#Modelos de IA

Claude Fable 5.5 has not been announced: no model id, no model card, no pricing. A tracker, with dates and sources, of what's confirmed (Fable 5.1 is still the current model, Anthropic's IPO is targeted for mid-November) and what's just timeline chatter (hidden routing, viral demos, a URL returning 404). Plus what to do with your code in the meantime.

GPT-6 Sol and Luna arrived at half the price of GPT-5.6, Claude Opus 5.5 delivers Fable 5.1 level at $4/$20 with four breaking changes in the API, and Google says Gemini 4 ships before the end of the year. What each one brings that's different, the catches (Luna regresses on agentic coding, Opus default effort dropped to medium), and which one to use now.

Grok 4.7 landed on September 21, 2026 costing 5x less per token than Fable 5.1 and GPT-6 Astra, and it still loses to Astra on cost per completed task. Where this model actually pays off (spoiler: latency, not code), where it sits 22 points behind on Terminal-Bench, and the math that takes apart the list-price comparison.

Jev costs $0.042 per million tokens and is a closed API. Laya is Apache 2.0, runs offline on a GPU from 2018, and measures 7.8x faster at P50. A comparison using the numbers each side published, plus the prior-art fight that blew up on Hacker News two days after the launch.

TypeSafe launched Jev, the first System One model: it doesn't complete text, it takes your program's state and returns a typed decision in a single parallel pass. No parser, no retries, no broken JSON. In this post: what Jev actually is, why it can't hallucinate (and why that doesn't mean it can't be wrong), the real math on $0.042 per million tokens with free output, the three primitives with running Python code, and the 5 traps the docs themselves admit to.

GPT-6 Astra is OpenAI's new top-of-the-line model, launched on September 3, 2026 at $10/$50 per million tokens, the same price as Claude Fable 5.1. Benchmark by benchmark against Fable 5.1 and GPT-5.6 Sol, the cache math that makes an agent session 54% more expensive on Astra, and the ARC-AGI-3 run where the same model scored 62.7% or 99.9% just by swapping the harness.

Anthropic released Claude Fable 5.1 on September 1, 2026. It beats Opus 5 on every published benchmark, but almost always by 2 to 3 points, and it costs twice as much per token. The official numbers, the real math on an agentic session with a warm cache (where the cost ratio drops from 2x to 1.3x), the decision tree between Fable 5.1, Opus 5 and Sonnet 5, and the 3 breaking changes that break your code if you just swap the model id.

Alibaba announced Qwen3.8-Flash-Next: 125B total with only 6B active per token, plus 51B in N-gram embeddings and a redesigned sparse attention. What Qwen has confirmed, what's still community estimate, how much memory it really needs, and why the architecture is being published ahead of Qwen 4. No official benchmark has come out so far.

Ox Alpha was GLM-5.3-Flash. Five days before any announcement, tokenizer fingerprinting was already pointing to Zhipu: 95 out of 95 against the GLM-5 vocabulary. Now Z.ai has confirmed it, published the weights on Hugging Face under an MIT license and revealed the architecture: 320B total with 18B active, 1M context, $0.075 per million. The 80% benchmark is still what it always was: a sample of ten tasks. On the full set, 63%.

Google ran the same play and shipped Flash before Pro. Except the $0.75/M that took over the timeline isn't a low price: the official table shows it's the 3.6 Flash price with a 50% discount through December 31, 2026, and the bill doubles on January 1. Here are both numbers, the real benchmarks (FrontierCode 43.6%, AutomationBench 30.4%), what breaks when you migrate from 3.6, and the data point the release leaves out: hallucination went up from 55.6% to 64.5%.

A month before the GPT-6 launch, OpenAI announced that an internal version of Astra solved 10 open problems in mathematics and complexity, with verifiable Lean proofs. A record of what was confirmed (Connes, Erdős, non-sofic groups, the $2,000 cost), the mathematicians' skepticism, and what circulated as rumor until the model shipped.