❯ Alibaba prices Qwen3.8-Max at $2 per million tokens, open-sources weights next week

PRICE MOVEAlibaba has priced its 2.4-trillion-parameter Qwen3.8-Max at $2 per million input tokens and $6 per million output tokens. According to The Information, that undercuts Kimi K3 — which shipped days earlier at $3 / $15 — by one-third on input and 60% on output. Bloomberg reports Alibaba says the model beats Kimi K3 on some benchmarks and plans to release the weights of two models together next week.

VALIDATIONThis time Alibaba didn’t just toss out benchmark scores. It produced evidence outsiders can audit line by line: the model started from an empty folder, worked autonomously for 16 straight days, produced a command-line tool, and left behind 265 commits and 127 pull requests — the entire process public on GitHub. The move targets one of the hardest capabilities for today’s large models to credibly demonstrate: staying on track through long-horizon tasks. The release cadence is tight, too. Kimi K3 landed just days ago; MiniMax’s H3 went live the same day as Qwen3.8-Max, hours apart. Independent evaluator Artificial Analysis posted it to its leaderboard that same day, with an AA-Briefcase total score of 1430 Elo and a 48% rule-pass rate — above Claude Sonnet 5 and GPT-5.6 Sol at 42%, but still trailing Kimi K3.

REALITYThe internal gap on this report card is worth unpacking: Qwen3.8-Max scores 1595 Elo on analysis quality but only 1340 on presentation quality — a 255-point spread. It reads more like a model that can think its way through a problem but stumbles on the final delivery. Researchers who’ve already gone hands-on offer a more mixed read; some find it unusually sensitive to the calling framework, with the same task able to burn through over a million tokens in different environments. The teams that actually get the bargain are those willing to write their own orchestration layer; teams expecting to save money by simply swapping API endpoints will likely burn their per-token savings right back into token volume.

▪ SIGNALOpen-sourcing the weights cedes pricing power; the only layer left to monetize is the engineering that makes the model run smoothly.