The article reports the release of new AI models: Claude Opus 5.5 by Anthropic and GPT‑6 Sol and GPT‑6 Luna by OpenAI, noting that GPT‑6 variants are priced at half the cost of their GPT‑5.6 counterparts. It provides a detailed pricing table comparing input, cached input, and output costs across several models, highlighting how GPT‑6 Luna is among the cheapest ever offered by OpenAI. The author also comments on visual differences in model outputs, noting that GPT‑6 outputs are more muted compared to GPT‑5.6.
Simon Willison announces the release of Kimi K3.1 Pro on the Kimi API, noting it is not yet open‑weights but full weights will be available by Nov 4 2026. The model offers a high‑speed variant 2‑3× faster at double the price, with US dollar pricing of $2.00/million input tokens and $10/million output tokens—matching GPT‑6.1 Sol and half the cost of Claude Opus 5.5. Benchmarks from Moonshot show Kimi roughly on par with Opus 5.5 and GPT‑6 Astra, scoring 55 in Artificial Analysis, ahead of several competitors.
Claude Sonnet 5.5, a new model from Anthropic, is announced as running 30% faster and costing up to 30% less than its predecessor while matching or exceeding performance on benchmarks. It is now the model powering the free tier on claude.ai, offering a more capable free experience than OpenAI’s ChatGPT free tier, which uses Luna 5.6. The release also mentions upcoming availability of Haiku 5.5 in the coming weeks.
Anthropic’s top AI model is struggling to attract users even as cheaper alternatives thrive. The company’s July revenue is projected at $65 bn, up from $47 bn in May, and it expects Q3 profitability while boasting 6,000 high‑spending customers. In contrast, OpenAI’s revenue has risen 35 % this quarter, spurred by GPT‑5.6, and a Ramp AI index shows Anthropic’s newer models (e.g., Fable) are less popular than older ones like Opus 4.8.
Qwen 3. 8 27B scores 52 on the Artificial Analysis Intelligence Index That's the same score as GPT-5.
The article discusses Anthropic’s Claude Fable 5.1 release, highlighting its claimed improvements in coding, knowledge work, and problem‑solving, particularly a 52.6% score on the new Terminal‑Bench‑Science 0.1 benchmark. The author examines the model’s performance on the pelican benchmark, noting that Fable 5.1’s five reasoning levels (low, medium, high, xhigh, max) sometimes skip reasoning entirely for certain prompts, as evidenced by token counts and cost metrics. The piece provides detailed transcript data for each reasoning level when generating an SVG of a pelican riding a bicycle.