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Build more natural voice experiences with GPT‑Live‑1 in the API

OpenAI releases GPT-Live-1 in the API, a full-duplex voice model that handles interruptions natively and delegates reasoning to backend models.

OpenAI launched GPT-Live-1 in the API, a single-model full-duplex voice system that listens and speaks simultaneously, replacing chained STT-LLM-TTS architectures. It improves Full Duplex Bench performance by 30 percentage points over GPT-Realtime-2.1 and ranks #1 on Tau3 when paired with GPT-6 Astra at medium reasoning effort. Early partner Speak reported nearly 80% fewer interruptions in language tutoring. The API release costs $0.05 per minute for the front-end voice layer and supports telephony, native ASR transcripts, keyword biasing, and expanded voice and language options.

OpenAI News · 7d agoModel release1

[AINews] DeepSeek v4.1-Flash: 763B-P8B-D16B novel causal Encoder–Decoder architecture with vision marks the Return of the Whale

DeepSeek released V4.1-Flash, an open-weight 763B-parameter model with a novel causal encoder-decoder architecture, 1M context, vision input, and MIT license.

DeepSeek launched V4.1-Flash, an open-weight MIT-licensed model using a novel causal encoder-decoder architecture with 763B total parameters and asymmetric active parameters: 8B for prefill and 16B for decode. It supports 1M-token context and text+image input, priced at $0.30 per 1M input and $1.20 per 1M output tokens with a 50% off-peak discount. Artificial Analysis scored it 40 on its Intelligence Index, above DeepSeek V4 Pro 0813, and Vals ranked it the #1 open-weight model ahead of Kimi K3. Baseten shipped day-0 support and Ollama began rolling it out to paid subscribers.

Latent Space · 5d agoModel release 2 sources1

OpenAI's GPT-Live-1 API lets developers build apps that talk and listen at the same time

OpenAI's GPT-Live-1 API enables full-duplex speech apps, outperforming GPT-Realtime-2.1 with 0.8s turn-taking latency at $0.05 per minute.

OpenAI released GPT-Live-1 as a developer API for full-duplex speech, allowing applications to listen and talk simultaneously; it already powers ChatGPT voice. Benchmarks show 80.1% on full-duplex interactivity versus 45.4% for GPT-Realtime-2.1, turn-taking latency of 0.8 seconds versus 1.4 seconds, tool-calling accuracy of 87% versus 60%, and a 32% pass rate on a banking voice-support benchmark versus 12.4%. The model costs $0.05 per minute, ships twelve new voices, provides ASR transcripts and response text, and is already in production at Yelp for phone-based reservations.

The Decoder · 6d agoModel release1

[AINews] Claude Fable/Mythos 5.1: new SOTA model, 75% cache price cut but 70% more output tokens

Anthropic launched Claude Fable 5.1 and Mythos 5.1, claiming new SOTA benchmarks, with 75% cache-read price cut and 1M-token context.

Anthropic released Claude Fable 5.1 and Mythos 5.1 as flagship models for coding and knowledge work, with a 1M-token context window and pricing of $10/$50 per million input/output tokens and cache reads cut 75% to $0.25. Artificial Analysis Intelligence Index scored Fable 5.1 at 66 versus 63 for Claude Opus 5, with HLE at 59.1% and Terminal-Bench v2.1 at 91.4%, though per-task cost rose ~20% due to 1.7x output token usage. Community analysis suggested Fable and Mythos may share underlying weights with different safety/routing behavior, and release notes highlighted Enterprise Frontier Safeguards and zero-data-retention support.

Latent Space · 15d agoModel release2

[AINews] NVIDIA buys HuggingFace for $13B, as OpenAI publishes their HF incident retro

Z.ai released open-weight GLM-5.3-Flash (320B/18B active, 1M context, MIT) while Nvidia confirmed buying Hugging Face for $13B.

Z.ai formally launched GLM-5.3-Flash, the model previously previewed as Ox Alpha: 320B total parameters with 18B active, a 1M-token context window, natively multimodal, MIT-licensed, and claimed on par with Claude Opus 4.8 on coding. Artificial Analysis scored it 57 on its Intelligence Index at $0.09 per task, roughly 7.5x cheaper than GLM-5.3, and it scored 84.3% on Terminal-Bench 2.1. Nvidia's $13B acquisition of Hugging Face (~80x its $150M ARR) was confirmed, nearly double its initial $7B January offer. The roundup also notes Qwen shipping an impressive Flash model on Chinese chips as part of a broader open-model narrative.

Latent Space · 21d agoModel release1

unsloth/Qwen3.8-Flash-Next-GGUF — new model trending #21 on Hugging Face

Qwen released Qwen3.8-Flash-Next, an experimental 125B-parameter open-weight MoE previewing the Qwen4 architecture, with Unsloth shipping optimized GGUF quants.

Qwen released Qwen3.8-Flash-Next, an experimental open-weight preview of the architecture planned to underpin Qwen4. The model has 125B parameters with 6B activated, 512 experts (10 routed plus 1 shared), Qwen Sparse Attention (QSA), Gated DeltaNet, Gated Residual, and n-gram embeddings, with 262,144-token native context extendable to 1,000,000 tokens. Unsloth provides Dynamic 3.0 GGUF quantizations, and multi-token prediction (MTP) delivers 1.3-1.7x faster inference via llama.cpp or Unsloth Desktop.

Hugging Face trending models · 21d agoModel release1