On July 6, Tencent Hunyuan polished the Hy3 Preview released in late April into an official version, open-sourcing it under Apache 2.0 across all channels — Hugging Face / ModelScope / GitCode / CNB, with the Hy3-FP8 quantized version also going live simultaneously. Architecturally, Hy3 continues the 295B-total / 21B-activated MoE design, plus a 3.8B MTP layer; top-8 activation among 192 experts, 80 main layers + 1 MTP layer, 64-head GQA (8 KV heads), native 256K context, vocabulary 120,832. It's the "standard configuration" of the current open-source flagship tier, but Tencent has put the focus on post-training. Compared to the Preview phase, the biggest change in the official version isn't "can it run" but "can it ship" — feedback from 50+ business teams has been condensed into three things: on tool-call stability, the accuracy variance between CodeBuddy / Cline / KiloCode three scaffolds on SWE-Bench Verified has been compressed to within 4%, with a significant reduction in dead-loop invalid calls; on hallucination resistance, internal evaluation's hallucination rate dropped from 12.5% to 5.4%, common-sense error rate from 25.4% to 12.7%; on multi-turn complex intent, composite multi-turn question rate dropped from 17.4% to 7.9%, with the open-source long-conversation benchmark MRCR jumping from 42.9% to 75.1%. Even more impressive is the blind test with 270 cross-domain experts: across 312 valid comparisons, Hy3 scored 2.67/4, leading GLM-5.1's 2.51/4, with the gap most pronounced in "front-end development / CI/CD / data storage" three blocks. In other words, Hy3's differentiation bet is real-engineering-link reliability, not leaderboard ceilings. On deployment, the official provides dual vLLM and SGLang recipes, MTP speculative decoding, tool-call/reasoning parser all ready to go, with 8× H20-3e as the recommended minimum hardware. Short take: the open-source flagship competition over the past half year has quietly shifted from "who's longer / who's better at Olympiad math" to "who can simultaneously get tool-calling, long-horizon tasks, long context into production-acceptable". Hy3 has the right direction, but whether the FP8 version can compress 295B inference cost to "independently deployable" levels will determine whether it stays in the domestic flagship camp, or truly becomes the "public utility" of the Agent era.