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SpaceXAI releases Grok 4.5, which Elon describes as an ‘Opus-class model’
12:30 PM PDT · July 8, 2026
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SpaceXAI has released its latest model, Grok 4.5 — the first since the company went public several weeks ago.
In a blog post published Wednesday, SpaceXAI characterized its new release as a workhorse that can tackle all of the typical tasks that the AI industry has sought to automate: coding and app-building, office and clerical work, research, writing, and other forms of routine knowledge work.
Grok can supposedly do all this for less spend, too, as SpaceXAI says that its model has “twice greater token efficiency” than other leading models. If it carries through to real-world use cases, that efficiency would be a big advantage for SpaceXAI, since the cost of tokens has been a growing concern for AI consumers.
The company released benchmark metrics Wednesday that appeared to show Grok’s competitiveness with other top models from SpaceXAI competitors, although just short of best-in-class:
Image Credits: SpaceXAI
In a post on his social media platform X (which is a subsidiary of SpaceXAI), founder Elon Musk compared the model to Opus, Anthropic’s LLM designed for intensive and complex tasks.
“Based on strong positive feedback from customers in our beta test program, @SpaceXAI will make Grok 4.5 available to the public tomorrow. It is an Opus-class model, but faster, more token-efficient and lower cost,” wrote Musk in his post on X.
Musk later added: “Our internal assessment is that Grok 4.5 is roughly comparable to Opus 4.7, but much faster. The combination of capability, faster speed and lower cost is what makes it competitive.”
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SpaceXAI says that its new model costs $2 per million input tokens and $6 per million output tokens. That’s quite competitive, if Grok’s capabilities match SpaceXAI’s rhetoric.
Opus 4.7, by comparison, costs $5 per million input tokens and $25 per million output tokens. OpenAI has tiered costs for different model versions: Sol, its most expensive, costs $5 for 1 million input tokens and $30 for 1 million output tokens, while its least expensive, Luna, costs $1 for 1 million input and $6 for 1 million output tokens.
It’s a big week for AI model releases. OpenAI is planning to release GPT 5.6, its latest, most powerful model, on Thursday. The release of that model had previously been limited by the Trump administration, due to concerns about its security implications. OpenAI has called it its “strongest model yet.”
Topics
AI, ChatGPT, Elon Musk, Grok, OpenAI, spacexai
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Lucas Ropek
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Lucas is a senior writer at TechCrunch, where he covers artificial intelligence, consumer tech, and startups. He previously covered AI and cybersecurity at Gizmodo.
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OpenAI releases new voice models for more natural live conversations
10:00 AM PDT · July 8, 2026
OpenAI today released new conversational models, called GPT-Live-1 and GPT-Live-1 mini, claiming that they sound more natural and can handle turn-taking better. These are full-duplex models, meaning they can speak and listen at the same time, allowing users to interrupt naturally and enabling features like live translation.
The company is also replacing its current Advanced Voice Mode in ChatGPT with GPT-Live-1 mini by default. Users of paid tiers will be able to access the larger GPT-Live-1 model. The previous model combined a speech-to-text model to transcribe speech, a large language model to generate responses, and a text-to-speech model to deliver the final answer.
The company said in a press briefing that the new models solve issues like interrupting users while they’re talking and not having enough intelligence to answer questions. OpenAI’s new models will send the query to its latest text models like GPT-5.5 for search, reasoning, or agentic capabilities while continuing the conversation.
OpenAI also showed that the model can stay silent for a long time and absorb the context of the conversation until it’s called upon. Plus, as the new voice mode has access to newer GPT models, it can also present some information in a visual format. Other startups like Monogram, which raised $40 million in seed funding from DST and Lux Capital, are also leaning into visual responses to make assistants more interactive.
The company said the new voice mode in ChatGPT is designed to have longer conversations. During the briefing, ChatGPT Voice’s product lead, Atty Eleti, said he has had 30- to 40-minute-long conversations with the voice feature during walks.
OpenAI thinks that voice could be the primary interface to computing for complex work. Reports have suggested that it could launch a pair of earbuds with AI capabilities this year. However, it didn’t provide any information on hardware products.
“Over time, we think this will also unlock the ability to use voice as a kind of primary interface to computing, and to manage increasingly complex long-running agentic work. The kind of amazing use cases that we see people using Codex and ChatGPT to accomplish, we think voice can be the future interface to all kinds of work,” Eleti said.
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OpenAI has worked on bolstering voice-based features over the past few years to make ChatGPT’s voice mode sound more natural. The company said that more than 150 million people talk to ChatGPT using features like Voice and Dictation.
Rivals are also attempting to make assistants more expressive.
Both Apple and Amazon have updated their assistants to be more conversational with better context handling. Startups like Sesame, founded by Oculus co-founder Brendan Iribe and Ankit Kumar, also launched AI assistants with more natural conversation while completing tasks in the background.
OpenAI is moving in the same direction, aiming to let users talk to its assistant hands-free for a longer time. Despite its claim that the new voice mode sounds more natural, the company emphasized that it’s not aiming to make this an AI companion. It noted that the new models have safeguards built in to give age-appropriate responses to teens and provide resources if the conversation turns to topics like self-harm.
The new voice mode still needs work. During the demo, when the company showed its live translation feature in Hindi, the assistant had a heavy American accent and spoke in Hindi that was unnatural sounding and had slightly bookish tone. The company said the new mode is optimized for “most spoken languages” but didn’t specify which ones.
Topics
AI, AI, Apps, ChatGPT, voice model
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Image Credits: ZML
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Hot French startup ZML releases free product to speed inference across lots of AI chips
1:00 AM PDT · July 8, 2026
The days of Nvidia’s unparalleled market dominance aren’t over, but challengers and choices are arising from all directions.
ZML, a hot French AI startup endorsed by Turing Award winner Yann LeCun, has released inference-performance software that allows a variety of open source large language models to run on a variety of chips — including Nvidia’s, AMD’s, Google’s TPU, Apple Metal, and Intel Arc.
With ZML/LLMD, the newly launched LLM inference server, the company’s ambition is to break existing silos and make different chips available for AI use cases at their maximum available speed, and sometimes faster, ZML founder Steeve Morin told TechCrunch.
As AI becomes integrated into our work and everyday lives, optimizing inference — aka, the processing of prompts — has been outpacing model training in importance, but often feels patchy behind the scenes, with software and architecture barriers that lead to vendor lock-in, Morin said.
The promise of achieving peak performance across a variety of chips is a technological feat, but it could also be a market disruptor, amid mounting fears over AI-related costs.
ZML hopes to provide enterprises and clouds with the option to use a mix of chips, some of which might be less costly or consume less energy. “The idea is to give people back the power to create their own system and achieve real efficiency gains that allow [AI] to be disseminated,” Morin said.
Such a software assist may help novel AI chipmakers, many of which happen to be from Europe, Morin observed, citing Axelera, Fractile, Kalray, OLIX, Q.ANT, SiPearl, SpiNNcloud, and VSORA. But more than their region of origin, what matters to him is that ZML can work with them on “things that haven’t been done before anywhere in the world.”
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That doesn’t mean Morin is bearish on Nvidia. He’s not, in part because of its existing supply. He told TechCrunch that ZML has a good relationship with the AI chip giant, which has been gearing up for the rise of inference.
Inference has been an area of such intense investment that the trend has been hailed the “ inference gold rush.” So ZML has competition such as Baseten, recently valued at $13 billion; Inferact, from the creators of open source project vLLM; as well as RadixArk, the commercial company behind SGLang.
Both vLLM and SGLang partially compete with LLMD, but Morin’s ambitions for ZML cover a broader spectrum. “We have reached the point where we are co-designing silicon,” he said. He further credited ZML’s lean team of 20 people as the reason why the Paris-based startup has been able to move fast, with more releases in the plans.
It also helped that this small team is well funded for its size. Thanks to his track record as VP of engineering of Zenly, which Snapchat acquired for nine figures in 2017, Morin raised $20 million from venture firms including Harry Stebbings’ 20VC, >commit, AALVC, Drysdale Ventures, Xavier Niel’s Kima Ventures, Kindred Capital, LocalGlobe, and Puzzle Ventures.
Unlike ZML’s first public project, the inference-focused ML framework released in 2024 and updated in March, ZML/LLMD is not open source. But it is launching as a free product with the goal of learning about usage. “I’d rather measure and [then generate revenue] where it is most effective without hindering my growth stupidly because I have been too greedy from the get-go,” Morin said.
It is too early to tell when ZML/LLMD might become a paid product, and what its adoption will look like. But the startup’s cap table confirms that other founders are paying attention, including Dagger and Docker founder Solomon Hykes, Clément Delangue and Julien Chaumond from Hugging Face, as well LeCun, now with AMI Labs. This also builds the case that Europe’s AI startups can now build from home. “I couldn’t do ZML anywhere but in Paris,” Morin said.
Topics
AI, AI inference, Europe, Exclusive, France, Fundraising, Startups, ZML
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As a freelance reporter at TechCrunch since 2021, she has covered a large range of startup-related topics including AI, fintech & insurtech, SaaS & pricing, and global venture capital trends.
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