On list prices as of 14 October 2026, GPT-6.1 Sol is the cheapest of the three at $2 input and $10 output per million tokens, Claude Opus 5.5 costs $4 and $20, and Gemini 4 Argon is $2 and $10 until 30 November 2026, then $4 and $20. No public benchmark crowns a single winner for marketing work: each vendor's numbers favour its own model, and independent aggregators disagree with each other. The honest answer is to run your own briefs through all three and measure edit time.
Key Takeaways
- Price per million tokens: Sol $2/$10, Argon $2/$10 (introductory, then $4/$20), Opus 5.5 $4/$20.
- Access differs: Argon needs a paid Google plan or API paid tier; Sol is in ChatGPT Work and Codex plus the API; Opus 5.5 is on Claude plans and the API.
- Benchmarks are mixed. Argon leads some of Google's own rows, Opus 5.5 leads others, and aggregators LLM Stats and Artificial Analysis rank them differently.
- Cost per task is not cost per token. Artificial Analysis reports Argon used far more output tokens per task than Astra.
- None of these benchmarks measures brand-voice writing, Indian-language quality or your CMS workflow.
- Use a 10-brief bake-off scored on edit minutes, factual errors and cost per accepted asset.
What I could and could not compare
I did not run these models side by side for this post. Everything below is from vendor pages and third-party aggregators I opened, labelled by source. Where sources conflict, I say so. If you want my existing view of the earlier generation, see my Astra vs Fable 5.1 content-team comparison and my model-choice guide. The Arena Alignment Index post covers the behavioural side.
The core comparison table
| Gemini 4 Argon | GPT-6.1 Sol | Claude Opus 5.5 | |
|---|---|---|---|
| Input / output per 1M tokens | $2 / $10 to 30 Nov 2026, then $4 / $20 | $2 / $10 | $4 / $20 |
| Cached input per 1M | $0.10 intro, $0.20 after | Not listed on the aggregator page I read; ProPakistani reports $0.10 | $0.20 |
| Context window | Google's launch post gives a 1M output limit; input window not clearly stated in Google's text | About 1.05M input, 128K output per LLM Stats | 1M input, 128K output per LLM Stats |
| Released | Announced 30 Sep 2026; subscriber rollout 13 Oct | Late Sep 2026 | 22 Sep 2026 |
| Where you use it | Gemini app (Pro/Ultra), AI Mode, Antigravity (Ultra), paid API | ChatGPT Work and Codex (Plus and up), API | Claude plans, API, Claude Code |
Sources: Google pricing page, Google's Argon post, Anthropic's Opus 5.5 page, ProPakistani on Sol, LLM Stats Opus vs Sol. Sol's $2/$10 comes from a secondary report and an aggregator, so confirm on OpenAI's pricing page before you budget. One source notes Sol's rate applies to inputs up to 272K tokens.
What each vendor claims
Gemini 4 Argon (Google, 30 September 2026)
Google reports 77.9% on DeepSWE v1.1, 91.7% on LVBench and a first-place AutomationBench result of 51.3%, per its launch post. A relay of Google's full table by eesel shows Argon trailing on Terminal-Bench 4.0 (57.4% against Opus 5.5's 66.4%) and FrontierSWE (55.0% against 65.5% for GPT-6 Astra). Notably, that table compares Argon with Astra, not Sol.
GPT-6.1 Sol (OpenAI)
OpenAI says Sol gives near-Astra performance on agentic coding, computer use and professional work at one-fifth Astra's price, as reported by ProPakistani. It lists AutomationBench at 2.2 points above Opus 5.5 at about a third of the cost. These are OpenAI claims relayed by a news site.
Claude Opus 5.5 (Anthropic, 22 September 2026)
Anthropic says Opus 5.5 performs at the level of Fable 5.1 on most work, costs 40% less to run than Opus 5 on typical workloads and is more than 30% faster. It also says thinking mode can no longer be switched off, which affects latency planning. Again, vendor claims.
What independent sources say
Independent data points in different directions, which is itself the finding.
- Artificial Analysis scores Argon 53 on its Intelligence Index, tied with Astra and one point above Sol, according to its Argon report. It also says Argon averages 62K output tokens per task versus 27K for Astra, and puts Argon's cost per index task at $1.99 on introductory pricing, 2.7 times Sol's cost. A DEV Community write-up citing Artificial Analysis puts Opus 5.5 higher on that index (58 against 53); I could not confirm that figure on Artificial Analysis's own page.
- LLM Stats gives Opus 5.5 a composite score of 60.7 against Sol's 54.0 and Argon's 55.4 on its own methodology, with Opus winning most shared benchmarks; see its Opus vs Argon page. It warns the models are not evaluated on identical numbers of benchmarks.
- Hands-on tests are thin. One October test on a Mac mini (lilting.ch) could not use Argon at all and substituted Gemini 3.8 Flash, so it says nothing about Argon.
So "Which is best?" has no supported answer today. "Which is cheapest per accepted draft on my work?" does.
Where each might fit in marketing work
This is my working hypothesis, not a benchmark result. Test before adopting.
| Marketing task | What to test first | Why (assumption to verify) |
|---|---|---|
| Long-form drafting in a brand voice | Opus 5.5 and Sol | Both have long outputs of 128K; Opus has a cheap $0.20 cache read for a style guide |
| Bulk meta descriptions, tagging, classification | Cheapest model that passes | Cost per item dominates; consider smaller models such as Haiku 5.5 (see Haiku vs Sonnet) |
| Long document review (decks, contracts, transcripts) | Argon | Google reports an 84.2% GraphWalks long-context result, a vendor claim; verify on your files |
| Agent workflows in ads, CRM, shops | Whichever sits in your tool stack | Argon's tasks mode and 40+ connected apps vs Sol in Codex vs Claude Code |
| Video understanding | Argon | Google reports 91.7% on LVBench, vendor claim |
| Anything touching customer data | The one with a zero-data-retention option you have approved | Check each vendor's terms |
Cost math with a realistic content job
Take one 1,500-word post: say 6,000 input tokens (brief, style guide, outline) and 3,000 output tokens per draft, with two drafts per accepted post. That is a made-up job for arithmetic, not a measured one.
- Input: 12,000 tokens. Output: 6,000 tokens.
- Sol at $2/$10: $0.024 + $0.060 = $0.084.
- Argon at intro $2/$10: also $0.084; at $4/$20 from 1 December: $0.168.
- Opus 5.5 at $4/$20: $0.168.
At this scale the model bill is cents, and your editor's time is the real cost. Reasoning tokens can change the maths: Argon's higher output per task on Artificial Analysis shows token use can offset a low token price. For a deeper cost walk-through of Argon see my Argon API pricing post.
A 10-brief bake-off you can run this week
- Pick 10 real briefs. Include 4 easy, 4 typical and 2 hard ones, such as a regulated claim or a Hindi-English mix.
- Fix everything except the model. Same prompt, same style guide, same reference docs, same effort setting where available.
- Run each brief twice per model. Variance is real; one run is an anecdote.
- Blind the outputs. Strip model names before your editor scores.
- Score four things: factual errors found, minutes to make it publishable, brand-voice misses, and cost per accepted draft.
- Add one trap per brief. Include a wrong number in the source material and see whether the model repeats it.
- Decide by cost per accepted asset, not price per million tokens.
A scoring sheet
| Brief | Model | Run | Factual errors | Edit minutes | Voice misses | Tokens in/out | Cost |
|---|
Access and compliance questions
- Plan gating. Argon in the API is paid-tier only, and Antigravity needs Ultra per 9to5Google. Sol appears in ChatGPT Work and Codex rather than regular ChatGPT conversations, per ProPakistani.
- Data handling. Google's pricing page says Argon does not use customer content to improve Google's products on the paid tier. Check Anthropic's and OpenAI's current terms yourself.
- Region. Argon's tasks mode is limited to select countries per SiliconANGLE. I have not confirmed availability in India for any of the three, so check your account.
What I would do as a small team
- Keep one default model for drafting and one cheap model for bulk work.
- Run the bake-off once now and once after the Argon introductory period ends, because a price doubling can flip the ranking.
- Do not move your whole stack on a launch-week benchmark.
- Record the model name inside every content brief so that you can trace quality problems later.
FAQ
Which is cheapest: Gemini 4 Argon, GPT-6.1 Sol or Claude Opus 5.5?
On list price, Sol at $2/$10 per million tokens and Argon's introductory $2/$10 are equal and cheapest; Opus 5.5 is $4/$20. Argon rises to $4/$20 on 1 December 2026. Cost per finished task can differ because models use different numbers of tokens.
Which model is best for content writing?
No source I found measures brand-voice writing across the three. Run a blind test on your own briefs. Opus 5.5 has a cheap cache-read rate that suits a long style guide, but that is a cost point, not a quality claim.
Is Gemini 4 Argon better than Claude Opus 5.5?
It depends on the benchmark. Google reports Argon ahead on DeepSWE and long-context tests, while Opus 5.5 leads Terminal-Bench 4.0 and appears higher on Artificial Analysis's index per a secondary write-up. Aggregators disagree on composites.
Can I use Argon for free?
No. The API lists it as unavailable on the free tier, and the Gemini app needs Google AI Pro or Ultra. Google has a free six-month Antigravity programme for up to 10,000 scientists.
How big are the context windows?
LLM Stats lists 1M input and 128K output for Opus 5.5 and about 1.05M input for Sol. Google's own text emphasises Argon's 1M output limit and does not clearly state the input window, so check Google's docs.
Are these benchmark numbers trustworthy?
Treat vendor numbers as marketing claims run on vendor-chosen setups. Independent trackers help but use their own methods and can disagree. Your own blind test is the most relevant evidence.
Does model choice affect SEO?
Not directly. Models you use to write content do not change how Google ranks it. Google's guidance cares about quality and helpfulness, not tool. Argon as an AI Mode engine is a separate topic covered in my Argon in AI Mode post.
Should I switch my stack right now?
Probably not in launch week. Run the bake-off, check data terms, and revisit after 30 November when Argon's introductory price ends.
What about Claude Mythos or Fable?
Mythos 5.1 is gated to vetted cyber and life-sciences organisations, so it is not a marketer tool. Fable 5.1 remains available at $10/$50 per million tokens, per my earlier posts.
Let's talk about your AI workflow
I'm Younus Fardeen, an organic growth, SEO and AEO strategist with 4+ years of marketing experience across edtech and startups. If you want help turning a model comparison into a workflow your team can run, see my work and reach me through the contact form at younusfardeen.in. Everything above is as of 14 October 2026, and vendor figures are attributed to their sources.