# SpaceXAI 发布 Grok 4.5，专注编程与智能体任务 - 来源：Hacker News 热门（buzzing.cc 中文翻译） - 作者：BoumTAC - 发布时间：2026-07-10 05:46 - AIHOT 分数：80 - AIHOT 链接：https://aihot.virxact.com/items/cmre2mjao00nlihwk6dhq4pl6 - 原文链接：https://x.ai/news/grok-4-5 ## AI 摘要 7月8日，SpaceXAI 推出 Grok 4.5，主打编程、智能体任务和知识工作。模型使用数万块 NVIDIA GB300 GPU 训练，通过强化学习聚焦多步软件工程。基准测试中，DeepSWE 1.0 得分 62.0%，SWE Marathon 解决率 29.0%，Terminal Bench 2.1 为 83.3%，SWE Bench Pro 解决率 64.7%。推理速度达 80 TPS，输出 token 效率约为 Opus 4.8 的 4.2 倍。定价为每百万输入 token $2、输出 token $6。即日起可在 Grok Build、Cursor 及 SpaceXAI API 中使用，欧盟地区预计 7 月中旬开放。 ## 正文 Grok 4.5 is SpaceXAI's smartest model built for coding, agentic tasks, and knowledge work. Today, we're launching Grok 4.5, SpaceXAI's smartest model built to excel at coding, agentic tasks, and knowledge work. It's our strongest model ever and was trained alongside Cursor. Real-world engineering excellence Grok 4.5 was trained on datasets spanning knowledge in coding, science, engineering, and math. With both intelligent and efficient reasoning, Grok 4.5 excels at real engineering tasks and exceeds comparable leading models at these tasks. DeepSWE 1.0 DeepSWE 1.1 SWE Marathon Terminal Bench 2.1 SWE Bench Pro Competitor figures are drawn from the respective developers’ published system cards or benchmark leaderboards Benchmark bar charts of model scores. DeepSWE 1.0 (eval created by Datacurve, run with each model provider’s harnesses by AA): Fable (max) 66.1%, GPT 5.5 (xhigh) 64.31%, Grok 4.5 62.0%, Opus 4.8 (max) 55.75%, Opus 4.7 (max) 40.12%. DeepSWE 1.1 (mini-swe-agent harness run by Datacurve): Fable (max) 70%, GPT 5.5 (xhigh) 67%, Opus 4.8 (max) 59%, Grok 4.5 53%, GLM 5.2 44%. SWE Marathon resolution rate (pass@1): Grok 4.5 29.0%, Opus 4.8 (max) 26.0%, Fable (max) 24.0%, Opus 4.7 (max) 16.0%. Terminal Bench 2.1: Fable (max) 84.3%, GPT 5.5 (xhigh) 83.4%, Grok 4.5 83.3%, Opus 4.8 (max) 78.9%, Opus 4.7 (max) 78.9%. SWE Bench Pro resolve rate: Fable (max) 80.4%, Opus 4.8 (max) 69.2%, Grok 4.5 64.7%, Opus 4.7 (max) 64.3%, GLM 5.2 62.1%, GPT 5.5 (xhigh) 58.6%. Competitor figures are drawn from the respective developers’ published system cards or benchmark leaderboards. Training Grok 4.5 Grok 4.5 was trained across tens of thousands of NVIDIA GB300 GPUs, with training and stability techniques designed for large-scale runs. Beyond raw token volume, we invested heavily in data filtering and curation: deduplication, quality scoring, and domain-focused selection so that the data mixture stayed high-coverage and high-signal. We scaled reinforcement learning with a strong focus on per-token intelligence. Our RL training covers hundreds of thousands of tasks, centered on multi-step software engineering and other technical work, with automated and model-based grading. Our stack is built for highly asynchronous training, so agentic rollouts can run for many hours while learning continues across tens of thousands of GPUs. The result is more intelligent and efficient reasoning on real engineering and agentic tasks. Built with one prompt Grok 4.5 is incredibly capable at coding, from challenging Rust and C/C++ tasks to end-to-end app building from prompt to production. Below are some examples built by the model with one prompt. Grok 4.5 is highly proficient at creating well-designed, end-to-end functional apps even with minimal specification. Solar system Make a beautiful simulation of the universe and solar system. should be sped up with adjustable time, realistic motion, orbits, stars. use threejs. Make the HUD well styled and conform to modern design principles. Faster than flash models Grok 4.5 is served at fast-model speeds of 80 TPS. Combined with twice greater token efficiency than the latest leading models at the same tasks, the model delivers intelligent results to you more quickly and at far lower costs. Token efficiency avg. output tokens per SWE Bench Pro task Grok 4.5 0 Opus 4.8 (max)0 4.2×fewer tokens 0 70 k tokens Token efficiency, average output tokens per SWE Bench Pro task — Grok 4.5 resolves tasks with 15,954 output tokens on average, about 4.2× fewer than Opus 4.8 (max) at 67,020 Excels at Office work Grok 4.5 is now the default model in Grok Build. In addition to its coding proficiency, Grok Build is capable of building complex Excel models that involve research from the web, multi-sheet formula use, and even leaves stickies or notes behind for future reference. In PowerPoint and Word, Grok 4.5 is similarly meticulous. The model is capable of using native PowerPoint shapes to build complex diagrams, designing intuitive slide content, and writing clear prose in Word. Outline a 5-slide quarterly business review Learn more about our plugins for Word, PowerPoint, and Excel. Pricing Grok 4.5 is delivered at an incredibly competitive cost compared to other leading models. Grok 4.5 is priced at $2 per million input tokens and $6 per million output tokens. The model also achieves roughly 2x the token efficiency of comparable leading models, solving tasks in under half the number of steps. Overall, Grok 4.5 delivers the highest intelligence per unit of time and cost. Getting started Grok 4.5 is available today in Grok Build, in Cursor on all plans, and from the SpaceXAI console. Simply grab an API key and get started in a few lines of code: curl -s https://api.x.ai/v1/responses \ -H "Authorization: Bearer $XAIAPIKEY" \ -H "Content-Type: application/json" \ -d '{ "model": "grok-4.5", "input": "Find and fix the bug, then explain it: function median(a){a.sort();return a[a.length/2]}" }' Note: Grok 4.5 is not yet available in the EU in any SpaceXAI products or the API console. EU availability is expected in mid-July. Create an API Key Start building with Grok 4.5 today via the SpaceXAI API. Start Building API Docs Read the docs and integrate Grok 4.5 into your stack. Read the Docs Try it in Grok Build for free We’re offering free Grok 4.5 usage for a limited time inGrok Buildand Cursor. Get started today atx.ai/cli. $ curl -fsSL https://x.ai/cli/install.sh | bash