◆ THE LAB · Models

Google's Argon beats Opus 5.5 on LiveBench reasoning, not coding

The News

Google released Gemini 4 Argon on October 13, 2026, to paying API customers, enterprises, and Google AI Pro and Ultra subscribers in the Gemini app and AI Mode, after a September 30 rollout to trusted cyber defenders. Through the API it costs $2 per million input tokens and $10 per million output through November 30, then $4 and $20.

Chandni Melwani

Chandni Melwani

Founder & Editor

Oct 18, 2026 · 1 MIN READ

A Google office building with a glass facade and the company's coloured logo, beside a tree Global Photo: Alban / Unsplash

Know More

  • — GPT-6 Astra: $10 in and $50 out per million tokens, more for prompts over 272K input tokens.
  • — Claude Sonnet 5.5: $2 in and $10 out per million tokens, Argon's introductory rates.
  • — Token limits: 1,048,576 input plus output; 65,536 output by default on synchronous calls, 1,048,576 with long decode.
  • — Thinking levels: low, medium and high; Vals and Artificial Analysis both tested high.

Vals.ai ran Argon three times through Terminal-Bench 4.0, 66 long tasks an AI agent works through in a terminal, and it passed 57.58% on average. That ranks it sixth, behind Claude Opus 5.5 at 65.15%, Claude Sonnet 5.5, GPT-6 Astra at 59.60%, Claude Fable 5.1 and Meta’s Muse Wonder Full. Vals ran Opus 5.5 with older Claude models as server-side fallbacks for refusals and lists 22 of its 198 attempts as fallbacks. Vals lists Argon at $4 and $20, its December rates, and its cost at $17.64 a task, more than any of those five.

On LiveBench 2.0, released October 14, Argon scores 95.1 on reasoning, the measure New in AI’s model comparison uses, to Opus 5.5’s 92.2, and 89.7 to 96.3 on coding. Artificial Analysis, as of October 18, shows no output speed and gives Argon an Intelligence Index of 53 at high; Opus 5.5 scores 54 at high and 58 at max, both with fallback.

The Read

From December 1, Argon's input, output and cached-input rates match Opus 5.5's and Meta's Muse Wonder's to the cent. On LiveBench, Argon tops the two short question sets, reasoning and data analysis; Opus 5.5 beats it on four of the five agentic suites, all but browser use. That points to buyers splitting work between them by task.

Room for Disagreement

Vals' results don't split so neatly. Argon ranks first on the Vals Index, 68.90% to Opus 5.5's 66.97%; it measures agentic model performance across finance, coding, legal and tax tasks, weighted by each sector's share of U.S. GDP. By Vals' formula, Finance Agent v2 alone supplies most of that lead.

Related

#Google#Gemini#Models#Pricing#Benchmarks#Anthropic#OpenAI

Frequently Asked Questions

Which Google plans include Gemini 4 Argon?

Google says Google AI Pro and Ultra subscribers get Argon in the Gemini app and AI Mode in Search, that developers build with the Gemini API paid tier, and that Ultra subscribers can also try it in Google Antigravity and AI Studio. On October 15, Google's Antigravity post said Argon was rolling out there for Ultra subscribers; by October 16 it said Pro and Ultra. Google's API pricing page says 'Gemini 4 Argon is not available on the Free tier.'

How does Argon's access for cyber defenders differ?

Google says members of its Fairwind Program, for trusted cyber defenders, get Argon without cyber guardrails on a rolling basis, as do its own internal teams. Argon began rolling out to Fairwind members on September 30, and on October 13 Google began expanding the program to hundreds of additional partners. Google's pricing footnote applies to 'the Argon model intended for public access only.'

What does Google claim for Argon on other benchmarks?

Google says that, relying on pure reasoning, Argon scores 87% on the Embodied Reasoning (ERQA) benchmark, ahead of all other frontier models, and that it leads Gray Swan's Indirect Prompt Injection benchmark, cutting attack success across 15 adaptive attempts to 0.7%. It also says shortcut attempts fell to 2% on coding benchmarks where models have no incentive to hold back, its best performance compared to previous Gemini models.

Sources

Chandni Melwani

Chandni Melwani

Chandni Melwani is the founder and editor of New in AI, covering AI agents, M&A, and enterprise adoption. She holds a Master's in Management of Artificial Intelligence from Queen's University and brings a practitioner's perspective from her work in Data and AI leadership.

Follow ↗

The Lab Briefing

Get the five-beat briefing in your inbox.

The big story, frontier labs, AI at work, e-commerce and the capital crossing borders, each with the part that tells you why it matters, not just that it happened.

Free · No spam · Unsubscribe in one click

More from The Lab

Labs

Anthropic is turning away distillers' paying traffic

Anthropic says early evidence suggests its new defences have cut the data harvested by distillers, who covertly extract Claude's capabilities to replicate them in other models, by around 90 to 99%, and that it has turned away meaningful revenue and trillions of tokens' worth of paying traffic from distillers.

A hand holds a phone showing a folder labelled AI with app icons for ChatGPT, Mistral AI, Claude, Gemini, Copilot and Poe, with a cup of coffee blurred in the background

Chandni Melwani · Global · Oct 21, 2026

Models

Meta releases Muse Spark Open under its own licence

Meta's open-weights Muse Spark Open is free of charge under its Muse Model License, but if a company or any of its affiliates offers AI models to third parties via API or a similar interface, and together they gross over $20m in any consecutive 12 months, the company must notify Meta and sign a separate written agreement before offering the model or a derivative as part of that model-as-a-service business. Meta's own table puts it behind GLM 5.3, Kimi K3 and Qwen3.8-2.4T-A95B on the Artificial Analysis Intelligence Index.

The back panel of an Apple Mac Studio desktop computer on a wooden desk, showing its ports and ventilation grille

Chandni Melwani · Global · Oct 20, 2026