Open models just gottoo cheap to ignore
This is the first edition of Cinco. The format is what the name says: five things a week, chosen from a couple of hundred I read, each with what it is, what was demonstrated, what was not, and why it matters to people who build. The original source is always one click away.
The week had a theme without anyone agreeing on it: cost. Two Chinese labs released open-weight models under truly permissive licenses — one of them served, the company says, only on domestic chips, at fifteen cents per million tokens. In the same window, OpenAI launched GPT-6 Astra without touching the price, and admitted in its own report that reading the model's reasoning has become less reliable. A Fudan benchmark reminded us that, on real scientific software, the best agent solves fewer than half the bugs. And Brazil published, with a number and a deadline, the tender for the RN supercomputer.
If you only have time for one: the second.
This week's five
- 1
Tencent open-sourced a 770B MoE under Apache 2.0 — and it edges Kimi K3 on code with a quarter of the parameters
It is the largest Apache-2.0 open-weight release of the period, and it confirms the pattern: Chinese labs shipping frontier-adjacent agentic coders at a fraction of proprietary cost.
- 2
GLM-5.3-Flash: an MIT-licensed 320B model served entirely on Chinese chips, at US$ 0.15 per million tokens
It is the clearest datapoint yet that a competitive model can be trained and served at scale without NVIDIA hardware — and it prices Opus-class agentic work at cents.
- 3
On real scientific software, the best coding agent solves fewer than half the bugs
It quantifies the gap between saturated leaderboards and real domain-heavy engineering — exactly where engineers will be asked to deploy agents next.
- 4
GPT-6 Astra: same price, new benchmark ceiling — and a system card that says reasoning is getting harder to monitor
For builders, it resets the frontier price/performance point; for governance, it is the first flagship whose own report admits reading the reasoning is becoming less reliable.
- 5
The government published the R$ 959 million tender for the Rio Grande do Norte AI supercomputer — bids due 8 October
It is the first concrete, dated and funded step toward sovereign AI compute in Brazil — and the tender terms will shape which stacks Brazilian engineers get to use.
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What changed since the last edition
- Tencent open-sourced a 770B MoE under Apache 2.0 — and it edges Kimi K3 on code with a quarter of the parameters
- GLM-5.3-Flash: an MIT-licensed 320B model served entirely on Chinese chips, at US$ 0.15 per million tokens
- On real scientific software, the best coding agent solves fewer than half the bugs
- GPT-6 Astra: same price, new benchmark ceiling — and a system card that says reasoning is getting harder to monitor
- The government published the R$ 959 million tender for the Rio Grande do Norte AI supercomputer — bids due 8 October
- ReAct: interleaving reasoning and action is what made the first language agents work
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Today, one person: João Campista, in São Paulo. I read a couple of hundred things a week and pick five. Triage is AI-assisted; the reading, the judgment and the writing are mine.