Google announced Gemini 4 Carbon on Oct 28, 2026, and the number everyone is quoting is 59 on the Artificial Analysis Intelligence Index v5.0. On the Gemini 4 Carbon vs Claude Opus 5.5 question, that looks like a one-point lead. Two caveats matter more than the gap: the 59 comes from Google’s announcement, and most developers cannot call the model yet.
As of Nov 2, Carbon is going to selected cyber defenders first, with no general availability date. This guide compares Carbon with Gemini 4 Argon, Claude Opus 5.5 and GPT-6 Astra, and keeps vendor claims apart from independent data. This first part covers the scores, the claims and the access picture.
Key Takeaways
- Carbon scores 59 on AA Intelligence Index v5.0 according to Google’s announcement. I did not find an Artificial Analysis page for Carbon, so treat the figure as vendor-reported for now.
- Claude Opus 5.5 (Max) shows 58 on AA’s own page, and GPT-6 Astra (Max) shows 57. A one- or two-point gap is thin evidence for a clear winner.
- Carbon’s introductory API price is $2 input / $10 output per million tokens, the same as Argon. A footnote reportedly puts the later price at $4 / $20, and no source says when the introductory rate ends.
- Access is the real limit. Carbon is for a subset of cyber defenders, then more partners through Google’s Fairwind Program. Opus 5.5 is generally available today.
- Do not compare scores across Index versions. Only v5.0 numbers belong next to Carbon’s 59.
Table of Contents
- Gemini 4 Carbon vs Claude Opus 5.5: What the v5.0 Scores Show
- Vendor Claims vs Independent Data
- Gemini 4 Carbon P
ricing and Availability: Who Can Actually Buy It - Side-by-Side: Carbon, Argon, Opus 5.5 and Astra
- Which Model to Use: A Pick-by-Use-Case Guide
- Pros, Cons and What to Do Next
- Frequently Asked Questions
- Conclusion
Gemini 4 Carbon vs Claude Opus 5.5: What the v5.0 Scores Show
The only fair comparison right now uses Index v5.0, which Artificial Analysis released on Oct 28. The index changed versions several times recently (v4.1.1 at Astra’s launch, v4.3.2 in late September and early October), and scores from different versions are not comparable.
| Model | AA Intelligence Index v5.0 | Source status |
|---|---|---|
| Gemini 4 Carbon | 59 | Reported by Google, citing AA v5.0 |
| Claude Opus 5.5 (Max) | 58 | On AA’s model page |
| Claude Opus 5.5 (xhigh) | 57 | On AA’s xhigh page |
| GPT-6 Astra (Max) | 57 | On AA’s model page |
| Gemini 4 Argon | Not confirmed | No v5.0 score in the sources I reviewed |
Carbon sits at the top of this list, but by one point over Opus 5.5 and two over Astra. The claim also rests on Google’s own post. gHacks notes that all Carbon benchmark figures come from the announcement without independent verification.
Is Claude Opus 5.5 at 58 or 58.4?
Sources disagree, and the explanation is simple. AA’s own page for Opus 5.5 (Max) shows the whole number 58. The aggregator ModelCap lists 58.4 for the Reasoning configuration in a snapshot dated Oct 28. The 58.4 may be an unrounded value, but I could not confirm that from AA. The safest reading is 58 on AA’s Intelligence Index v5.0, with some aggregators showing 58.4. Either way, it stays below Carbon’s reported 59.
One more trap: a NeuralTrust piece shows decimals such as Opus 57.6, Argon 52.6 and Astra 52.7. Those belong to the older v4.3 index and should not be set beside v5.0 figures.
Gemini 4 Carbon vs Argon
I do not have a confirmed v5.0 score for Argon, so I will not rank it against Carbon on the index. What the sources do confirm is that the two share the same introductory API price, and Carbon uses the same safety and security stack as Argon. Google says Carbon cuts unsupported claims by about 2x versus Argon in its internal testing, which is a vendor claim rather than independent data.
Vendor Claims vs Independent Data
Most of what makes Carbon look strong comes from Google. That does not make it wrong, but it changes how much weight you should give it when choosing a production model.
What Google says about Carbon
- Carbon is Google’s strongest model, with state-of-the-art cybersecurity and long-horizon capabilities, per the announcement.
- It ranks #1 on AA Index v5.0 at 59.
- It gains +89 Elo points to #4 (1769) on WebDev Arena, according to 9to5Google.
- Its external cyber benchmarks were run without guardrails, which is a point to remember when reading those results. Production deployments run with the safety stack on.
What is independently visible
For the rivals, AA publishes model pages. Opus 5.5 (Max) generated 220M output tokens on the index, at the high end against a median of 70M. Its xhigh setting costs $6.05 per index task, while Astra (Max) costs $6.24 per task and runs at 78.2 tokens per second. Cost per task is not list price, but it shows what the benchmark run actually consumed. I found no equivalent AA page for Carbon.
Even vendor-reported numbers for the rivals can split. Anthropic reports Terminal-Bench 4.0 at 66.4% for Opus 5.5, per AlphaCorp, while ModelCap shows 64.9% from its AA-based board. They are different sources and should not be treated as one number.
Gemini 4 Carbon P
ricing and Availability: Who Can Actually Buy It
Carbon’s introductory API price is $2 input and $10 output per million tokens, matching Argon, according to gHacks. Cached input tokens cost 95% less than the standard input rate, which works out to about $0.10 per million at the introductory price. Unite.ai reports that a footnote in the announcement lists $4 input and $20 output after the introductory period. I found no source that says when that period ends.
The price matters less than access. Google says Carbon starts with a subset of cyber defenders, then phases in more trusted partners through its Fairwind Program. Forbes reports that Google says Fairwind works with more than 650 partners. Google only says developers, businesses and consumers will get Carbon “soon,” and gHacks notes there is no date for public API access. If you are not in a vetted program, $2/$10 is a number to watch, not a price you can pay.
Side-by-Side: Carbon, Argon, Opus 5.5 and Astra
| Model | AA Index v5.0 | API price per 1M tokens (input / output) | Access |
|---|---|---|---|
| Gemini 4 Carbon | 59 (Google-reported) | $2 / $10 introductory; $4 / $20 later, per a footnote | Selected cyber defenders; no GA date |
| Gemini 4 Argon | Not confirmed | $2 / $10, matching Carbon’s introductory rate | Not confirmed in my notes |
| Claude Opus 5.5 | 58 (Max); 57 (xhigh) | $4 / $20; Batch API $2 / $10; fast mode $8 / $40 | Generally available on the Claude API, Amazon Bedrock, Google Cloud and Microsoft Foundry |
| GPT-6 Astra | 57 (Max) | $10 / $50 | Released by OpenAI; API ID gpt-6-astra |
Opus 5.5 specifics come from Powerdrill and Emergent. They include a 1M-token context window by default, 128k max output and $0.20 per million for cache reads. Astra has a context window of about 1.05M tokens. Artificial Analysis says its prices are 2.5x those of GPT-5.6 Sol. The Sept 3 Astra release date comes from a single secondary source, so treat it as unconfirmed.
List price is not the whole bill. AA says Opus 5.5 (Max) produced 220M output tokens on the index, well above the 70M median. Astra (Max) costs $6.24 per index task and Opus 5.5 xhigh costs $6.05, so the two cost about the same to run on this benchmark despite a 2.5x gap in list price. Anthropic estimates typical workloads cost about 40% less than before because the model uses fewer tokens, though that is a vendor estimate.
Which Model to Use: A Pick-by-Use-Case Guide
Coding and agent work today
Opus 5.5 is the pick if you need a top-tier model you can call right now. It sits at 58 on AA’s own page, is generally available on four platforms, and has a documented coding result: Anthropic reports 66.4% on Terminal-Bench 4.0, while ModelCap’s AA-based board shows 64.9%. Those are different measurements, so do not average them. Carbon’s coding evidence in my notes is limited to Google’s claim of #4 on WebDev Arena at 1769. That is vendor-reported and covers web development only.
If you run Claude through Google’s cloud, see our guide to Claude on Google Cloud.
Security teams
Carbon is built for this audience. Google calls its cybersecurity capability state-of-the-art, and its external cyber benchmarks were run without guardrails. If you are a defender at a qualifying organization, ask Google about Fairwind. Everyone else should wait for independent cyber evaluations before changing tools. For something available now, our piece on Claude Security covers continuous scanning.
Cost-sensitive workloads
Argon shares Carbon’s $2/$10 price, but I could not confirm a v5.0 score or its availability, so check Google’s current documentation before planning around it. Opus 5.5 through the Batch API also lands at $2/$10 for jobs that can wait. Astra is the most expensive of the four at $10/$50 and needs a clear reason to justify that.
Teams already on OpenAI
Astra at 57 is within one or two points of the others, so staying put is defensible if your tooling is built around it. Cost is the main argument against it. OpenAI also has a lower-cost option; read about GPT-6.1 Terra before committing to Astra’s pricing.
Pros, Cons and What to Do Next
Strengths and limits
- Carbon pros: highest reported index score (59), low introductory price, same safety stack as Argon.
- Carbon cons: no independent score, no general availability, and the price may double to $4/$20.
- Opus 5.5 pros: available now, 1M context, several price levers (Batch API, caching).
- Opus 5.5 cons: heavy output-token use on the index, and the score is one point behind Carbon on the reported numbers.
- Astra cons: highest price, and a score of 57 does not justify the premium on benchmark evidence alone.
Steps for developers and teams
- Check the live AA leaderboard for current v5.0 scores before you decide.
- Run your own test set on Opus 5.5 and your current model. A two-point index gap says little about your tasks.
- Budget for the $4/$20 Carbon price, not $2/$10, if you plan to adopt it later.
- If you are a security team, apply for Fairwind access instead of waiting for public availability.
- Keep model choice swappable in your code so a switch costs a config change, not a rewrite.
Frequently Asked Questions
Does Gemini 4 Carbon beat Claude Opus 5.5?
On reported v5.0 numbers, 59 beats 58 by one point. Google reports the Carbon figure and I found no AA page for it, so I would not call it a verified win.
Is Claude Opus 5.5’s score 58 or 58.4?
AA’s own page shows 58. ModelCap shows 58.4 for the Reasoning configuration. The decimal may be unrounded, but I could not confirm that from AA.
Can I use Gemini 4 Carbon today?
Only if you are among the selected cyber defenders Google is onboarding. Public API access has no date.
How much does Gemini 4 Carbon cost?
The introductory rate is $2 input and $10 output per million tokens. A footnote reportedly lists $4 and $20 afterward, and no source says when the switch happens.
What is the best AI model for coding in November 2026?
Among models you can use now, Opus 5.5 has the clearest case from the sources I reviewed. Carbon may change that once it ships and gets independent testing.
Conclusion
Carbon has the highest reported score, but it is a vendor figure for a model few people can call. Use Opus 5.5 for coding and agent work today, keep Astra only if your stack already depends on it, and
