% on Vals Index v2.2 and 51.3% on AutomationBench Zapier; Balanced multi-modal diagram and technical schematic comprehension with 71.6% on Chartography and 54.4% on Blueprint-Bench 2; Strong long-horizon retrieval with 84.2% on GraphWalks 1M BFS across a 1,048,576 token native context window. Full pillar-by-pillar numbers are in the benchmark tables above.

What should you watch out for with Gemini 4 Argon?↓

Known trade-offs include: Throughput of 82.4 tps sits slightly below specialized low-latency flash tiers. Weigh these against the strengths above for your specific workload.