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Gemini 4 Carbon costs $7.76 per Intelligence Index task, ~23% less than Claude Opus 5.5 (max, $10.04) but ~1.2x GPT-6 Astra (max, $6.25). It uses 123k output tokens per task, 29% fewer than Claude Opus 5.5 (max, 173k). At the same $4/$20 standard pricing, its Cost per Task is in line with Gemini 4 Argon ($7.68), while scoring 9 points higher on the Intelligence Index. October 28, 2026
In Google's announcement of the new Gemini 4 model , it talked up its collaboration with the U.S. government for model screening and pre-release testing. In a similar manner to the way Anthropic handled Mythos' release in 2025, Google is rolling out access to Gemini 4 Carbon at a slower pace.
"We're taking a deliberate approach to rollout and are actively engaged in the U.S. government’s voluntary process for pre-release model testing," Google's launch statement reads .
To that end, it's opening up Carbon to a subset of "cyber defenders," and will gradually make the model more widely available through trusted partners through its Fairwind Program . Before it makes Carbon available to developers, it wants to iterate on its guardrails to make the AI safer and more effective for cybersecurity purposes, making it harder for nefarious actors to use it for exploits and hacking.
Where the idea of slowing the industry and introducing greater oversight for model development has risen and fallen in the estimations of the major tech companies, it does appear to be cementing itself as more of a foundational idea for future model releases. Google talks up its release on the improved safety and security of its model, highlighting that it thwarted all attempts from the Gray Swan Indirect Prompt Injection benchmark to have it do something it shouldn't.
Google claims Carbon cuts unsupported claims in its responses twice as much as the Gemini 4 Argon model it debuted just two weeks ago. If it can't complete an action, it will just not do so, rather than fabricating an answer or hedging around missing evidence, Google claims.
It also suggests Carbon will present sources and suggested actions to the user more readily, rather than pursuing its own intentions when there are discrepancies or uncertainties, allegedly cutting model overreach by 26%.
As governments and companies look to make realistic use of AI, tracking usage, managing token budgets, and preventing workers from creating new exploit paths through overuse, a model's safety, security, and reliability will be paramount.
Gemini 4 Carbon scores 54 on AA-Omniscience, the highest of any model, 6 points ahead of Claude Opus 5.5 (max, 48). It answers more questions correctly than Gemini 4 Argon (58% vs 48% accuracy), at the cost of a higher hallucination rate (11% vs 4%). This is still far below Claude Opus 5.5 (max) and GPT-6 Astra (max), both at 50% October 28, 2026
For the past year, a clear focus from frontier and open-weight model developers has been on efficiency and cost. While raising intelligence and improving capabilities, particularly through agentic workflows, has seen great development alongside pomp and circumstance, many of the major announcements and developments have also considered cost a clear component.
That's not likely to change, with the latest research from Gartner showing that just 3% of companies are actually achieving cost and productivity improvements from AI use. But as organizations push to find the real value in AI, maximize token budgets, and try to empower workers who have found improvements from using AI, they'll want consistency.
Tracking return on investment with AI is notoriously difficult, with hallucinations making that far harder. If Google can sell its latest model(s) as the safest and least likely to hallucinate, and do so with high intelligence at a relatively low cost, that might be the new winning formula.
Jon Martindale Freelance Writer Jon Martindale is a contributing writer for Tom's Hardware. For the past 20 years, he's been writing about PC components, emerging technologies, and the latest software advances. His deep and broad journalistic experience gives him unique insights into the most exciting technology trends of today and tomorrow.
Key considerations
- Investor positioning can change fast
- Volatility remains possible near catalysts
- Macro rates and liquidity can dominate flows
Reference reading
- https://www.tomshardware.com/tech-industry/artificial-intelligence/SPONSORED_LINK_URL
- https://www.tomshardware.com/tech-industry/artificial-intelligence/google-reveals-new-gemini-4-carbon-ai-model-narrowly-beating-claude-opus-5-5-frontier-ai-model-is-also-the-least-likely-to-hallucinate-benchmarks-claim#main
- https://www.tomshardware.com/my-account
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