
Sonnet 5.5 Review: Five Builds Against Opus 5.5, With What Every Run Cost
Sonnet 5.5 against Opus 5.5, Fable 5.1, GPT-6 Astra and Sonnet 5 on the same builds, ranked blind, with the tokens, time and cost of every run.
Sonnet 5.5 came close to Opus 5.5 in my builds, which Sonnet 5 never did against Opus 5, but Opus 5.5 still won overall. Ranked blind against Opus 5.5, Fable 5.1, GPT-6 Astra and Sonnet 5, it placed 3rd, 2nd and 3rd of five across three builds, beat Sonnet 5 every time and beat Opus 5.5 once, on a 3D horror game. My verdict in the video was to make it the everyday model for emails, copy, reports and lighter coding, keep it on medium effort, and hand heavy 3D work to Opus 5.5 (my verdict at 43:40).

Sonnet 5.5, Anthropic's mid-tier Claude model, costs the same per token as Sonnet 5: $2 per million input tokens and $10 per million output. Anthropic says it costs up to 30% less per task because it needs fewer tokens (Anthropic's announcement). Cache reads were halved, to $0.10 per million tokens from Sonnet 5's $0.20 (Claude pricing page).
On high effort it cost $85.40 across the three ranked builds against $84.24 for Opus 5.5, because rebuilding one website with its 3D took it 206 minutes and $57.64.
| Test | Sonnet 5.5 blind rank | Winner | Sonnet 5.5 cost and time | Opus 5.5 cost and time |
|---|---|---|---|---|
| Make a launch video for Sonnet 5.5 | 3rd of 5 | Opus 5.5 | $12.41, 73 min | $29.68, 116 min |
| Build a 3D Backrooms horror game | 2nd of 5 | Fable 5.1 | $15.35, 114 min | $20.89, 91 min |
| Rebuild the butter.video website, 3D included | 3rd of 5 | Opus 5.5 | $57.64, 206 min | $33.67, 63 min |
| All three | 2nd to 3rd | Opus 5.5 won two | $85.40, 393 min | $84.24, 270 min |
Every build ran on high effort, in Claude Code for the Claude models and Codex for GPT-6 Astra, and the costs are the real token counts priced at each lab's API rates. The full per-test tables, two extra builds cut from the video, and every prompt are further down.
Is Sonnet 5.5 better than Opus 5.5?
No, Opus 5.5 was better overall in my builds, but the gap was small. Opus 5.5 won two of the three blind rankings, the launch video and the website rebuild, while Sonnet 5.5 finished 3rd in both. On the Backrooms horror game the order flipped: Sonnet 5.5 came 2nd and Opus 5.5 came 3rd, behind Fable 5.1.
Anthropic's own launch page puts the two close together, listing Sonnet 5.5 against Opus 5.5 at 1844 to 1846 on GDPval-AA, a test of real-world work across many jobs, 55.5% to 57.8% on CursorBench 4.0, a coding test, and 61.6% to 64.4% on Chartography, a chart-reading test (Anthropic).
The one test where Anthropic has Sonnet ahead is Terminal-Bench 4.0, a coding test run in a command-line window, at 70.6% against 66.4% for Opus 5.5. In the video I pointed out that Sonnet's 70.6% comes from its max effort setting, so the two scores were not run at the same effort level.
In the video I said: "This seems like the first time that a Sonnet model is performing just as good on a lot of these tasks as Opus." For how Opus 5.5 did against Fable 5.1 and GPT-6 Astra, see my Opus 5.5, Fable 5.1 and GPT-6 Astra on the same app.
Sonnet 5.5 release date and price
The input and output prices did not change. Anthropic announced Claude Sonnet 5.5 on September 28, 2026, at $2 per million input tokens and $10 per million output tokens, the same as Sonnet 5 (Anthropic's announcement; Claude pricing page, checked October 29, 2026). Cache reads, the cheaper rate for re-sent context, dropped to $0.10 per million tokens from Sonnet 5's $0.20 (Claude pricing page).
The saving Anthropic advertises comes from token use. Its page says Sonnet 5.5 "typically needs far fewer tokens to do the same work," costs up to 30% less per task than Sonnet 5, and writes its answers 30% or more faster.

Opus 5.5 lists at $4 per million input tokens and $20 per million output, so Sonnet 5.5 is half its price per token (Claude pricing page). That gap did not carry over to my high-effort builds, where Sonnet 5.5 worked longer and ended up at $85.40 against $84.24 for Opus 5.5 across the three ranked tests.
You can pick Sonnet 5.5 in the Claude apps and Claude Code, call it through Anthropic's API as claude-sonnet-5-5, or use it on Amazon Web Services, Google Cloud and Microsoft Azure, per Anthropic's announcement. For lighter, high-volume jobs there is also Claude Haiku 5.5, the cheaper tier below it.
What I tested
Every model got the same prompts with nothing added, running inside the coding agent its own lab ships, which means Claude Code for the four Claude models and Codex for Astra, all on high reasoning effort and all in goal mode, the /goal command, which keeps the agent working until the prompt's own finish line is met. The three tests in the video are a launch video for Sonnet 5.5 made with my public launch-video skill, a realistic Backrooms horror game built with Blender, and a clone of the butter.video website with its 3D modeled in Blender, and there were no follow-up prompts and no re-running a build to get a luckier result. The two tests at the bottom, a code-only demo and a Diablo-style RPG, are from an earlier round that I cut from the video, and I've left them here because the builds and the numbers are real, although Sonnet 5 joined after the RPG was already cut. The website clone prompt is longer than Claude Code's 4,000-character goal limit, so the Claude models got that same text as a file, and Sonnet 5.5 finished its clone without compiling the site, so I ran the build command from its own README before putting it online.
The skills used in these builds (free on GitHub)
★ 20
Launch Video Clone
The skill every model followed to make its Sonnet 5.5 launch video
★ 247
Clone App Pat Pro
The skill every model followed to clone butter.video
Test 1: Make the launch video for Sonnet 5.5
A 30 to 60 second launch video for Sonnet 5.5 built from Anthropic's launch page, following my free Launch Video Clone skill.
Make the launch video for Claude Sonnet 5.5, and make it as beautiful as possible. Context you should know: this is going into a video watched by a large audience. Your launch video is played on screen next to three other frontier models given this identical prompt. The comparison is blind. Never put your model name, your company's name, or any mention of which AI made it anywhere in what you build: not in on-screen text, credits, the page title, file names, code comments, or metadata. Sonnet 5.5 and Anthropic appear in the video itself because they are its subject; that is the only exception. **Follow the skill.** Clone https://github.com/per-simmons/launch-video-clone and read its SKILL.md first. Use its **Original mode**: there is no reference video to copy. Pick the category that fits, take timing numbers from donors, write the script, storyboard, build in HyperFrames, render, review and fix, following every step and the motion rules in references/motion-feel.md. **The source.** Everything the video says comes from Anthropic's launch page: https://www.anthropic.com/claude-sonnet-5-5. Real claims, real numbers, real product names. Never invent a feature or a stat. Requirements: 1. **No generic AI-video look.** No glassmorphism or frosted-glass panels, no floating cards sliding in from below, no gradient blobs, no default fonts, and none of the stock HyperFrames or Remotion look. If a shot could come from any AI launch video, redo it. 2. **Real craft.** Considered typography, deliberate easing that differs per element, hold times long enough to read, camera moves with intent, and a clear rhythm cut to the music. 3. **Use every tool that makes it better:** HyperFrames, code-drawn motion graphics and shaders, generated imagery (an image generator is provided), 3D if it helps, and a soundtrack plus sound design made with ElevenLabs. 4. **Length 30 to 60 seconds, 1920x1080, 30 or 60 fps**, with sound. 5. **Deliver** `final.mp4` in this folder, the HyperFrames project that renders it, and the storyboard stills. DONE when: final.mp4 renders from the project, plays start to finish with sound, every claim in it matches the launch page, and a review pass finds no shot that looks like a generic AI launch video.
| Sonnet 5.5 | Sonnet 5 | Opus 5.5 | Fable 5.1 | GPT-6 Astra | |
|---|---|---|---|---|---|
| Input tokens | 43.0M | 18.6M | 69.7M | 43.6M | 8.5M |
| Output tokens | 211k | 120k | 329k | 237k | 40k |
| Cost | $12.41 | $5.90 | $29.68 | $50.13 | $12.33 |
| Build time | 73 min | 27 min | 116 min | 117 min | 26 min |
Test 2: Build a realistic Backrooms horror game
A first-person horror game set in an endless Level 0, with the rooms modeled and lit in Blender and a creature that hunts by sound.
Build a first-person Backrooms horror game that runs in the browser, and make it as realistic as possible. Context you should know: this is going into a video watched by a large audience. I will play your game on camera next to three other frontier models given this identical prompt. The comparison is blind. Never put your model name, your company's name, or any mention of which AI made it anywhere in what you build: not in on-screen text, credits, the page title, file names, code comments, or metadata. Requirements: 1. **Level 0, as close to photoreal as possible.** Mono-yellow wallpaper with a faded pattern, damp stained carpet, drop ceilings with buzzing fluorescent panels, some flickering or dead. Build the environment in Blender: model the room pieces, give them physically based materials, and bake the lighting (soft fluorescent bounce light, contact shadows, grime) with Cycles into lightmaps, then export glTF/GLB for the browser. Add subtle fog, camera exposure and grain that sell it as footage. It should look like a photo of a real place, not a video game. 2. **Endless, procedurally generated layout.** Rooms, corridors, pillars and dead ends generate around the player as they walk, never the same twice, with no visible seams or pop-in. 3. **First-person movement that feels human.** WASD and mouse look with pointer lock, walking and a limited sprint, subtle head bob, footsteps that change with speed. 4. **An entity that hunts by sound.** Something in the dark that you rarely see clearly. It moves toward noise: sprinting and running into things draw it in, walking slowly keeps you hidden. Getting caught ends the run. 5. **A way out.** An exit exists somewhere, with faint clues that lead toward it (a sound, a change in the light, a marking on the wall). Finding it ends the run with an escape screen. A typical run lasts 5 to 15 minutes. 6. **Sound is half the horror.** Fluorescent hum, distant noises, footsteps, the entity's approach, all synthesized or generated by you, positioned in 3D so you can tell direction. 7. **Performance.** Holds a smooth frame rate at 1920x1080 in desktop Chrome using WebGL2. Libraries via CDN or npm are fine. 8. **Original everything.** No assets or names taken from existing Backrooms games or videos. **Prove it.** Play it yourself through automation: walk the maze, get caught once, and reach the exit once. Then look at your own screenshots next to real photos of the Backrooms' Level 0 and push the realism until they're hard to tell apart. DONE when: the game loads in Chrome with no console errors, you have been caught and have escaped through automation, it runs smoothly at 1080p, and your screenshots look like a real place.
| Sonnet 5.5 | Sonnet 5 | Opus 5.5 | Fable 5.1 | GPT-6 Astra | |
|---|---|---|---|---|---|
| Input tokens | 44.9M | 58.3M | 53.8M | 43.4M | 3.9M |
| Output tokens | 306k | 236k | 307k | 310k | 46k |
| Cost | $15.35 | $17.22 | $20.89 | $36.09 | $7.28 |
| Build time | 114 min | 51 min | 91 min | 151 min | 28 min |
Test 3: Clone butter.video, 3D and all
A rebuild of butter.video, the same site for every model, following my free Clone App Pat Pro skill, with its 3D keychain modeled in Blender and nothing taken from the original.
Rebuild https://www.butter.video/ pixel for pixel, including its 3D, making every asset yourself. Context you should know: this is going into a video watched by a large audience. Your clone is put on screen next to the real site and next to three other frontier models given this identical prompt, at the same viewport. The comparison is blind. Never put your model name, your company's name, or any mention of which AI made it anywhere in what you build: not in on-screen text, credits, the page title, file names, code comments, or metadata. **First, read the methodology.** Clone `https://github.com/per-simmons/clone-app-pat-pro-public` and read `SKILL.md` and `references/00-contract.md` before anything else, then each stage reference as you reach it. Follow its workspace layout, artifacts, verification gate and convergence loop. `scripts/assert-styles.mjs` is the gate. Two overrides, and they win where they conflict with the repo: - **Do not stop to check in.** You are running unattended. Run the whole pipeline start to finish without asking for approval or asking questions. - **Use your own browser automation**, headless Playwright or Puppeteer, anywhere the repo says to use the Claude Chrome extension. Computed styles read off the live page through the CSSOM are ground truth. Screenshots and screen recordings are visual reference only, never the gate. You have two creative tools: **Blender**, driven headless with Python scripts, and an **image generator** (OpenAI gpt-image) you can call from the command line. Requirements: 1. **Recon the whole page before writing code.** Every section top to bottom at desktop and mobile widths, every hover and scroll-triggered state, the navigation, the timeline section, the effect tiles, the logo wall, the footer, and all loading and transition motion. 2. **Extract, don't guess.** Pull real computed values off the live page: type scale, exact colors, spacing, radii, shadows, grid and container widths, breakpoints, easing curves and durations, font families and weights. 3. **Make the 3D yourself.** The hero keychain and its puffy, inflated charms must be real 3D: model them in Blender, export glTF/GLB, and render them live in the page with WebGL, matching the original's composition, lighting, material softness and motion. Use the image generator for textures, decals, and flat artwork, and as a design reference for shapes before you model them. Any other 3D or inflated artwork on the page gets the same treatment. 4. **No lifted assets.** Do not hotlink, download, or trace the original's images, video, 3D files, or fonts. Anything visual you did not generate in code, Blender, or the image generator is a placeholder matched to the original's role, aspect and color. Brand logos in the customer wall become neutral wordmarks set in type. Fonts come from an open CDN with metrics matched as closely as you can. List every substitution in the README. 5. **Rebuild it all.** Every section, every component, every interactive state, at desktop and mobile. The motion is part of the clone: scroll choreography, hover behavior, the hero's 3D movement, the timeline, the effect tiles. A static skin over a site whose identity is motion is a failed clone. 6. **Prove the match.** Run `assert-styles.mjs` against your extracted tokens and iterate until there are zero failures and the project builds clean. Then compare your clone to the real site at the same viewport, desktop and mobile, and fix what your eye catches that the assertions missed. 7. **Ship it runnable**, with a documented run command and a README covering what you substituted, how you made the 3D (Blender scripts included in the repo), and your final assertion results. 8. **Depth over breadth.** If you have to choose, a hero and first three sections that are indistinguishable from the original beat a whole page that is approximately right. DONE when: the clone passes the style gate with zero failures, runs from a documented command, its 3D hero is real Blender geometry rendering live in WebGL, and it holds up next to the real site at full screen.
| Sonnet 5.5 | Sonnet 5 | Opus 5.5 | Fable 5.1 | GPT-6 Astra | |
|---|---|---|---|---|---|
| Input tokens | 215.5M | 69.0M | 90.5M | 33.4M | 19.7M |
| Output tokens | 845k | 273k | 405k | 352k | 102k |
| Cost | $57.64 | $18.65 | $33.67 | $43.41 | $29.54 |
| Build time | 206 min | 42 min | 63 min | 84 min | 45 min |
Test 4: Make the most impressive demo of yourself
A self-directed audiovisual demo in one HTML file, where every pixel and every sound is generated by code, cut from the video.
Make the most impressive demo of yourself. Context you should know: this is going into a video watched by a large audience. Your demo is played on screen next to three other frontier models given this identical prompt. The comparison is blind. Never put your model name, your company's name, or any mention of which AI made it anywhere in what you build: not in on-screen text, credits, the page title, file names, code comments, or metadata. The only constraints: 1. It is a single self-contained HTML file. Every pixel and every sound is generated by your code at runtime. No images, audio files, video, fonts, 3D models, or libraries, loaded or inlined. 2. It has sound. A click-to-start screen is fine, since browsers block audio until the viewer interacts. 3. It runs full screen in a current desktop Chrome at 1920×1080 and holds a smooth frame rate there. Everything else, what it is, how long it runs, and what it shows, is your call. DONE when: the file opens in Chrome, starts on one click, plays start to finish with sound and no console errors, and you would put your name on it.
| Sonnet 5.5 | Sonnet 5 | Opus 5.5 | Fable 5.1 | GPT-6 Astra | |
|---|---|---|---|---|---|
| Input tokens | 38.0M | 9.5M | 19.0M | 8.3M | 1.7M |
| Output tokens | 257k | 100k | 219k | 144k | 31k |
| Cost | $13.39 | $3.80 | $10.74 | $14.10 | $4.15 |
| Build time | 50 min | 35 min | 47 min | 48 min | 18 min |
Test 5: Build a Diablo-style action RPG
A browser dungeon crawler with a town, four random floors, loot, skills, saving and a boss, cut from the video.
Build a complete, playable dark-fantasy action RPG in the style of Diablo (1996) and Diablo II, that runs in the browser. Context you should know: this is going into a video watched by a large audience. I will play your game on camera, start to finish, next to three other frontier models given this identical prompt. The comparison is blind. Never put your model name, your company's name, or any mention of which AI made it anywhere in what you build: not in on-screen text, credits, the page title, file names, code comments, or metadata. Requirements: 1. **The loop.** A town hub, then a dungeon of at least four floors going down, ending in a boss fight. Beating the boss ends the run with a victory screen. Dying drops you back in town with a penalty, and you can go down again. 2. **Isometric, real-time, click to move and attack**, the way the originals play. Mouse drives movement and the main attack; number keys or hotkeys fire skills and drink potions. 3. **One playable class with at least four skills** that feel different: at least one melee, one ranged or area spell, one defensive or movement skill. Skills cost mana and have cooldowns where it makes sense. Leveling up grants stat points and skill points you spend yourself. 4. **Procedural dungeons.** Every floor is generated fresh: rooms, corridors, doors, stairs down, and fog of war that clears as you explore. Deeper floors are harder. 5. **At least five enemy types with distinct behavior**, e.g. a melee rusher, a ranged attacker that keeps its distance, a swarm of weak ones, a caster, and a tough slow one, plus elite packs with a named champion. The boss has phases. 6. **Loot that means something.** Enemies drop gold, potions and items. Items have rarity tiers (normal, magic, rare, unique) shown by color, random affixes that actually change your stats, and an item-level that scales with depth. An inventory grid, equipment slots on a paper doll, tooltips that compare against what you're wearing, and a town vendor to sell and buy. 7. **Game feel.** Hit reactions, damage numbers, death animations, screen shake used sparingly, lighting that pushes back the dark around the player, and sound effects and music generated or synthesized so nothing is loaded from a third party. 8. **Save and continue.** Progress, character, and inventory persist across page reloads. 9. **Original everything.** No names, art, or audio from any existing game. Make your own world, class, enemies and boss. Code-generated art, your own sprites, or 3D (libraries via CDN are fine) are all acceptable. 10. **Prove it's winnable.** Before you finish, play it yourself through automation: run a character from town to the boss and beat it. Fix whatever breaks. Then balance it so a human who knows the genre can finish it in roughly 15 to 30 minutes. DONE when: the game loads in Chrome with no console errors, you have played it from town to a killed boss yourself, and every system above is present and working.
| Sonnet 5.5 | Sonnet 5 | Opus 5.5 | Fable 5.1 | GPT-6 Astra | |
|---|---|---|---|---|---|
| Input tokens | 61.2M | – | 18.7M | 7.3M | 3.2M |
| Output tokens | 475k | – | 290k | 177k | 64k |
| Cost | $19.54 | – | $12.69 | $15.82 | $7.24 |
| Build time | 81 min | – | 53 min | 52 min | 36 min |
What it cost
Whether Sonnet 5.5 saves money depends on the job, because it came in cheaper than Opus 5.5 on the launch video, $12.41 against $29.68, and on the Backrooms game, $15.35 against $20.89, but cost $57.64 against $33.67 on the website clone, where it re-read 215 million tokens of its own growing work. Across the three video tests that evens out to $85.40 for Sonnet 5.5 and $84.24 for Opus 5.5, while Fable 5.1 came in highest at $129.63, GPT-6 Astra at $49.15 and Sonnet 5 lowest at $41.77, which shows that how many steps a model takes to finish counts for far more than its price per token.

| Sonnet 5.5 | Sonnet 5 | Opus 5.5 | Fable 5.1 | GPT-6 Astra | |
|---|---|---|---|---|---|
| Input tokens | 402.6M | 155.4M | 251.7M | 135.9M | 37.1M |
| Output tokens | 2.1M | 729k | 1.6M | 1.2M | 282k |
| Cost | $118.32 | $45.57 | $107.67 | $159.55 | $60.54 |
| Build time | 525 min | 155 min | 370 min | 452 min | 152 min |
These are API-equivalent costs, meaning the real token counts from each build priced at each model’s published rates, even though the builds themselves ran on subscriptions.
Is Sonnet 5.5 better than Sonnet 5?
Yes. Sonnet 5.5 beat Sonnet 5, the model it replaces, in all three blind rankings, where Sonnet 5 came last every time. Anthropic's page shows the same jump on its coding test, Terminal-Bench 4.0, from 10.3% for Sonnet 5 to 70.6% for Sonnet 5.5 (Anthropic).
When I tested Sonnet 5 on release, it "just wasn't even close to Opus 5," and in this video I said, after reading Sonnet 5.5's price and efficiency: "If you're running Sonnet 5 anywhere, definitely recommend you immediately upgrading just based on that."
Sonnet 5 was still the cheapest model in the test, at $41.77 across the three video builds against $85.40 for Sonnet 5.5, because it stopped sooner. On the launch video it finished in 27 minutes for $5.90, where Sonnet 5.5 kept working for 73 minutes and spent $12.41.
How good is Sonnet 5.5 at Blender and 3D?
It was good at 3D games and weaker at detailed 3D models. Both 3D tests had every model build its 3D in Blender, the free 3D modeling app, driven by scripts with no one touching the interface.
On the Backrooms horror game, a first-person game with rooms modeled and lit in Blender, Sonnet 5.5 came 2nd of five, ahead of Opus 5.5, GPT-6 Astra and Sonnet 5. Fable 5.1 won it.
On the butter.video rebuild, where each model had to recreate an award-winning website including its 3D keychain hero, Sonnet 5.5 came 3rd. In the video I said it "actually did the best in the rest of the website," and that "the only thing it didn't do well was that 3D work."
That website rebuild was also where Sonnet 5.5 cost the most. It ran for 206 minutes, read 215.5 million input tokens and cost $57.64, against 63 minutes and $33.67 for Opus 5.5. My take in the video was that for this kind of 3D web work "it just makes more sense to hand off to Opus or Fable 5.1," and that Astra did a great job there too.
Is there a Fable 5.5?
No. As of October 29, 2026, Anthropic's newsroom has no Fable 5.5 announcement (Anthropic newsroom, checked October 29, 2026). The newest Fable I've tested is Fable 5.1.
Fable 5.1 is in every test on this page. It won the Backrooms horror game, came 2nd on the launch video and came 4th on the butter.video rebuild, and it was the most expensive model across the three video builds at $129.63.
When I published this review on September 29, I said: "We will surely see Fable 5.5 come out, I would guess, in the next couple weeks." For my earlier Fable results, see Fable 5.1 against Fable 5 and Opus 5.
Questions people ask
Is Sonnet 5.5 better than GPT-6 Astra?
In two of my three blind rankings, yes. Sonnet 5.5 beat GPT-6 Astra on the launch video (3rd against 4th) and the Backrooms game (2nd against 4th), and Astra beat it on the butter.video rebuild (2nd against 3rd). Astra was cheaper, at $49.15 across the three builds against $85.40.
Is Sonnet 5.5 faster than Sonnet 5?
Anthropic says it writes its answers 30% or more faster than Sonnet 5. In my builds on high effort it still took longer to finish every time, 73 minutes against 27 on the launch video and 206 against 42 on the website rebuild, because it kept working through more steps.
Were the demo and action RPG tests ranked?
No. Those two builds were cut from the video, so only their prompts, builds and costs are published, in the test sections above, with no ranking.
How I'd set up Sonnet 5.5 for a team
Make Sonnet 5.5 the everyday model and keep Opus 5.5 for the hard jobs. In the video I said: "I feel like Sonnet 5.5 is a good recommendation as a daily driver for your team."
The jobs I named were follow-up emails, drafting copy, pulling together a report and lighter coding work. If you're trying to save on cost, you can have Sonnet 5.5 take the first pass and have Opus 5.5 or Fable check its work, especially on larger builds.
Leave it on medium effort. Anthropic recommends medium, and it's the default effort in Claude Code and the Claude apps (Anthropic). I ran every build here on high, which is how the website rebuild ran for three and a half hours and cost more than Opus 5.5 and Fable 5.1. As I put it in the video, "it just doesn't really make a whole lot of sense to run this on max when you could just instead go to Opus 5.5 or Fable."
One job I said I'd use Sonnet 5.5 for right away is video editing: "I've had Sonnet 5.5 editing most of this video where it's cutting out bad takes, removing pauses." The skill behind that is in the Premiere editing skill Sonnet 5.5 now runs. For everything else, I said I'm just using Opus 5.5.
Both skills the models used are free on GitHub, so you can run them yourself: the launch video skill for the launch video test, and Clone App Pat Pro for the website rebuild. Every prompt is in the test sections above.
Updated October 29, 2026: Added the verdict and a results table at the top, Anthropic's release date and price, and answers on Opus 5.5, Sonnet 5, Blender and Fable 5.5, plus a Sources list.






























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