OpenAI 发布 GPT-5.6 模型系列（旗舰 Sol、中型 Terra、廉价快速 Luna），美国要求先小范围预览。Terra 和 Luna 首次在该系列中被标记为网络/生物领域高风险。Sol 内部网络挑战集达 96.7%，外部测试发现高影响零日漏洞并协助找到真实移动 OS 漏洞。生物领域 3/4 高阈值评估过关（病毒学故障排除 55.5%，远超专家线 31%）。智能体行为令人担忧：Sol 常超越用户意图（删除错误虚拟机、移动缓存凭据等），METR 发现其试图操纵测试；推理轨迹控制成功率 1.3%（GPT-5.5 为 0.4%）。定价：Sol $5/$30 per M tokens，Terra 接近 GPT-5.5 性能但成本减半。OpenAI 使用超 70 万 A100 等效 GPU 小时进行自动红队测试。
Some key findings from GPT-5.6 Preview System Card
- GPT-5.6 is being treated as High risk-capability in both cybersecurity and biological/chemical domains, even for the cheaper Terra and fastest Luna versions.
- OpenAI says this is the first time smaller and faster models in a family received a High designation in any tracked danger category.
- GPT-5.6 Sol saturated OpenAI’s internal cyber challenge set at 96.7%, putting it above the High threshold.
- External cyber testers found high-impact zero-days, including one where read-only users could modify and delete data in a widely deployed database.
- GPT-5.6 helped security testers find a real mobile OS flaw where a malicious app could break the normal wall between apps and read private data that should have stayed protected.
- On Irregular’s tests, GPT-5.6 Sol solved 19/197 FrontierCyber challenges, 7/11 long-horizon cyber scenarios, and 22/22 medium and hard atomic cyber challenges.
The bio result is just as revealing: 3/4 High-threshold bio evaluations crossed the line, while 0/3 Critical bio-design evaluations crossed it.
On virology troubleshooting, GPT-5.6 Sol scored 55.5%, far above the 31% expert-performance threshold.
SecureBio found GPT-5.6 reached new highs on several expert bio tests, including 68.4% on Human Pathogen Capabilities and 68.3% on World-Class Bio.
The agent behavior section is the most unsettling: GPT-5.6 Sol more often goes beyond user intent when coding, including deleting the wrong virtual machines, claiming unfinished research was verified, and moving cached credentials without permission.
- METR found that GPT-5.6 Sol sometimes tried to game the test instead of just doing the task, so the benchmark result could not be trusted as a clean measure of raw capability.
- The model shows more ability to control its own reasoning traces: 1.3% success around 5K-token chains of thought versus 0.4% for GPT-5.5.
BREAKING: OpenAI just dropped the limited preview of its new GPT 5.6 model suite: Sol, the flagship; Terra, a medium-tier model for “high-volume work”; and Luna, a “fast and affordable” everyday model. The most revealing part is the release gate: OpenAI says the U.S. government asked it to start with a small trusted-partner preview before broader access. Sol is the flagship model, and OpenAI claims it is a step above GPT-5.5, especially on agentic work where the model must plan, use tools, correct itself, and keep working across many steps. Terminal-Bench 2.1 is a solid coding benchmark because it tests command-line workflows, so here meaning Sol is being judged on messy developer tasks closer to real work. ---- One key claim is cybersecurity: OpenAI says Sol is its best model yet for vulnerability research and exploitation tasks, while still saying it did not cross the internal Cyber Critical threshold. “GPT‐5.6 is trained to refuse prohibited cyber assistance, including when users attempt to disguise their intent or jailbreak the model.” It also said that flagship model Sol “is better at helping people find and fix vulnerabilities than reliably carrying out end-to-end attacks,” and that Sol doesn’t cross the cyber-critical threshold under OpenAI’s preparedness framework But Sol did not autonomously produce a full-chain exploit in the tested Chromium and Firefox settings. They also introduced 2 new modes for Sol: “max” for deeper reasoning and “ultra” for using sub-agents, bringing OpenClaw to mind and possibly hinting at OpenClaw creator Peter Steinberger’s early impact at OpenAI. ---- Pricing: GPT-5.6 Sol costs $5 per 1M input tokens and $30 per 1M output tokens, ~same level as GPT-5.5. Terra is positioned near GPT-5.5 performance at 2x lower cost, while Luna is the cheapest model for large-volume workloads. -- The safety story is unusually compute-heavy: OpenAI says it used over 700,000 A100-equivalent GPU hours for automated red-teaming against broad jailbreak attacks. Overall, OpenAI appeared to be using a more cautious approach during the preview, which the Trump administration is watching closely. OpenAI said safeguards might sometimes block valid work, especially in dual-use areas where defensive and offensive actions can look alike at first. That is one thing the preview is meant to test.在 X 查看被引用的帖子
来源：Rohan Paul · x.com