English translation is being prepared.
Matched fieldsSummary
←Search results
Search “OpenAI”
English translation is being prepared.
Matched fieldsSummary
English translation is being prepared.
Matched fieldsSummary
English translation is being prepared.
Matched fieldsSummary
English translation is being prepared.
Matched fieldsSummary
English translation is being prepared.
Matched fieldsSummary
English translation is being prepared.
Matched fieldsSummary
English translation is being prepared.
Matched fieldsSummary
English translation is being prepared.
Matched fieldsSummary
English translation is being prepared.
Matched fieldsSummary
English translation is being prepared.
Matched fieldsSummary
Xiaomi MiMo-V2.5-Pro achieves multiple breakthroughs on the Arena leaderboard
Xiaomi MiMo announced on April 26 that MiMo-V2.5-Pro has achieved multiple breakthroughs on the latest Arena leaderboard: Text Arena (Expert) ranks 6th globally and 1st among open-source models, while also ranking 1st among Chinese models; Xiaomi ranks 3rd globally by lab, behind only Anthropic and OpenAI. Text Arena (Overall) ranks 2nd among open-source models globally, Code Arena (WebDev) ranks 3rd among open-source models globally, and it ranks 1st among open-source models globally in four sub-leaderboards: Hard Prompts, Hard Prompts (English), Instruction Following, and Long Query. On April 28, Xiaomi MiMo further open-sourced the MiMo-V2.5 series under the MIT license, supporting commercial deployment, continued training, and fine-tuning without additional authorization; both models support a 1M token context window, with MiMo-V2.5-Pro targeting complex agent and coding tasks and ranking first among open-source models on GDPVal-AA and ClawEval, while MiMo-V2.5 is a native omni-modal model. SGLang and vLLM provided support on day one and completed Day-0 adaptation for multiple chip platforms.
: Text Arena (Expert) ranks 6th globally and 1st among open-source models, while also ranking 1st among Chinese models; Xiaomi ranks 3rd globally by lab, behind only Anthropic and OpenAI. Text Arena (Overall) ranks 2nd among open-source models globally, Code Arena (WebDev) ranks 3rd among open-source models globally, and it ranks 1st among open-source models globally in four sub-leaderboards: Hard Prompts, Hard Prompts (English), Instruction Following, and Long Query. On April 28, Xiaomi MiMo fu
Matched fieldsSummary
English translation is being prepared.
Matched fieldsSummary
English translation is being prepared.
Matched fieldsSummary
Mistral Releases Large 4 Open-Weight Model, Focused on Coding and Cyber Defense
French company Mistral AI has released the Large 4 model (ML4), featuring advanced coding and cyber defense capabilities; enterprises can download the open-weight version and deploy it to run on their own infrastructure. The model has a total of 1.05 trillion parameters, with approximately 52 billion parameters actually activated per task execution, and was trained in a European data center using 3,800 NVIDIA Grace Blackwell GPUs. Mistral claims it is comparable to other leading open models on coding tasks and emphasizes that open source helps prevent frontier AI technology from concentrating in the hands of a few players.
French company Mistral AI has released the Large 4 model (ML4), featuring advanced coding and cyber defense capabilities; enterprises can download the open-weight version and deploy it to run on their own infrastructure. The model has a total of 1.05 trillion parameters, with approximately 52 billion parameters actually activated per task execution, and was trained in a European data center using 3,800 NVIDIA Grace Blackwell GPUs. Mistral claims it is comparable to other leading open models on c
Matched fieldsBody
Edge0 Releases Audio8-TTS-Realistic: A 0.6B Open-Source Voice Cloning TTS Model
Edge0 has released the open-weight voice cloning TTS model Audio8-TTS-Realistic, with 601M parameters, supporting 23 languages, with weights and code released under Apache 2.0. The model requires only 1 reference audio clip and its corresponding text for zero-shot voice cloning, and can also directly generate speech when no reference voice is available. Self-reported results show an average error rate of 4.86% on the CV3 nine-language benchmark, lower than Qwen3-TTS-1.7B's 7.73%, but it lags behind 4B-class models on the MiniMax benchmark, with Thai WER reaching 48.57%.
Edge0 has released the open-weight voice cloning TTS model Audio8-TTS-Realistic, with 601M parameters, supporting 23 languages, with weights and code released under Apache 2.0. The model requires only 1 reference audio clip and its corresponding text for zero-shot voice cloning, and can also directly generate speech when no reference voice is available. Self-reported results show an average error rate of 4.86% on the CV3 nine-language benchmark, lower than Qwen3-TTS-1.7B's 7.73%, but it lags beh
Matched fieldsBody
10-person team Phonic releases speech model Phonic-1, claims it can query and book in parallel during calls
The 10-person startup Phonic has released a speech model, Phonic-1, which it says can execute queries and bookings before the caller has finished speaking. The model tops the Artificial Analysis speech-to-speech leaderboard with a score of 87.1, 0.2 points higher than xAI's Grok Voice 3.0, with a customer service task completion rate of 79.9% and a first-audio latency of 0.61 seconds. Phonic says it scored 90.2 on the Cekura call test set, but the public Cekura leaderboard lists Phonic v1 at 68.3%; the company has completed a $27.5 million Series A round led by First Round, bringing total funding to $31.5 million.
The 10-person startup Phonic has released a speech model, Phonic-1, which it says can execute queries and bookings before the caller has finished speaking. The model tops the Artificial Analysis speech-to-speech leaderboard with a score of 87.1, 0.2 points higher than xAI's Grok Voice 3.0, with a customer service task completion rate of 79.9% and a first-audio latency of 0.61 seconds. Phonic says it scored 90.2 on the Cekura call test set, but the public Cekura leaderboard lists Phonic v1 at 68.
Matched fieldsBody
Google releases Gemini 4 Carbon, topping the Artificial Analysis Intelligence Index with 59 points
Google has released its new-generation flagship model Gemini 4 Carbon, which tops the Artificial Analysis Intelligence Index v5.0 with 59 points, surpassing Claude Opus 5.5 and GPT-6 Astra. On Terminal-Bench 4.0, the model improved from Argon's 57.1% to 65.2%, and on the GraphWalks long-context test it rose from 84.2% to 96.2%, but developers report that its generation speed is about 2 to 4 times slower than Argon. This week Google first opened it to a small number of cybersecurity defense organizations, then expanded it to trusted partners through the Fairwind program; the opening time for general users has not yet been announced.
Google has released its new-generation flagship model Gemini 4 Carbon, which tops the Artificial Analysis Intelligence Index v5.0 with 59 points, surpassing Claude Opus 5.5 and GPT-6 Astra. On Terminal-Bench 4.0, the model improved from Argon's 57.1% to 65.2%, and on the GraphWalks long-context test it rose from 84.2% to 96.2%, but developers report that its generation speed is about 2 to 4 times slower than Argon. This week Google first opened it to a small number of cybersecurity defense organ
Matched fieldsBody
Chaoyan Intelligence Open-Sources 35B Model Apex-35B-V1.0, with AI Participating in Its Own R&D
Beijing-based large model startup Chaoyan Intelligence has released and open-sourced its first large model, Apex-35B-V1.0, with 35 billion total parameters, approximately 3 billion parameters activated per token, and support for a 262,000-token context window, optimized through mid-training and post-training based on Qwen3.6-35B-A3B. The model scored 60.9 and 40.0 on the paper reproduction test PaperBench and the scientific research challenge test FrontierScience, respectively, higher than GLM-5.3's 42.5 and 30.7; it scored 84.0 on the tool-calling test BFCL V4, higher than DeepSeek-V4.1-Flash-1017's 75.0. The model has been released with open weights under the Apache 2.0 license, and the official release provides approximately 72GB of BF16 weights and GGUF quantized versions at various precisions.
Beijing-based large model startup Chaoyan Intelligence has released and open-sourced its first large model, Apex-35B-V1.0, with 35 billion total parameters, approximately 3 billion parameters activated per token, and support for a 262,000-token context window, optimized through mid-training and post-training based on Qwen3.6-35B-A3B. The model scored 60.9 and 40.0 on the paper reproduction test PaperBench and the scientific research challenge test FrontierScience, respectively, higher than GLM-5
Matched fieldsBody