Gemini 4 Carbon is now available

Google released Gemini 4 Carbon to developers, enterprises, scientists and consumers, following a two-week early release to cybersecurity defenders through its Fairwind Program. Google said Carbon ranks #1 on CursorBench 4.0, Perplexity's WANDR and Zapier's AutomationBench at more than 2X lower cost per task than the next best external model, and is priced at the same introductory rate as Gemini 4 Argon: $2 per million input tokens and $10 per million output tokens. Google also previewed /swarm in Google Antigravity, which turns a single prompt into a coordinated team of agents, and partnered with Artificial Analysis on a new Multimodal Knowledge Agent benchmark, where Carbon ranks #2 at more than 6X lower average cost per task than the top model.

Gemini 4 Carbon is now available Today, we’re making Gemini 4 Carbon available to developers, enterprises, scientists, and consumers. Carbon is our strongest model with frontier performance in cybersecurity capabilities and long-horizon agentic workflows across complex knowledge work, software engineering, and scientific reasoning. Two weeks ago https://blog.google/innovation-and-ai/models-and-research/gemini-models/introducing-gemini-4-carbon/ , we released Carbon to a set of cybersecurity defenders via our Fairwind Program https://deepmind.google/fairwind-program/ . Following our recent launch of Gemini 4 Argon https://blog.google/innovation-and-ai/models-and-research/gemini-models/introducing-gemini-4-argon/ , Carbon pushes the frontier even further. Argon remains the ideal choice for the majority of software engineering and knowledge work, while Carbon is built for tasks that test the limits of a model’s intelligence like complex, multi-step coding and debugging and open-ended scientific research and discovery — using more tokens than Argon to explore thoroughly, reason deeply, and run extended verification loops. Across independent benchmarks designed to test model performance in real workflows, Carbon pairs frontier accuracy with practical production economics. It ranks 1 on CursorBench 4.0 https://cursor.com/cursorbench , Perplexity’s WANDR https://www.perplexity.ai/hub/blog/wandr-benchmark-evaluating-research-agents-that-must-search-wide-and-deep , and Zapier’s AutomationBench https://zapier.com/benchmarks at more than 2X lower cost per task compared to the next best external model. To put Carbon’s capabilities to work on larger and complex projects, we’re previewing http://antigravity.google/blog/gemini-4-carbon-in-google-antigravity/ /swarm in Google Antigravity, turning a single prompt into a coordinated team of agents you can track in real time. Developers can assign Carbon to roles that demand the deepest reasoning, like architectural design, coordination, and auditing, while pairing it with faster, lighter models across parallel isolated workspaces and adversarial verifiers that test every change. Gemini 4 Carbon is available via the API in Google AI Studio https://aistudio.google.com/prompts/new chat?model=gemini-4-carbon and Gemini for business https://cloud.google.com/gemini-enterprise for all paying developers and enterprises, at the same introductory price https://aistudio.google.com/docs/pricing <sup 1</sup footnote-1 as Gemini 4 Argon $2 per million input tokens and $10 per million output tokens . It is also rolling out to all Google AI Ultra subscribers in Google Antigravity https://antigravity.google/ , the Gemini app http://gemini.google.com/ , and AI Mode in Search http://aimode.google/ . Higher-precision knowledge work, artifact generation, and data analysis Across legal, finance, and enterprise operations, Gemini 4 Carbon combines frontier visual understanding, reasoning, and exhaustive retrieval to synthesize grounded insights across large sets of dense documents and data. It follows strict schemas and formatting to generate polished and precise spreadsheets, presentations, and reports. Existing benchmarks don’t adequately capture how agents reason natively over dense files with charts, images, blueprints, schematics, and tables, so we partnered with Artificial Analysis to launch the new Multimodal Knowledge Agent https://artificialanalysis.ai/evaluations/mka MKA benchmark that tests a model’s multimodal performance in agentic workflows. Carbon ranks 2 while being more than 6X lower in average cost per task compared to the top performing model. In pre-release evaluations, Carbon matched the performance of the best model tested on deep financial research on Hebbia’s E2E Financial Agentic evaluation, and ranked at the top out of 23 frontier model configurations on Balyasny Asset Management’s General Financial Intelligence benchmark, spanning legal expertise, agentic tool use and execution, coding and data engineering, and perception and context understanding. Improved agentic coding, full stack development, and 3D and UI design Carbon performs exceptionally well on engineering tasks that require multi-agent collaboration like multi-package migrations, cross-subsystem root-cause investigations, and complex architectural redesigns. For web app development, it runs build-and-verify loops, recovers from errors, and checks both its code and the rendered UI to produce complete, working applications. Stronger visual design, spatial reasoning, and attention to environmental detail also carry over to 3D game development and creative coding. Frontier cybersecurity capabilities Gemini 4 Carbon for cyber delivers our strongest cybersecurity capabilities to date, giving security teams the end-to-end intelligence they need in protecting critical software. When accessed through the Fairwind Program, Carbon leads on key benchmarks across finding SEC-bench Pro , exploiting ExploitGym , and patching CWE-bench v1 vulnerabilities: inspecting software, tracing how flaws can be chained together across systems, and generating verified root-cause patches. Early testers inside and outside of Google are already seeing strong results with Carbon for cyber in practice. - In Project Fortify https://cloud.google.com/transform/how-google-does-it-using-agents-help-find-track-and-fix-vulnerabilities , Google’s autonomous system spanning scanning, triage, and remediation, Carbon hit 100% recall on scanning and 95% precision on triage, on our internal benchmark. On Open Source code repository testing we see an over 25% relative improvement on Argon's already strong recall rate, surfacing previously undetected, real-world logic flaws. Bringing these gains across Google, one of the world’s largest users of open-source software, helps secure both our own systems and the broader ecosystem. - Google’s Cloud Vulnerability Research CVR team recently used Carbon to prove that two bugs in a popular open-source software were in fact exploitable vulnerabilities, comparable in severity to the recent PHP2Shell exploit https://www.wiz.io/blog/php2shell-php-rce . By using Carbon to build a proof of concept, CVR helped maintainers re-classify the bug as critical and swiftly issue a patch. Details will be shared after the responsible disclosure process completes. - As part of Wiz’s Scan for Good https://www.wiz.io/blog/scan-for-good-critical-ai-exposures program, the team used Carbon to assess vulnerabilities in public digital infrastructure. For example, when scanning two major SaaS providers, the model uncovered 0-day vulnerabilities in under two hours compressing weeks of vulnerability research to a single afternoon. The team partnered with the impacted organizations to remediate in record time, helping to mitigate potential impact on tens of thousands of companies. Stronger scientific and mathematical reasoning Gemini 4 Carbon shows strongly improved performance in reasoning across physics, math, and life sciences, synthesizing experimental data, testing hypotheses, and reasoning through multi-step domain problems. For drug toxicity research company Axiom Bio, Carbon is now the leading model in performance for translational science, finding novel mechanisms of toxicity they hadn’t found previously. Axiom is now moving their production scientific analyses and agents to both Carbon and Argon to unlock the creation of safer drugs. Researchers across Google have been using Carbon in Google Antigravity to accelerate their work: - Code verification: Researchers built a new agentic framework for formal verification called AlphaProof Code and put it to work on a major security challenge: mathematically proving the actual code underlying the cryptographic protocol of Signal https://deepmind.google/blog/introducing-alphaproof-code . Using Carbon alongside other models, our researchers translated security goals to mathematical theorems. AlphaProof Code agents then used Carbon to generate millions of lines of code in Lean, a computer language for writing mathematical proofs, helping them prove key security properties in weeks — a task that historically takes expert teams years. The result indicates Carbon’s potential to unlock scalable formal verification, long considered a gold-standard approach to building secure software. - Enzyme assay development : Provided with only lab notebooks and raw data, Carbon went beyond standard analysis to surface hard-to-interpret data anomalies, which it used to diagnose subtle wet lab experimental artifacts such as incomplete automated mixing in deep wells, leading to substantially improved reproducibility. Moreover Carbon improved methods to deconvolute chromatography peaks and caught trace sample carryover in research instruments, significantly accelerating the development of new assays and tightening the feedback loop between computation and the bench. - Protein structure prediction: Structure prediction models like AlphaFold 3 use Multiple Sequence Alignments MSAs of evolutionary relatives to help infer how amino acid chains fold. As a result they often struggle on understudied, viral, microbial, and eukaryotic proteins that have very few matches in standard databases. Working in a multi-agent setup, our researchers used Gemini 4 Carbon to autonomously discover remote homologs across petabase-scale unannotated sequence archives, environmental and viral sequence catalogs, and 3D structure databases. For example, across 7 low-homolog protein families from the CASP17 blind test set, Carbon increased the number of homologs retrieved by 40-fold on average, greatly increasing the information available to structure prediction models without need for retraining. While broader benchmarking is still underway, addressing this upstream search bottleneck potentially offers a promising path toward modeling hard-to-characterize regions of the proteome. Four weeks ago, we opened applications to give 10,000 scientists access to Argon in Google Antigravity free of charge for six months to accelerate the pace of their research, and we’ve onboarded thousands of scientists already. Today, we’re expanding access to Carbon for current and future participants, and going forward, the program will continue providing access to our latest frontier models as they become available. Applications remain open https://forms.gle/WvmBbPvRbpKG1BPn9 and onboarding continues on a weekly rolling basis, subject to eligibility, capacity, and selection. Progress in model safety and security With each new model release, we continue to strengthen our safety and security mitigations, agentic misuse prevention, model alignment, and harm reduction proportionately with model capability. Because Gemini 4 Carbon introduces stronger cyber capabilities we build on Argon’s strong safety and security stack https://blog.google/innovation-and-ai/technology/safety-security/gemini-4-model-safety-security/ to fortify robustness to misuse and prompt injection. - Mitigating frontier safety misuse risks: We’ve strengthened our misuse safeguards to help ensure stronger defensive reasoning does not translate into offensive risk. In simulated cyberattack testing environments seeded with ExploitBench and CyScenarioBench, Carbon blocked 99% of attack trajectories from our adaptive red-teaming agent that can iteratively revisit its attack plans after each block. The Carbon safeguards lowered the per-attempt breach rate to just 0.8% down from 3.1% on Argon . Our safeguards also lowered the automated cyberattack query success rate to 2.17% in Gray Swan’s testing, compared to 9.86% on Argon. And external testing by Trajectory Labs found zero new universal jailbreaks across 132 hours and over 13,000 requests. - Promoting safe and aligned model interactions: When we announced Carbon, we showed significant improvements in alignment as measured by our monitor flag rates across the model’s lifecycle, as well as reductions in data fabrication. New results show that on our 375-task agentic honesty benchmark, it passed 92% of tasks compared to 70% for Argon — declining to fill in missing experimental data 98% of the time and flagging methodological flaws 68% of the time. - Protecting users from indirect prompt injection attacks: Two weeks ago, we shared that Carbon achieved a 0% prompt injection attack success rate on the Gray Swan IPI benchmark — marking the first time that milestone has been reached. At the same time, we know that prompt injection robustness remains an area for continued improvement. Our advanced automated red teaming continues to push the limits here and has shown that models could be further improved against sophisticated attacks in some distributions. It provides the data for us to continuously advance our models’ security to the next frontier. For more details, read the full Gemini 4 Carbon Safety and Security report https://storage.googleapis.com/deepmind-media/gemini/gemini 4 carbon safety report.pdf . Getting started with Gemini 4 Carbon Starting today, Carbon joins Argon in our family of frontier models across our products: - For developers: Build with the Gemini API paid tier in AI Studio and Android Studio, and if you’re a Google AI Ultra subscriber, you can try it in Google Antigravity and AI Studio. - For enterprises: Try it in Gemini for business https://cloud.google.com/gemini-enterprise via the API or model drop down, Google Antigravity, or CodeMender. - For everyday users: Try Carbon starting today in the Gemini app and AI Mode in Search if you’re a Google AI Ultra subscriber. - For scientists & researchers: Apply https://forms.gle/WvmBbPvRbpKG1BPn9 for a chance to get access to both Argon and Carbon via Google Antigravity’s highest usage tier free of charge for 6 months onboarded on a rolling basis , subject to eligibility, capacity, and selection. - For cybersecurity defenders: Apply to join the Fairwind Program https://deepmind.google/fairwind-program/ to get access to Carbon for cyber on a rolling basis. See the model card https://storage.googleapis.com/deepmind-media/Model-Cards/Gemini-4-Carbon-Model-Card.pdf to learn more about Gemini 4 Carbon and to start building with it, explore our updated Gemini 4 developer guide https://aistudio.google.com/learn/gemini-4-carbon-developer-guide and documentation https://aistudio.google.com/docs/whats-new-gemini-4-carbon for best practices on migrating workflows to the model.