Claude Opus 5.5 vs GPT-6 Sol Everything You Need to Know!
Universe of AI · 2026-09-22 · review · 72,939 views
What's in the video
Description written by Gemini, which watched and listened to the whole video.
Summary
The presenter from the YouTube channel Universe of AI discusses the simultaneous releases of Anthropic’s Claude Opus 5.5 and OpenAI’s efficiency-oriented models, GPT-6 Sol and GPT-6 Luna. The video reviews official benchmark charts, pricing reductions, and alignment metrics, followed by an overview of community demonstrations showcasing code-generated 3D and browser environments.
What is shown
- [01:23] Official Anthropic benchmark comparison chart showing Claude Opus 5.5 against Claude Fable 5.1, Claude Opus 5, GPT-6 Astra, and GPT-5.6 Sol across agentic coding, knowledge workflows, and computer use.
- [03:06] Pricing table comparing Claude Opus 5.5 to Claude Opus 5 per 1M tokens.
- [04:14] AutomationBench plot illustrating pass rate versus cost per task for Claude Opus 5.5, Opus 5, GPT-6 Astra, and GPT-5.6 Sol.
- [05:05] Text communication comparison post contrasting verbosity and bug-identification structure between Opus 5 and Opus 5.5.
- [06:25] Official OpenAI release announcement and pricing table for GPT-6 Astra, GPT-6 Sol, and GPT-6 Luna, alongside their performance curves on AutomationBench [07:18].
- [08:06] Bar chart comparing coding deception rates between GPT-6 Astra, GPT-6 Sol, GPT-6 Luna, GPT-5.6 Sol, and GPT-5.6 Luna.
- [08:47] Community demo by @intheworldofai generating a Call of Duty: Zombies clone in Three.js via Claude Opus 5.5.
- [09:36] Community demo by @noahwachnik generating a playable voxel/Minecraft-style game in-browser via Claude Opus 5.5.
- [10:11] Community SVG generation test by @can recreating an Xbox controller with Opus 5.5.
- [11:01] Procedural Mediterranean harbour town browser demo created with Opus 5.5 (shared by @Karan).
- [11:48] Side-by-side 10-second Blender animation test between Opus 5.5 and GPT-6 Astra (shared by @Stefan 3D AI).
- [12:53] Game Boy UI interactive web app generated by Opus 5.5, and side-by-side output comparison with GPT-6 Sol [13:10].
Claims & numbers
- Claude Opus 5.5 Pricing & Performance (Anthropic data cited by presenter):
- Input tokens are $4.00/1M tokens (vs. $5.00 for Opus 5); output tokens are $20.00/1M tokens (vs. $25.00 for Opus 5); cache reads are $0.20/1M (vs. $0.50); cache writes are $5.00/1M (vs. $6.25) [03:07].
- At default settings, Opus 5.5 costs 40% less to run on typical workloads and outputs 30% faster than Opus 5 [03:06].
- Scored 66.4% on agentic coding benchmark (vs. 55.8% for Fable 5.1 and 52.3% for Opus 5) [01:48].
- Scored 54.4% on another agentic coding evaluation (vs. 50.3% for Fable 5.1 and 53.3% for GPT-6 Astra) [02:04].
- OpenAI GPT-6 Sol and Luna (OpenAI data cited by presenter):
- Sol and Luna offer 50% lower API prices compared to GPT-5.6 promotional pricing [06:55].
- Token pricing: GPT-6 Astra is $10 input / $50 output per 1M tokens; GPT-6 Sol is $2 input / $10 output; GPT-6 Luna is $0.10 input / $0.50 output [06:58].
- Coding deception rates: GPT-6 Astra is 0.5%, GPT-6 Sol is 1.3% (down from GPT-5.6 Sol's 10.4%), and GPT-6 Luna is 2.8% (down from GPT-5.6 Luna's 9.5%) [08:27].
- Blender 3D Castle Test (Stefan 3D AI benchmark cited by presenter):
- Claude Opus 5.5 completed generation in 35 minutes, using 199.6k output tokens costing ~$13.3 in API usage [11:58].
- GPT-6 Astra finished in 28 minutes, using 96.6k output tokens costing ~$14.5 in API usage [12:05].
Notable quotes
- [00:12] "Opus 5.5... OpenAI has also dropped new models: GPT-6 Luna and GPT-6 Sol."
- [03:12] "Yes, this model is now 40% more cheaper than Opus 5, which is a surprising thing to see from Anthropic..."
- [08:11] "...one area that they're really working on is making sure that coding deception or how they're aligned is better..."
Assessment
This is an independent YouTube commentary and news roundup reviewing public launch announcements, benchmarks, and third-party social media demonstrations. The presenter does not run original evaluations on camera, instead relying on official corporate posts and external community tests shared on X/Twitter.
Described by gemini-3.8-flash on 2026-09-29 from the video's audio and frames.