This comparison lines up Claude Opus 5.5 vs GPT-6.1 Sol vs Gemini 4 Argon on the numbers that actually change a procurement decision: per-token pricing, context and output limits, coding benchmarks, cybersecurity capability and plan-level availability. The standout figure is Gemini 4 Argon’s output ceiling, which Google lifted from 64,000 tokens to 1 million tokens, more than a 15-fold jump that lets a single response cover an entire codebase review or a lengthy legal document without chunking. But raw capacity is only one part of the picture, and the other two models win on different fronts.
None of these three models is interchangeable with the default chat experience most people already use. GPT-6.1 Sol is not the model answering everyday ChatGPT prompts; that’s GPT-5.6, which already handles everyday ChatGPT prompts. GPT-6.1 Sol is a specialised, more expensive-to-build-but-cheaper-to-run upgrade that currently lives in ChatGPT Work and Codex, not ordinary Chat. Claude Opus 5.5 is Anthropic’s flagship, sitting above Sonnet 5.5 and Haiku 5.5 in the current Claude 5.5 family. Gemini 4 Argon is Google’s new top-tier model, replacing the narrower-output Gemini 3.8 generation at the frontier end. Keeping those distinctions straight matters, because comparing the wrong tier against the wrong tier is the single most common mistake in AI procurement right now.
Don’t miss new tech stories on Google
Add Tech Insider once in the Google app and our stories appear in your news suggestions.
Add Now
Release Timeline: What Changed and When
Understanding this comparison starts with the calendar. All three vendors moved within the same five-week window, and the sequence explains a lot of the current confusion about which model is “newest.” Here is the confirmed timeline, pulled from each company’s own release pages and safety documentation.
- September 22, 2026, Anthropic releases Claude Opus 5.5, the first model in the Claude 5.5 family. September 29, 2026, OpenAI announces GPT-6.1 Sol as an upgrade to GPT-6 Sol.
- September 28, 2026, Anthropic releases Claude Sonnet 5.5, pitched as more than 30% faster and up to 30% cheaper than Sonnet 5 for most work.
- September 29, 2026, OpenAI publishes a safety addendum to the GPT-6 Astra system card specifically covering GPT-6.1 Sol, and expands its rollout.
- September 30, 2026, Google announces Gemini 4 Argon and opens a limited early-access phase for trusted cyber defenders through its Fairwind Program.
- October 6, 2026, Anthropic expands its Cyber Verification Program, adding three access tiers for qualifying security professionals working with Opus 5.5, Sonnet 5.5 and the restricted Claude Mythos 5.1.
- October 7, 2026, Anthropic releases Claude Haiku 5.5, its fastest small model; OpenAI begins a global rollout of GPT-6 with a new “Intelligent UI” to Plus, Pro, Business and Enterprise ChatGPT users.
- Anthropic reportedly commits US$150 million over three years to the Genesis Mission, a federal initiative intended to accelerate scientific and technological discovery with AI.
- Anthropic adds “preserved thinking,” an anti-distillation safeguard for Opus 5.5 and Claude Fable 5.1, as Anthropic detailed in its distillation-defenses research note.
- October 13, 2026, Gemini 4 Argon reaches general availability through the Gemini API, AI Studio and the Gemini app for Google AI Pro and Ultra subscribers.
- October 14–17, 2026, Anthropic reports that Opus 5.5, Sonnet 5.5 and Haiku 5.5 each scored 99% on its internal political-evenhandedness evaluation.
- October 20, 2026, Google updates the Gemini app with Argon-powered coding workflows through its Antigravity interface for Google AI Ultra subscribers.
The pattern is clear: every major lab treated late September and October 2026 as a launch window, and the three models under discussion here are each vendor’s current best answer to “what do we ship next.” That makes this a genuinely fresh comparison rather than a rehash of mid-2026 pricing, when Claude Opus 5, GPT-6 Sol and Gemini 3.8 Flash were the relevant names.
Full Specs Table: Claude Opus 5.5 vs GPT-6.1 Sol vs Gemini 4 Argon
The table below puts the three models side by side on the specifications that matter most for a buying decision. Prices are official, standard API rates in US dollars, as published on each company’s own pricing page; this is how developer and enterprise billing is denominated across all three vendors, regardless of the customer’s home currency.
| Spec | Claude Opus 5.5 | GPT-6.1 Sol | Gemini 4 Argon |
|---|---|---|---|
| Maker | Anthropic | OpenAI | |
| Release date | September 22, 2026 | Announced September 22, 2026 | Announced Sept 30, GA October 13, 2026 |
| Model identifier | claude-opus-5-5 |
gpt-6.1-sol |
gemini-4-argon (per third-party reporting) |
| Positioning | Flagship for agentic coding and knowledge work | Near GPT-6 Astra intelligence for coding, computer use and professional work, at a fraction of the cost | Frontier model for long-horizon software engineering, legal/financial work, cybersecurity and science |
| Standard input price | US$4 per million tokens | US$2 per million tokens | US$2 per million tokens (introductory, to Nov 30, 2026) |
| Standard output price | US$20 per million tokens | US$10 per million tokens | US$10 per million tokens (introductory) |
| Cached input price | US$0.20 per million tokens | US$0.10 per million tokens | 95% discount off input-token rate |
| Fast/turbo mode | US$8 input / US$40 output per million tokens, up to 2.5x speed, in Claude Code and the Claude Platform | Not separately listed | Not separately listed |
| Output limit | Not specified as a standalone figure | Not specified as a standalone figure | 1,000,000 tokens, up from 64,000 tokens in the prior generation |
| Headline coding benchmark | 54.6% on FrontierCode at default effort, Anthropic’s top score | Up to 86.6% on a COBOL legacy-migration test, per LetsDataScience, up from 5.4% | Ties for first on CWE-bench v1 vulnerability remediation at 68% |
| Cybersecurity program | Cyber Verification Program, three access tiers (expanded Oct 6) | Addendum to GPT-6 Astra system card (Sept 29) | Fairwind Program for trusted cyber defenders (early access) |
| Consumer app access | Claude app for Pro, Max, Team and Enterprise subscribers, per Anthropic’s release notes | Not yet in ordinary ChatGPT Chat as of October 21, 2026 | Gemini app and Search AI Mode for Google AI Pro and Ultra subscribers |
| Cloud/API availability | Claude Platform, AWS, Google Cloud, Microsoft Azure | OpenAI API, ChatGPT Work, Codex | Gemini API, Google AI Studio, Google Antigravity (Ultra only) |
| Data retention | Zero data retention available, as with prior Opus models | Not specified in this comparison | Not specified in this comparison |
Two things jump out immediately. First, GPT-6.1 Sol and Gemini 4 Argon’s introductory rate both undercut Claude Opus 5.5 on raw per-token price, by exactly half on both input and output. Second, Gemini 4 Argon’s 1-million-token output ceiling is in a different league to anything the other two vendors have published for this trio, though it comes with an introductory price that Google has already confirmed will roughly double on December 1, 2026.
Pricing Compared: Input, Output and Cache Tokens
Pricing is where this three-way comparison gets genuinely interesting, because two of the three vendors are using introductory or positioning-driven numbers rather than settled long-term rates. Claude Opus 5.5 is priced at US$4 per million input tokens and US$20 per million output tokens, which Anthropic says represents a 40% drop in typical running cost compared with Opus 5, even though the headline per-token rate is the highest of the three. Anthropic’s own explanation is that Opus 5.5 needs fewer tokens to finish the same task, so the effective cost per completed job falls even as the sticker price looks steep next to its two rivals.
GPT-6.1 Sol is the cheapest of the three on paper: US$2 per million input tokens, US$0.10 per million cached-input tokens, and US$10 per million output tokens. OpenAI has described this as roughly one-fifth of what it charges for GPT-6 Astra, its top-of-range model, while claiming performance that approaches Astra on several evaluations. That positioning, cheap but nearly as capable as the flagship, is the core of OpenAI’s pitch for GPT-6.1 Sol in coding and computer-use workloads.
Gemini 4 Argon matches GPT-6.1 Sol’s US$2/US$10 rate for now, with cached input tokens discounted 95% off the standard input rate. The catch is the word “introductory.” Google has stated plainly on its own release pages that once this period expires on November 30, 2026, the price jumps to US$4 per million input tokens and US$20 per million output tokens, landing Argon at exactly the same rate as Claude Opus 5.5. Any Australian team budgeting for Gemini 4 Argon usage into the new year needs to model that doubling now, not discover it on the first December invoice.
| Price component | Claude Opus 5.5 | GPT-6.1 Sol | Gemini 4 Argon (to Nov 30) | Gemini 4 Argon (from Dec 1) |
|---|---|---|---|---|
| Input tokens | US$4 / million | US$2 / million | US$2 / million | US$4 / million |
| Cached input tokens | US$0.20 / million | US$0.10 / million | 95% off input rate | 95% off input rate |
| Output tokens | US$20 / million | US$10 / million | US$10 / million | US$20 / million |
| Fast/turbo mode input | US$8 / million | Not offered | Not offered | Not offered |
| Fast/turbo mode output | US$40 / million | Not offered | Not offered | Not offered |
What this table shows is that the “cheapest” model depends entirely on when you ask the question. Today, GPT-6.1 Sol and Gemini 4 Argon are tied at half of Claude Opus 5.5’s rate. From December 1, Gemini 4 Argon and Claude Opus 5.5 will be identically priced, leaving GPT-6.1 Sol as the clear budget option at that point, assuming OpenAI doesn’t move its own price in the meantime. None of the three companies has published consumer subscription pricing specific to these individual models in Australian dollars; the figures above are developer and enterprise API rates, which is how all three bill regardless of customer location.
Coding and Agentic Benchmarks
Benchmarks across three different labs rarely use the same test, which makes a true apples-to-apples score comparison almost impossible. What’s available instead is each vendor’s strongest claim on its own preferred measure, plus one independent third-party result for GPT-6.1 Sol specifically. Taken together, they sketch three different strengths rather than one clear winner.
Anthropic’s own FrontierCode benchmark, which measures whether an agent’s code changes would actually be merged into a real repository, has Claude Opus 5.5 scoring 54.6% at default (medium) effort. Anthropic says that beats GPT-6 Astra’s top score of 53.3% on the same test, at roughly a fifth of the cost per completed task. On Anthropic’s AutomationBench, built in partnership with Zapier to test real business workflows across connected apps, Opus 5.5 outscores both its own predecessor Opus 5 and GPT-5.6 Sol at every effort level. On Perplexity’s WANDR benchmark, which measures agents on large-scale data collection tasks, Opus 5.5 again outperforms both Opus 5 and the restricted-access Claude Fable 5.1 at a lower cost per task.
GPT-6.1 Sol’s standout number comes from outside OpenAI. LetsDataScience reported on October 20 that GPT-6.1 Sol’s score on a legacy COBOL code-migration test jumped to 86.6%, up from a previous 5.4% result for an earlier model generation on the same style of task. That’s a 16-fold swing on exactly the kind of unglamorous enterprise work, migrating decades-old mainframe code, that Australian banks, insurers and government agencies still pay specialist contractors to handle by hand. OpenAI’s own documentation adds that GPT-6 Astra still holds the highest score among the models it tested on Terminal-Bench Science 0.1, at 68.1%, and should be the choice for the hardest scientific-research workloads; GPT-6.1 Sol is explicitly not positioned to beat Astra there, only to close the gap at a much lower price.
Gemini 4 Argon’s strongest documented result is security-specific: it ties for first place on CWE-bench v1, a benchmark that scores a model’s ability to find and remediate real software vulnerabilities, with a top score of 68%. Google says this builds on the frontier-level performance its earlier Gemini 3.8 Flash Cyber model already set on the predecessor CWE-bench v0 test. Tech Times reported on October 15 that the benchmark scores circulating for Argon reflect its high-effort mode rather than the default behaviour most subscribers see day to day, a useful caveat for anyone trying to reproduce Google’s numbers on a standard Gemini app account.
One further data point deserves a heavy caveat rather than a table entry. A Chinese finance outlet reported on October 21, 2026 that a robotics simulation benchmark called RoboColiseum scored Claude Opus 5.5 at 76.28 overall, ahead of Gemini 4 Argon at 66.86. That result comes from a single media source, has not been corroborated by any of the three model makers, and should be read as one data point in an embodied-AI niche rather than a verified ranking of general capability.
| Benchmark | Result | Source |
|---|---|---|
| FrontierCode (agentic coding, default effort) | Opus 5.5: 54.6%, ahead of GPT-6 Astra’s 53.3% | Anthropic |
| AutomationBench (Zapier business workflows) | Opus 5.5 outscores Opus 5 and GPT-5.6 Sol at every effort level | Anthropic |
| WANDR (large-scale data collection) | Opus 5.5 outperforms Opus 5 and Fable 5.1 at lower cost | Perplexity / Anthropic |
| COBOL legacy migration | GPT-6.1 Sol: 86.6%, up from 5.4% | LetsDataScience |
| Terminal-Bench Science 0.1 | GPT-6 Astra: 68.1% (highest of models tested; Sol is not the top scorer here) | OpenAI |
| CWE-bench v1 (vulnerability remediation) | Gemini 4 Argon ties for first at 68% |
Context Windows and Output Limits
Context and output capacity is the one area where this comparison isn’t close. Google’s headline change for Gemini 4 Argon is a maximum output limit of 1 million tokens, up from 64,000 tokens on the previous Gemini generation. Google describes this as an industry-leading figure, and on pure arithmetic it’s hard to argue: a more than 15-fold increase means Argon can, in theory, produce a single response long enough to cover an entire legal contract review, a full technical specification, or a complete refactor of a mid-sized codebase without splitting the job into multiple calls.
Neither Anthropic nor OpenAI has published an equivalent standalone output-limit figure for Claude Opus 5.5 or GPT-6.1 Sol in the material reviewed for this comparison, so a direct numeric contest isn’t possible here. What is clear is that both companies are optimising for a different kind of long-running task: not a single enormous response, but many smaller, cheaper, chained responses inside an agentic workflow. Anthropic’s “fast mode” for Opus 5.5, running at up to 2.5 times normal speed in Claude Code, is explicitly built for exactly that pattern, rapid back-and-forth steps rather than one giant output.
For Australian teams, the practical takeaway is to match the model to the shape of the job rather than chasing the single biggest number. A legal team summarising a 400-page compliance document in one pass has a genuine use for Gemini 4 Argon’s expanded ceiling. A development team running dozens of small, iterative pull requests through an autonomous coding agent is better served by a model priced and tuned for high call volume, which is closer to how both Claude Opus 5.5’s fast mode and GPT-6.1 Sol’s low per-token rate are positioned.
Cybersecurity and Vulnerability Remediation
All three vendors are explicitly marketing frontier-tier cybersecurity capability right now, and each has built a gated-access program around it rather than opening the sharpest tools to every user. Anthropic expanded its Cyber Verification Program on October 6, adding three access tiers for qualifying security professionals, with varying levels of access to advanced capabilities across Opus 5.5, Sonnet 5.5, and the more tightly restricted Claude Mythos 5.1. Anthropic frames this as a way to give vetted defenders real offensive-adjacent tooling while keeping the same capability away from the general public.
Google’s equivalent is the Fairwind Program, which gave trusted cyber defenders early access to Gemini 4 Argon ahead of its general release. Google says Argon is designed to find, validate and autonomously patch critical software vulnerabilities, a claim that lines up with its CWE-bench v1 result but is still Google’s own characterisation rather than an independently audited performance assessment. OpenAI’s angle is narrower but concrete: its September 29 addendum to the GPT-6 Astra system card specifically documents GPT-6.1 Sol’s alignment properties, stating that the model shows substantial improvement over GPT-6 Sol on OpenAI’s own alignment evaluations, bringing it closer to GPT-6 Astra’s safety profile.
For Australian security teams evaluating these tools under frameworks like the Essential Eight, the practical difference is access model rather than raw capability. Gemini 4 Argon’s vulnerability-patching claims are the most benchmarked of the three on this specific axis, and hands-on access through the Gemini API and Google AI Studio is already generally available to developers, while the deepest tooling in Antigravity is reportedly gated behind Google AI Ultra. Anthropic’s tiered Cyber Verification Program is the most explicit about vetting who gets what, which may suit regulated organisations that need a documented access trail for compliance audits.
Safety, Governance and Political Evenhandedness
Anthropic has published the most detailed governance paper trail of the three companies across this release window. Beyond the Cyber Verification Program, it introduced “preserved thinking,” an anti-distillation safeguard that stops older or weaker models from reading Opus 5.5 and Fable 5.1’s internal reasoning traces, closing off a pathway that competitors could otherwise use to train cheaper copies off Anthropic’s output. For Claude Sonnet 5.5 specifically, Anthropic says reasoning transcripts are accessible only to the organisation that generated them in the first place.
Anthropic also reported that Opus 5.5, Sonnet 5.5 and Haiku 5.5 each scored 99% on its internal political-evenhandedness evaluation between October 14 and 17, an unusually high and unusually specific figure to publish ahead of the 2026 US midterm elections, which Anthropic separately addressed in its own preparedness guidance. On the research side, Anthropic reported on September 23 that Claude had autonomously identified a novel enzyme system associated with CRISPR-like DNA repeats, an example the company points to as evidence of its models contributing to genuine scientific discovery rather than just answering prompts faster.
Claude Opus 5.5 also carries watermarking measures aimed at compliance with the EU AI Act, and Anthropic notes it is no longer available with “thinking” mode switched off entirely, a change from earlier Opus releases. Zero data retention remains available for enterprise customers, consistent with prior Opus-generation privacy commitments. Neither OpenAI nor Google has published a comparably detailed public safety paper trail specifically for GPT-6.1 Sol or Gemini 4 Argon in the material reviewed here, though OpenAI’s system-card addendum and Google’s dedicated Argon safety-and-security page both exist and cover model-specific risk categories for their respective releases.
Real-World Deployments and Early Results
Benchmarks are one thing; production usage is another. A handful of concrete, named deployments have already surfaced for this generation of models, and they’re worth more than another synthetic score.
- Asana’s browser-agent workflow: OpenAI reported that Asana’s optimised browser-agent setup running on GPT-6.1 Sol averaged about US$0.47 per run and roughly four minutes per run in its own reported test configuration, a concrete cost-per-task figure that’s rare to see published this specifically.
- COBOL legacy migration: GPT-6.1 Sol’s jump to an 86.6% score on a legacy code-migration test, reported by LetsDataScience and corroborated by TechGig’s coverage of the same result, points directly at the mainframe-modernisation work that large Australian banks and government IT departments still budget for every year.
- Zapier’s AutomationBench: Built specifically to test whether an agent can complete real multi-app business workflows, this benchmark has Claude Opus 5.5 beating both its own predecessor and OpenAI’s GPT-5.6 Sol at every effort level, a workflow-automation result rather than a pure coding one.
- Perplexity’s WANDR benchmark: Testing agents on large-scale data-collection tasks, Opus 5.5 outperformed Opus 5 and Fable 5.1 while costing less per completed task, relevant to any team running research or data-aggregation agents at volume.
- CWE-bench vulnerability remediation: Gemini 4 Argon’s tied first-place score of 68% on real vulnerability-patching tasks is a direct, practical result for security operations teams rather than an abstract reasoning test.
- RoboColiseum robotics benchmark (unverified): The single-source Chinese finance report placing Claude Opus 5.5 ahead on embodied-AI tasks is worth tracking as this niche matures, but shouldn’t be treated as confirmed until an independent or official source corroborates it.
What stands out across these examples is specialisation rather than a single model dominating every category. GPT-6.1 Sol’s strongest public result is a narrow, high-value enterprise task. Claude Opus 5.5’s strongest results are in multi-step business and research workflows. Gemini 4 Argon’s strongest result is security-specific. That pattern should shape how any Australian organisation picks between them far more than a single aggregate leaderboard number would.
Availability by Plan: Who Gets Which Model
Plan-level access is the detail most likely to trip up a buying decision, because none of these three models is available identically across every tier its vendor sells. Claude Opus 5.5 is available through the Claude Platform, Amazon Web Services, Google Cloud and Microsoft Azure for developers, and Anthropic’s release notes describe it rolling out to Pro, Max, Team and Enterprise subscribers in the consumer Claude app, with increased five-hour usage limits on those tiers. There is no indication in Anthropic’s own materials that Opus 5.5 is available on a free tier.
GPT-6.1 Sol’s availability is more fragmented. OpenAI’s own release notes confirm it is available to Plus, Pro, Business, Enterprise and Edu users specifically inside ChatGPT Work and Codex, and through the standard API as gpt-6.1-sol. It is explicitly not available on Free or Go plans, and it has not rolled out to ordinary ChatGPT Chat for any plan; that surface is still running on GPT-6 Sol for paid tiers and GPT-6 Luna for Free and Go. Anyone expecting GPT-6.1 Sol to simply “be” their ChatGPT Plus experience is working from an outdated assumption.
Gemini 4 Argon sits in the Gemini app and Google Search’s AI Mode for Google AI Pro and Google AI Ultra subscribers, with the deepest tooling, Google Antigravity’s agent-oriented coding workflows, reserved for Ultra subscribers only. Developers reach Argon through the Gemini API and Google AI Studio independent of the consumer subscription tiers. None of the three companies has published Australian-dollar subscription pricing specific to these individual model releases in the sources reviewed for this piece, which is a gap worth flagging rather than guessing around.
Migration Guide: Moving to the Newest Generation
Teams already running agents or integrations against the previous generation, Claude Opus 5, GPT-6 Sol, or Gemini 3.8 Flash, face a genuinely different migration path for each vendor. Here’s a practical sequence for moving across safely.
- Audit current model identifiers in code. Search integration code for hardcoded model strings like
claude-opus-5,gpt-6-solor references to Gemini 3.8 Flash, and replace them withclaude-opus-5-5,gpt-6.1-solorgemini-4-argonrespectively. - Re-run cost estimates before switching. Because Opus 5.5 costs less per token than Opus 5 and needs fewer tokens per task, for a combined 40% drop in typical costs, and because Gemini 4 Argon’s rate will double on December 1, a cost comparison needs to be done on a per-completed-task basis, not a per-token basis alone.
- Check that “thinking” mode is handled correctly. Claude Opus 5.5 is no longer available with thinking mode switched off entirely; any integration that previously disabled reasoning for speed needs to be re-tested against the new default behaviour.
- Confirm which product surface you actually have access to. If your integration targets GPT-6.1 Sol, verify it’s calling ChatGPT Work, Codex, or the API directly, since the model is not present in standard ChatGPT Chat regardless of plan.
- Re-test agentic and multi-step workflows separately from single-prompt tasks. AutomationBench, built by Zapier, and Perplexity’s WANDR benchmark show Claude Opus 5.5 outperforming Opus 5 in multi-step workloads; a simple one-shot prompt test won’t reveal that advantage.
- Budget for the Gemini 4 Argon price change now. If you’re building on Argon’s introductory US$2/US$10 rate, model your December and January invoices at US$4/US$20 before committing to production volume.
- Re-apply for cybersecurity program access if relevant. Security teams previously vetted under older access tiers should confirm their standing under Anthropic’s newly expanded Cyber Verification Program or Google’s Fairwind Program rather than assuming prior approval carries over automatically.
- Keep a rollback path open for 30 days. All three companies have a track record of fast iteration this year; keeping the previous model identifier callable as a fallback avoids an outage if a workflow behaves unexpectedly on the new model.
Pros and Cons
Claude Opus 5.5
Claude Opus 5.5 wins on multi-step agentic workflow benchmarks and offers a fast mode purpose-built for high-frequency coding agents. Anthropic’s governance paper trail, including anti-distillation safeguards and a 99% score on its own political-evenhandedness test, is the most detailed of the three. The downside is price: at US$4/US$20 per million tokens, it’s the most expensive of the three today, and it is not available on a free consumer tier.
GPT-6.1 Sol
GPT-6.1 Sol is the cheapest of the three right now, with a documented, independently reported result on legacy code migration that’s hard to ignore for enterprise modernisation work. The downside is availability: it’s locked to ChatGPT Work, Codex and the API, with zero presence in ordinary ChatGPT Chat on any plan, and it explicitly trades some capability for cost compared with OpenAI’s own flagship GPT-6 Astra.
Gemini 4 Argon
Gemini 4 Argon’s 1-million-token output ceiling and tied first-place vulnerability-remediation score make it the strongest choice for long-document work and security operations. The downside is the confirmed price doubling on December 1, 2026, plus the fact that its most advanced tooling, Antigravity, is restricted to Google AI Ultra subscribers only.
Best Use Cases for Australian Teams and Developers
Matching the model to the job matters more than chasing a single winner. Based on the documented strengths above, here’s where each model fits best.
- Legacy system and COBOL migration projects: GPT-6.1 Sol’s 86.6% score on legacy-code migration, paired with its lower per-token price, makes it the strongest documented option for banks, insurers and government agencies working through mainframe modernisation backlogs.
- High-volume, multi-step business automation: Claude Opus 5.5’s results on WANDR, plus its fast mode for rapid iterative calls, suit agentic workflows that chain many smaller actions together, such as finance operations or large-scale research aggregation.
- Long-document legal, financial or compliance review: Argon’s 1-million-token output limit is the only one of the three built to handle a very long single document in one pass without manual chunking.
- Cost-sensitive agentic coding at scale: Both GPT-6.1 Sol and Gemini 4 Argon’s introductory pricing undercut Claude Opus 5.5 by half; teams running thousands of small coding-agent calls per day should model both before committing, keeping the December 1 Argon price change in mind.
- Regulated industries needing a documented access trail: Anthropic’s explicitly tiered Cyber Verification Program may suit organisations that need to show auditors exactly how advanced-capability access was granted and to whom.
- General consumer chat: none of these three models power everyday ChatGPT, Claude or Gemini chat for most users today; that role still belongs to GPT-6 Sol/Luna, the standard Claude 5.5 lineup, and earlier Gemini releases respectively, which is worth remembering before assuming a subscription automatically includes frontier-tier access.
The Verdict: Which Model Wins on the Data
There isn’t a single winner across this three-way comparison, and the data doesn’t support pretending otherwise. On price today, Claude Opus 5.5 costs $4 per million input tokens and $20 per million output tokens, while GPT-6.1 Sol and Gemini 4 Argon are both priced at $2 per million input tokens and $10 per million output tokens. That changes on December 1, when Gemini 4 Argon’s price is set to move to $4 per million input tokens and $20 per million output tokens, leaving GPT-6.1 Sol as the cheaper option from that date. On raw capacity, Gemini 4 Argon’s 1-million-token output limit is unmatched by any published figure from the other two. On agentic workflow benchmarks, Claude Opus 5.5 outperforms Claude Opus 5 on both AutomationBench and WANDR, though that doesn’t settle how it compares with GPT-6.1 Sol or Gemini 4 Argon on those same tests. On a single, concrete enterprise task, legacy COBOL migration, GPT-6.1 Sol’s 86.6% score is the standout number in this entire comparison.
For Australian organisations making a near-term decision, the practical read is this: pick GPT-6.1 Sol if the job is narrow, high-value, and cost-sensitive, particularly legacy-code work; pick Claude Opus 5.5 if the job is a long multi-step agentic workflow where Anthropic’s benchmark lead and governance documentation matter more than the sticker price; pick Gemini 4 Argon if the job genuinely needs either very long single-document output or security-specific vulnerability remediation, while planning now for its December price change. None of the three is a universal replacement for the other two, and that specialisation, more than any single leaderboard score, is the real story of this release cycle.
Frequently Asked Questions
What is Claude Opus 5.5 and when was it released?
Claude Opus 5.5 is Anthropic’s flagship model. Anthropic released it as the first model in the Claude 5.5 family, saying it performs at the level of Claude Fable 5.1 on most work while costing 40% less to run than Opus 5.
What is GPT-6.1 Sol and how does it differ from GPT-6 Astra?
GPT-6.1 Sol is OpenAI’s upgraded coding and computer-use model, priced at roughly one-fifth of GPT-6 Astra’s standard rate while approaching Astra’s intelligence on several evaluations. GPT-6 Astra remains OpenAI’s top model for the hardest scientific-research tasks, where it still holds the highest tested score.
What is Gemini 4 Argon and when did it become generally available?
Gemini 4 Argon is Google’s current frontier model, announced September 30, 2026, and taken to general availability on October 13, 2026, through the Gemini API, Google AI Studio, and the Gemini app for Google AI Pro and Ultra subscribers.
Which of the three models is cheapest for high-volume coding tasks?
As of October 21, 2026, GPT-6.1 Sol and Gemini 4 Argon are tied at US$2 per million input tokens and US$10 per million output tokens, both half of Claude Opus 5.5’s US$4/US$20 rate. That changes on December 1, 2026, when Gemini 4 Argon’s price doubles to match Opus 5.5, leaving GPT-6.1 Sol as the cheapest of the three from that date.
Can ChatGPT Free or Go users in Australia access GPT-6.1 Sol?
No. OpenAI’s release notes list GPT-6.1 Sol as unavailable on Free and Go plans. It is available to Plus, Pro, Business, Enterprise and Edu users, but only inside ChatGPT Work and Codex, not in standard ChatGPT Chat on any plan.
Will Gemini 4 Argon’s pricing change, and when?
Yes. Google has confirmed on its own release pages that Argon’s introductory price of US$2 per million input tokens and US$10 per million output tokens applies only until November 30, 2026. From December 1, 2026, the price rises to US$4 per million input tokens and US$20 per million output tokens.
Which model is best for cybersecurity teams?
Gemini 4 Argon has the most specific benchmarked result for this use case, tying for first place on CWE-bench v1 vulnerability remediation at 68%. Anthropic’s Claude Opus 5.5 offers the most explicitly tiered access program through its Cyber Verification Program, which may suit organisations needing a documented approval trail.
Is Claude Opus 5.5 available through AWS, Azure and Google Cloud at the same time?
Yes. Anthropic’s own release page confirms Claude Opus 5.5 is available on all three major cloud platforms, Amazon Web Services, Google Cloud and Microsoft Azure, in addition to the Claude Platform directly, under the model identifier claude-opus-5-5.
