Claude Opus 5.5 and GPT-6 Sol ship hours apart, each cheaper than before
Anthropic shipped Claude Opus 5.5 and OpenAI shipped GPT-6 Sol and Luna on Tuesday, each cheaper per token, and Artificial Analysis has first coding numbers for both. One more story inside.
Anthropic and OpenAI both shipped new models on Tuesday, less than two hours apart, and both cut prices. Claude Opus 5.5 costs 20% less per token than Opus 5, and Artificial Analysis measured it 11 points ahead of Opus 5 on Terminal-Bench 4.0, a coding test. GPT-6 Sol and Luna cost half what GPT-5.6 did at its promotional price, and score about level with it. DigitalOcean also opened a cloud for Claude Code and Codex. It bills only for the CPU they use.
Two new models, and a new place to run agents
Anthropic ships Claude Opus 5.5 at 20% below Opus 5 per token
On Anthropic's own coding benchmark, Terminal-Bench 4.0, Claude Opus 5.5 scores 66.4%, against 52.3% for Opus 5 and 55.8% for the pricier Fable 5.1. Anthropic hedges its own table: "the gap between Opus 5.5 and Claude Fable 5.1 is narrower than these scores suggest." Artificial Analysis, an independent benchmarking firm, measured 59.6% on its own run of that test, 11 points over Opus 5, and ranks it #1 on its Intelligence Index. It costs $4 and $20 per million input and output tokens, 20% less than Opus 5. Anthropic says it will cost 40% less at default settings on typical workloads. At max effort, Artificial Analysis found it level with Opus 5 per task, because it writes 1.6 times the output tokens. Anthropic's Boris Cherny says a couple of short prompts had it write formal proofs about the Claude Agent SDK, leading to 16 pull requests fixing bugs and race conditions. Subscribers get higher five-hour limits.
Introducing Claude Opus 5.5, the first model in our new Claude 5.5 family.
— Claude (@claudeai) September 22, 2026
It performs at the level of Claude Fable 5.1 for most tasks, and costs 40% less to run than Opus 5. pic.twitter.com/Q9C2VKQ79f
OpenAI ships GPT-6 Sol and Luna at half GPT-5.6's price
GPT-6 Sol and Luna are OpenAI's cheaper tiers under GPT-6 Astra, now $2 and $10 per million tokens for Sol and $0.10 and $0.50 for Luna, 50% below GPT-5.6's promotional price. On coding, Artificial Analysis's Coding Agent Index has Sol up 2 points on GPT-5.6 Sol, with Terminal-Bench 4.0 at 43% against 37%. Luna fell 2. OpenAI's Tibo Sottiaux calls them "a very significant improvement across the board." ChatGPT Plus, Pro and Business users got a banked usage reset.
Please welcome GPT-6 Sol and GPT-6 Luna to the GPT-6 universe.
— OpenAI (@OpenAI) September 22, 2026
GPT-6 Sol and Luna build on the advances behind GPT-6 Astra, bringing much of its strengths into faster and more affordable models to support work at scale.
We’ve also made caching and inference more efficient, and… pic.twitter.com/5LiVE4rbFt
DigitalOcean opens a pay-per-use cloud for coding agents
DigitalOcean opened Managed Agents to everyone in public preview. It hosts coding harnesses "such as Claude Code, Codex CLI, and OpenCode" in sessions that can pause when idle and "resume paused work in ~300 milliseconds." CPU is billed per second of actual use. DigitalOcean's example: two vCPUs at 25% use for an hour "would cost $0.060 in CPU and memory charges, compared with $0.126" for the full allocation. Inference and storage cost extra.
DigitalOcean Managed Agents is now in public preview.
— DigitalOcean (@digitalocean) September 22, 2026
Run Claude Code, Codex, or your own LangGraph agent in a runtime environment that pauses when idle. Put its tools behind one governed endpoint, and pick from 75+ open and proprietary models. One cloud, one bill.
Prompts to… pic.twitter.com/iPiPlxp0iD
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Ones to watch: early, unverified
- Unreal Agent: Unreal Labs says its agent harness "delivers up to 40% cost savings compared to Codex on production workloads and coding/science benchmarks, without any negative performance impact," by handling tool calls asynchronously. The maker's claim; nobody else has published a run yet.
Also worth your time
- Max Woolf had coding agents optimize his Rust libraries and reports "anywhere from 2x-20x speedup depending on the domain," with his prompts and benchmark results included.
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