Google's Gemini 4 Argon wins 13 of 19 benchmarks against GPT-6 Astra and Claude Opus 5.5 — but not all of them. Here is a simple breakdown of where it leads, where it loses, what it costs, and which AI model fits your business.
Google DeepMind has launched Gemini 4 Argon, and its benchmark table has the whole AI world talking. Google says Argon beats GPT-6 Astra, Claude Opus 5.5 and Claude Fable 5.1 on most tests. But "most" is not "all". In this guide, we explain the Gemini 4 Argon benchmarks in simple words — what each test means, where Argon wins, where it loses, and what it means for your business.
Quick answer: In Google's own table, Gemini 4 Argon wins 13 of 19 benchmark rows, ties 1, and loses 5. It is strongest at business tasks (finance, legal, automation), very long documents, and video understanding. It is weaker at hard terminal-based coding, where Claude Opus 5.5 leads, and at frontier coding, science terminal work and computer use, where GPT-6 Astra leads.
What Is Gemini 4 Argon?
Gemini 4 Argon is Google's newest top-level AI model. Google announced it on September 30, 2026, and it became generally available in the Gemini API on October 13, 2026 (model ID: gemini-4-argon). It is built for long, multi-step "deep work" — like software engineering, enterprise research, finance, legal and cybersecurity tasks.
- Context window: about 1 million tokens (shared across input, thinking and output)
- Input types: text, images, video, audio and PDF
- Thinking levels: low, medium and high
- Launch price: $2 per million input tokens and $10 per million output tokens (introductory)
Gemini 4 Argon Benchmarks: Full Comparison Table
Below are the scores Google published. Higher is better. The winner in each row is in bold.
| Area | Benchmark | Gemini 4 Argon | GPT-6 Astra | Claude Fable 5.1 | Claude Opus 5.5 |
|---|---|---|---|---|---|
| Knowledge work | Vals Index | 68.9% | 63.1% | 65.8% | 67.0% |
| Knowledge work | AutomationBench | 51.3% | 41.4% | 31.4% | 42.5% |
| Knowledge work | Vals Finance Agent v2 | 65.4% | 53.5% | 58.9% | 58.6% |
| Knowledge work | Harvey's Legal Agent Benchmark | 19.6% | 5.4% | 6.7% | 3.8% |
| Agentic coding | DeepSWE v1.1 | 77.9% | 74.1% | 67.4% | 74.2% |
| Agentic coding | FrontierSWE v2 | 55.0% | 65.5% | 56.3% | 62.3% |
| Agentic coding | Vibe Code Bench | 91.9% | 89.6% | 90.3% | 90.3% |
| Agentic coding | Terminal-bench 4.0 | 57.4% | 58.2% | 57.9% | 66.4% |
| ML engineering | PostTrainBench | 45.3% | 44.3% | 40.2% | 49.3% |
| Science & math | Terminal-Bench Science 0.1 | 57.6% | 68.1% | 52.6% | 63.3% |
| Science & math | LABBench 2 | 88.8% | 85.4% | 68.6% | 73.1% |
| Science & math | RiemannBench | 76.0% | 72.0% | 65.6% | 69.6% |
| Long context | GraphWalks (up to 128K) | 99.7% | 98.7% | 91.4% | 90.6% |
| Long context | GraphWalks (256K–1M) | 84.2% | 71.8% | 65.0% | 66.8% |
| Computer use | Agent's Last Exam | 39.5% | 34.2% | — | 38.2% |
| Computer use | OSWorld-2.0 (offline subset) | 69.2% | 72.6% | — | — |
| Multimodal | Chartography | 71.6% | 71.0% | 46.2% | 66.3% |
| Multimodal | LVBench (video) | 91.7% | 87.5% | 79.7% | 83.7% |
| Cybersecurity | CWE-bench v1 | 68.0% (tie) | 68.0% (tie) | 58.0% | 67.0% |
Source: Google DeepMind's Gemini 4 Argon launch table. "—" means no score was reported.
Where Gemini 4 Argon Wins
1. Real business tasks (finance, legal, automation)
This is Argon's strongest area. It tops the Vals Index, which scores AI on real work in finance, coding, legal and tax. It also leads Vals Finance Agent v2 by about 6.5 points and AutomationBench by about 9 points. The biggest gap is in legal work: on Harvey's Legal Agent Benchmark, Argon scores 19.6% while the others stay below 7%.
What it means: If your business wants AI agents that handle multi-step office work — reports, research, document checks — Argon is a strong option to test.
2. Very long documents
On GraphWalks between 256K and 1M tokens, Argon scores 84.2% — more than 12 points ahead of GPT-6 Astra and about 17 points ahead of Claude Opus 5.5. In simple words, it keeps track of details much better when you give it a huge amount of text at once.
What it means: Good for contracts, audit files, policy manuals and large knowledge bases used in RAG and generative AI systems.
3. Video and chart understanding
Argon leads on LVBench (long video) with 91.7% and on Chartography (reading charts). This helps with CCTV review, training videos, inspection footage and dashboard reading.
4. Science and math
Argon scores 88.8% on LABBench 2 (lab reasoning) and 76.0% on RiemannBench (hard math), ahead of all three rivals.
5. Safety against prompt injection
Google reports that Argon had the lowest attack success rate (0.7%) on Gray Swan's indirect prompt-injection test. Independent write-ups put Claude Opus 5.5 at 1.0% and GPT-6 Astra at 8.5%. This matters when AI agents read emails, web pages or files that may contain hidden instructions.
Where Gemini 4 Argon Loses
Argon is not the best at everything. Here are the 5 rows where a rival wins:
- Terminal-bench 4.0: Claude Opus 5.5 leads with 66.4% vs Argon's 57.4% (9-point gap). Opus is stronger at hard coding work inside a terminal.
- FrontierSWE v2: GPT-6 Astra leads with 65.5% vs 55.0% (10.5-point gap) on the hardest software engineering tasks.
- Terminal-Bench Science 0.1: GPT-6 Astra leads with 68.1% vs 57.6%.
- PostTrainBench (ML engineering): Claude Opus 5.5 leads with 49.3% vs 45.3%.
- OSWorld-2.0 (computer use): GPT-6 Astra leads with 72.6% vs 69.2%.
So the coding story is mixed. Argon wins DeepSWE v1.1 (77.9%) and Vibe Code Bench (91.9%), but loses the tougher terminal and frontier coding tests.
What Independent Tests Say
Company benchmark tables are useful, but they are chosen by the company. Independent tests give a more balanced picture:
- Artificial Analysis Intelligence Index: Claude Opus 5.5 (max) scores about 57.6, while Gemini 4 Argon (high) scores 52.6 and GPT-6 Astra (max) 52.7. So on general reasoning, Argon is roughly tied with Astra and behind Opus.
- Vals Index (independent): Argon is #1 at 68.9%, ahead of Opus 5.5 (66.97%) and Astra (63.13%) — the first Gemini model to top this index.
- Real-world tests by developers: early users report Argon gives the best results for visual and 3D work and is fast, while GPT-6 Astra was more reliable for complete, polished apps in one go.
Our take: No single AI model wins everything in 2026. The right model depends on the task.
Gemini 4 Argon Pricing vs Competition
| Model | Input (per 1M tokens) | Output (per 1M tokens) |
|---|---|---|
| Gemini 4 Argon (intro, till Nov 30, 2026) | $2 | $10 |
| Gemini 4 Argon (from Dec 1, 2026) | $4 | $20 |
| Claude Opus 5.5 | $4 | $20 |
| GPT-6 Astra | $10 | $50 |
For now, Argon is the cheapest of the three flagship models. After the introductory period, it will cost the same as Claude Opus 5.5. If you are building a budget, plan with the later price, not the launch offer.
Which AI Model Should Your Business Choose?
- Choose Gemini 4 Argon for: finance and legal workflows, long documents, video/CCTV analysis, chart reading, and business automation.
- Choose Claude Opus 5.5 for: hard coding and debugging in a terminal, ML engineering, and highest overall reasoning score.
- Choose GPT-6 Astra for: the hardest frontier coding tasks, science terminal work, and computer-use agents that click through software.
Many smart businesses now use a multi-model setup: a router sends each task to the model that does it best and costs least. This avoids vendor lock-in and keeps bills under control.
What This Means for Indian Businesses and MSMEs
For MSMEs and manufacturers in India, the big takeaway is simple: AI agents are now good enough to handle real office and shop-floor tasks — invoice checks, compliance documents, report writing, quality inspection from video, and customer replies. But picking the wrong model can waste money.
At Prism Infoways, we help businesses test models side by side on their own data before they commit. We build AI-powered automation, AI chatbots and multi-agent systems that can switch between Gemini, GPT and Claude as needed. You can also read our guide on AI chatbot development cost in India, or see how AI tools like Claude can work inside your admin panel with our Tungsten MCP plugin.
Since AI models now answer many search questions directly, it also helps to make your website easy for them to cite. Our Answer Engine Optimization (AEO) guide explains how.
Frequently Asked Questions
1. Is Gemini 4 Argon better than GPT-6 Astra?
On Google's table, Argon beats GPT-6 Astra on most rows, including Vals Index, DeepSWE v1.1, finance, legal, long context and video. But Astra wins on FrontierSWE v2, Terminal-Bench Science and OSWorld-2.0, and the two tie on CWE-bench.
2. Is Gemini 4 Argon better than Claude Opus 5.5?
Argon leads Opus 5.5 on business tasks, long context and multimodal tests. Opus 5.5 leads on Terminal-bench 4.0 and PostTrainBench, and scores higher on the independent Artificial Analysis Intelligence Index.
3. How much does Gemini 4 Argon cost?
The introductory API price is $2 per million input tokens and $10 per million output tokens until November 30, 2026. From December 1, 2026, it rises to $4 input and $20 output.
4. How many benchmarks does Gemini 4 Argon win?
In Google's launch table, Argon wins 13 of 19 rows, ties 1 (CWE-bench v1) and loses 5.
5. Which AI model is best for coding in 2026?
It depends on the task. Argon leads DeepSWE v1.1 and Vibe Code Bench, Claude Opus 5.5 leads Terminal-bench 4.0, and GPT-6 Astra leads FrontierSWE v2. For serious coding work, test two models on your own codebase.
6. Can Prism Infoways help us choose and use the right AI model?
Yes. Prism Infoways, based in Gurugram, Haryana, builds AI agents, chatbots and automation for businesses and can set up multi-model systems that use the best model for each task. Contact us for a free consultation.
Conclusion
Gemini 4 Argon is a big step for Google. It leads on real business work, very long documents and video, and it launches at a lower price than its rivals. But it is not the best at every task — Claude Opus 5.5 and GPT-6 Astra still win key coding and computer-use tests. The smartest move is to match the model to the job.
Want to build AI that actually saves time and money? Explore Prism Infoways' AI Solutions and talk to our team today.
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