#编码

OpenAI has reduced GPT-5.6 Sol's thinking budgets in an effort to make the model more efficient They essentially bumped everyone's reasoning down by 1... so if you were running Sol Extra High, you now have to set it to Max to get the same effort So we basically don't have Max reasoning anymore, how do you feel about these changes? 🤔

BREAKING - OFFICIAL RESULTS: GPT-5.6 Sol by @OpenAI is 1st overall on Design Arena with an Elo of 1353. This puts GPT-5.6 Sol above Claude Fable 5 by @AnthropicAI and in the same performance band as GLM 5.2 by @Zai_org on frontend design. This is an 18-position and 60-point Elo leap from GPT-5.5. GPT-5.6 Sol also establishes a new Pareto frontier for preference vs. speed, faster than any model at this performance. Congratulations to the @OpenAI team on the launch!

@thsottiaux 简而言之： - 用 Claude 和 Codex 认证设置 CLIProxyAPI - 连接到 Claude Code - 创建 "claudex" 别名来设置一些环境变量 大概花了 2 个提示（不过说实话我已经把代理设置好了）

Hello beautiful people! We have reset usage limits across Codex and ChatGPT Work. And another one will come later in the day. Rejoice. Now that I have your attention, a quick update on ChatGPT Work, Codex and all the updates we shared yesterday. We’ve spent the last 24 hours reading feedback, looking at usage patterns, and talking with many of you. The short version is that there is a *lot* of excitement for GPT 5.6 Sol, ChatGPT Work on mobile & web, but also that we didn't get everything quite right. - We made it too easy to use the highest-compute settings without making the impact on usage limits sufficiently clear. - We reorganized the desktop app in one bold move, making familiar things like chats and projects harder to find. - Our launch framing was focused on ChatGPT Work and to some of our Codex fans it made it feel like Codex was going away over time. Absolutely not our intention, we love Codex and it is here to stay. - And we introduced regressions for some existing multi-agent workflows, alongside a collection of rough edges in plugins and other parts of the experience. We’re landing a first set of improvements today. We’re resetting usage twice so people can keep experimenting, changing defaults and the model picker so they don’t push people toward unnecessarily expensive settings, fixing several plugin submission issues, improving how we represent Codex in the product, and cleaning up some of the most immediate desktop problems. A larger set of improvements will land next week. We’re bringing chats and projects back into the sidebar in a more familiar and customizable way, making usage and reset timing much more visible, clarifying when to use ChatGPT Work and when to use Codex, and addressing the many other smaller pieces of great feedback we've had. The ambition behind this launch hasn’t changed. We think bringing ChatGPT and Codex together into a workspace where people and agents can collaborate is a very important step forward. But an ambitious direction doesn’t excuse avoidable confusion or regressions in the first version. Please keep the feedback coming. We’re moving quickly, and you should see the experience already get better with a few updates today; and substantially better again next week.

Grok 4.5 from @SpaceXAI places #2 on the APEX-SWE leaderboard at 51.2% Pass@1 (±6.0), behind Fable 5 (65.5% ±6.2) on our benchmark for real-world software engineering work. It leads Integration (65.0% Pass@1) and places #2 in Observability (37.3% Pass@1), covering multi-step build tasks and diagnosis/debugging respectively. The Integration lead maps directly to the agentic workflows Grok 4.5 was built for: multi-step coding tasks run in collaboration with Cursor. Grok models have improved 30.2 pp in a year on this benchmark: Grok 4 (21.0% Pass@1) to Grok 4.5 (51.2% Pass@1). Congratulations to the xAI and Cursor teams.

Try Grok 4.5 for free in Grok Build! curl -fsSL https://x.ai/cli/install.sh | bash

Grok 4.5 performed GPT Sol level for free! We gave 4 models the same prompt: build three self-contained HTML5 canvas scenes with real physics demos Prompts: -robot deathmatch, Tombstone vs Minotaur -a hydraulic press flattening stuff on a conveyor -a semi truck jumping a canyon Outputs: GPT-5.6 Sol: 12.9K tokens, $0.51 (~7 min) Grok 4.5: 10.8K tokens, $0 (~5 min) Muse Spark 1.1: 26.8K tokens, $0.12 (~7.5 min) GLM 5.2: 10.9K tokens, $0.02 (~12 min) Grok 4.5 handled all three scenes genuinely well and got surprisingly close to GPT-5.6 this round. On top of that, it ran on the free tier. GPT-5.6 Sol, the frontier model, put out solid but not standout work. GLM 5.2 rendered all three scenes for pennies, but it came out the roughest of the four. Meta's new Muse Spark burned the most tokens yet still stayed cheap, delivering an average result.

fwiw, I think that turning Codex into ChatGPT Desktop is a generational fumble

(1) 今天我们发布 Muse Spark 1.1——这是一款性能强劲的智能体与编程模型，价格非常低廉。它已通过我们全新的 Meta Model API 上线，并集成在 Meta AI 中。

gpt 5.6 sol pro vs claude fable 5 vs grok 4.5 vs glm 5.2 today @OpenAI released the gpt-5.6 family – sol (flagship), terra, luna. key facts: • sol is the new flagship, priced $5/m input and $30/m output • openai claims "more work per token" and sota coding: artificial analysis coding agent index 80, browsecomp 92.2%, osworld 2.0 62.6% • sol pro = the highest-quality chat tier for complex tasks; the family also ships an 'ultra' setting that runs 4 agents in parallel • we ran sol pro our test – 3 prompts, single-file html, three.js: 1. floating-island district of london – tower bridge, big ben, london eye, the shard, tower of london 2. floating-island district of paris – pont alexandre iii, eiffel, arc de triomphe, louvre, notre-dame 3. floating-island district of nyc – brooklyn bridge, empire state, chrysler, one wtc, flatiron, statue of liberty requirements: two square floating islands, sheer cliffs, waterfalls pouring only from drainage pipes (real stream geo, foam, spray, mist), fps fly-cam, every square meter packed with landmarks + city fabric, cinematic golden-hour sky, bloom, no ui, no text results (summed across all 3 cities): cost #1 grok 4.5 – $0.41 #2 glm 5.2 – $1.45 #3 gpt 5.6 sol pro – $4.12 #4 fable 5 – $11.37 tokens #1 grok 4.5 – 60,291 #2 fable 5 – 174,083 #3 gpt 5.6 sol pro – 241,739 #4 glm 5.2 – 243,188 lines of code #1 fable 5 – 2,830 #2 gpt 5.6 sol pro – 3,003 #3 glm 5.2 – 3,474 #4 grok 4.5 – 3,830 sol pro's code quality – reviewed by opus 4.8: upsides: - modern r164 stack, zero deprecated apis, correct color management via outputpass - instancedmesh batches thousands of skyscraper windows into single draw calls - every cliff and facade is a procedural canvas texture, no external assets - clean animate loop, no per-frame allocations downsides: - the glass reflects nothing – materials set envmapintensity 1.3–1.4 and transmission, but no scene.environment or envmap is ever created, so the spec's "reflections on glass" don't exist - the city has no instancing or merging: box() mints a fresh geometry per call and every window is its own plane mesh, so london and paris ship thousands of draw calls with instancedmesh count 0 - one 2048² shadow map is stretched across the whole 440-unit district, so shadows come out coarse and crawling. and ~58% of buildings get a random cone "pyramid" roof regardless of style while ~32% skip casting shadows outright pattern: it writes a clean, deprecation-free scene that photographs well – then skips the reflections, draw-call discipline and material depth the prompt asked for. built for the thumbnail, not the spec observations: • all four are mid – frontier "graphics" aren't best-of-the-best. prettiest is london by glm 5.2, still not ideal • bridges break everyone: fable joins two towers with chains, no roadway. sol pro opens its bascule down instead of up • sol pro floats cars with no road in nyc • sol pro trends toward simple, boxy shapes – fable too models that were "5 minutes to agi" now ship sloppy and perform at roughly glm 5.2 level. glm is closing the gap from below, and political decisions are closing it from our side follow @thehypedotnews for 24/7 ai news, analysis and breakdowns