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Models2026-09-03 · source-backed
A September 1 analysis rebuilds Artificial Analysis's chart on a linear rather than logarithmic cost axis and prices models at what third-party providers actually charge. The spread is roughly 250x top to bottom: Fable 5.1 at $3.69 per task for intelligence 66, GLM-5.3-Flash at $0.023 for 55, a locally-run Qwen3.8-27B at $0.015 for 52. The author claims GLM-5.3-Flash covers about 90% of typical use at one-sixtieth the cost. Log axes are the right call for the physics and the wrong call for a budget conversation.
Each link below shares sources, entities, or timing with this story.
Three points behind GLM-5.3 at 60, tying GPT-5.6 Terra and Muse Spark 1.2, at $0.09 per task against $0.68 for GLM-5.3 max (Latent Space). It burned 149M output tokens to run the index, of which 134M were reasoning tokens, more than Kimi K3 at 133M or Qwen3.8 2.4T A95B at 136M...
Anthropic released Claude Fable 5.1 on September 1. Claude Code v2.1.257 made it the default Fable model at 17:53 UTC that day, with a 1M-token context window, $10 per million input tokens, $50 per million output, and $0.25 per million on cache reads (claude-code CHANGELOG). B...
The open-weight race just changed constraint. Moonshot AI suspended all new consumer subscriptions on July 20, roughly 48 hours after Kimi K3 launched, because request volume pushed its compute cluster to capacity. Remaining GPUs are reserved for existing paid subscribers. Tec...
Runta published FrontierHarness on September 2 and it's the most directly useful benchmark I've read this quarter, because it controls the one variable everyone conflates. Nine agent harnesses (Codex, Claude Code, OpenCode, Pi, Oh My Pi, DeepSeek Harness, Kimi Code, Exo Harnes...
OpenAI cut GPT-5.6 Luna roughly 80%, from $1 to $0.20 per million input and $6 to $1.20 output. Anthropic priced Opus 5 at $5/$25 per million, half of Fable 5. The trigger is DeepSeek, Zhipu's GLM-5.2 and Moonshot's Kimi K3 landing 60-90% below US flagship pricing, with DoorDa...
Anthropic shipped Fable 5 on June 9. Willison spent ~5.5 hours stress-testing it: slow and expensive, but it handled everything he threw at it, including agentic coding. (Simon Willison) The tell that it's a real working model and not a benchmark queen: because it post-dated A...
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