Ai Models 2026

Summary: Gemini 3.8 Live in 30 Seconds Google promoted two voice models to general availability on September 15, 2026: gemini-3.8-live and gemini-3.8-live-extended-thinking. Both are audio-to-audio. No speech-to-text model in front, no text-to-speech engine behind. Raw audio in, raw audio out. Pricing is quoted per minute as well as per token: $0.005/min for audio input, $0.018/min for audio output. There is a free tier. The only difference between the two models is thinking. The standard one rejects thinkingLevel; Extended Thinking accepts low, medium, high. Extended Thinking takes #1 on Artificial Analysis’ Speech to Speech Quality Index at 82.6. Plain 3.8 Live sits second in the Speech Agent Arena. It auto-detects and switches between 97 languages mid-conversation. The trap: without compression, audio-only sessions cap at 15 minutes and audio-plus-video sessions at 2 minutes. Google’s September did not end with 3.8 Flash. Today, September 15, 2026, two new stable models landed on the Live side of the Gemini API: Gemini 3.8 Live and Gemini 3.8 Live Extended Thinking. ...

Summary: DeepSeek V4.1 Flash in 30 Seconds DeepSeek-V4.1-Flash shipped on September 10, 2026. License is MIT, weights are on Hugging Face. 552B backbone parameters, but only 8B active while reading input and 16B while generating output. That asymmetry is the whole point of the model. New architecture: Causal Encoder-Decoder (CED). 40 layers, 20 causal encoder plus 20 decoder. The decoder’s global KV cache is projected from the encoder’s final hidden states instead of from each decoder layer’s own. Result: a global KV cache of 890 bytes per token. One quarter of V4-Flash, and 1/437 of DeepSeek-V1. Natively multimodal: images go through DeepSeek-ViT, a vision encoder trained from scratch, from the very start of language-model pre-training. Pre-training corpus is 45T tokens. Beats Claude Opus 5 on several agentic benchmarks: 90.6 vs 89.1 on Terminal-Bench 2.1, 74.2 vs 74.0 on DeepSWE v1.1, 54.8 vs 50.3 on AutomationBench. Reasoning effort is a continuous 1-100 dial, not an on/off thinking toggle. API pricing is $0.15 in / $0.60 out per million tokens off-peak, double that at peak. Roughly one twentieth of Claude Opus 5’s output price. DeepSeek is retiring V4 Pro: from September 14, 2026, deepseek-v4-pro requests get routed to V4.1 Flash and billed at Flash rates. Everyone in the open-weight race this year is chasing the same two numbers: active parameters and KV cache. The first decides what each token costs, the second decides how much memory a long context eats. GLM-5.3-Flash answered with hybrid attention, Qwen3.8-Flash-Next with 6B active parameters. ...

GPT-6 Astra in 30 Seconds GPT-6 Astra is OpenAI’s new flagship, announced on September 3, 2026. The company calls it “the world’s most intelligent and aligned model”. There is no Sol/Terra/Luna split this time. The lineup is Astra and Astra Pro. API pricing is $10 per million input tokens and $50 per million output tokens: 2.5x GPT-5.6 Sol’s promotional price, and identical to Claude Fable 5.1. The scores are high but footnoted. The headline 98.6% on ARC-AGI-3 came from a custom harness; the same model scores 62.7% on the standard one. Astra is the first OpenAI model to cross the Critical cybersecurity threshold in the Preparedness Framework. Standard access refuses parts of that work outright. Rollout is staged: Daybreak enterprise customers first, then Plus, Pro, Business, Enterprise, the API and AWS. Pro, Business and Enterprise also get Astra Pro. OpenAI launched GPT-6 Astra today, September 3, 2026. At the press briefing, president Greg Brockman first conceded that AGI remains a “gray, fuzzy thing”, then went ahead anyway: “I think it’s not unreasonable to feel that we are now in the AGI era.” He closed with the same line: “Welcome to the AGI era.” ...

TL;DR: Gemini 3.8 Flash in 30 seconds Gemini 3.8 Flash landed on September 2, 2026, three weeks after 3.7 Flash. That is the third Flash release in three months. Price did not move: $0.75 input, $3.75 output per million tokens. The promo ends December 31, 2026, then it doubles. A second model shipped alongside it: Gemini 3.8 Flash Cyber, tuned for vulnerability discovery and locked behind the new Fairwind Program. The benchmark table is split. It tops the chart on finance, legal, long video and chart reasoning, and it trails Claude Opus 5 badly on long horizon terminal and computer use work. The model “works harder”: more reasoning steps, more iterative tool calls. Same sticker price, potentially a bigger bill. The Flash release cadence has stopped being funny. 3.6 Flash shipped on July 21, 3.7 Flash on August 13, and Gemini 3.8 Flash today, September 2, 2026. Three releases in three months. ...

Summary: GLM-5.3-Flash in 30 Seconds GLM-5.3-Flash is Z.ai’s (formerly Zhipu AI) new model, released 26 August 2026. It is the first natively multimodal member of the GLM-5 series: text and images go through the same model. It is 320 billion parameters, but only 18 billion run per token. Layer count is roughly half of GLM-4.5’s: 45 against 92. The licence is MIT. Most strong Chinese models this summer shipped under bespoke community licences; here there is no fine print to read before shipping a product. It beats GLM-5.2 by a wide margin on coding and agentic tests (63.4 against 46.2 on DeepSWE) and approaches Claude Opus 4.8 overall, at roughly one tenth of GLM-5.2’s price. API pricing is $0.15 in / $0.50 out per million tokens, or $0.075 and $0.25 with the 50% discount running until 9 September 2026. It is the first model in the series to use hybrid attention: linear attention carries local dependencies, sparse attention retrieves distant context. Against GLM-5.3 that is 3x less attention compute and a 4.4x smaller KV cache. Before launch it was tested anonymously as ox-alpha on OpenCode and OpenRouter, where it became the most used model of the week. All of that traffic was served on Chinese AI chips. There is one race in open-weight models this summer: producing the same intelligence with less compute. Alibaba’s Qwen3.8-Flash-Next beat its own 397B sibling with 6 billion active parameters. Z.ai’s answer is GLM-5.3-Flash: 320 billion total parameters with only 18 billion running per token, leaving GLM-5.2 behind at a tenth of the cost. ...