Key Points
SpaceXAI released Grok 4.5 on July 9 at $2 per million input tokens.
Grok 4.5 is 60% cheaper than Claude Opus 4.8 on input costs and 76% cheaper on output costs.
The model was trained on Cursor developer data using tens of thousands of NVIDIA GB300 GPUs.
Grok 4.5 targets coding, agentic tasks, and enterprise knowledge work with comparable capability to Opus 4.7.
SpaceXAI released Grok 4.5 on July 9, 2026, calling it its smartest model yet and the first built using data from Cursor, the AI coding tool it acquired earlier this year. Elon Musk described it as an Opus-class model that is faster, more token-efficient, and cheaper than rivals. Priced at $2 per million input tokens and $6 per million output tokens, Grok 4.5 undercuts Anthropic’s Claude Opus 4.8 by 60 percent on input costs and 76 percent on output costs.
Why Grok 4.5 costs half as much as Claude
Grok 4.5 achieves lower pricing through twice the token efficiency of competing models, according to SpaceXAI. The company trained it on tens of thousands of NVIDIA GB300 GPUs at its Colossus supercluster in Memphis, Tennessee, using a mixture-of-experts architecture with 1.5 trillion parameters. Training included trillions of tokens of Cursor developer data, allowing the model to learn from real software interactions and agent workflows. SpaceXAI invested heavily in data filtering, deduplication, and quality scoring to maximize signal-to-noise ratio.
How Grok 4.5 stacks up against rivals
Musk claims Grok 4.5 is roughly comparable to Anthropic’s Opus 4.7 in raw capability but generates results much faster. Independent benchmarks show Grok 4.5 is genuinely competitive but not dominant on raw capability, according to the benchmarking firm Artificial. Claude Opus 4.8 costs $5 per million input tokens and $25 per million output tokens. OpenAI’s GPT-5.6 Luna is priced at $1 input and $6 output. Grok 4.5 excels in large codebases and handles long-running tasks spanning multiple repositories, hundreds of skills, and various tools.
What Grok 4.5 is built to do
Grok 4.5 targets coding, agentic tasks, and knowledge work including software engineering, data science, finance, and legal work. Musk announced the public release on July 8, stating it received strong positive feedback from beta testers. The model is available immediately in Cursor across desktop, web, iOS, CLI, and SDK. SpaceXAI claims Grok 4.5 is incredibly capable at coding, from challenging Rust and C++ tasks to end-to-end app building from prompt to production. A fast variant runs at $4 per million input tokens and $18 per million output tokens.
The competitive pressure reshaping AI pricing
Grok 4.5’s launch arrived hours before OpenAI released GPT-5.6 models into broad public release on the same day, July 9. Both launches signal direct price pressure on the frontier AI market. The era of $20-plus-per-million-token models is under attack. SpaceXAI trained Grok 4.5 using the same compute capacity it leases to competitors Anthropic and Google, leveraging its infrastructure advantage to undercut pricing while maintaining competitive capability.
Final Thoughts
Grok 4.5 forces a reckoning on AI pricing. At half the cost of Claude Opus with comparable capability and faster inference, it signals that the frontier model market is shifting from capability dominance to efficiency and cost. Enterprises now have a credible third option.
FAQs
Grok 4.5 costs $2 per million input tokens versus Claude Opus 4.8 at $5, a 60% discount. Output tokens cost $6 versus $25, a 76% reduction.
Grok 4.5 was trained on trillions of tokens of Cursor developer data, capturing real software interactions and agent workflows. Training used tens of thousands of NVIDIA GB300 GPUs.
SpaceXAI released Grok 4.5 to the public on July 9, 2026, after announcing it on July 8. It is available immediately in Cursor across all platforms.
Grok 4.5 costs $2 input and $6 output. OpenAI’s GPT-5.6 Luna costs $1 input and $6 output, making GPT-5.6 cheaper on inputs but identical on outputs.
Disclaimer:
The content shared by Meyka AI PTY LTD is solely for research and informational purposes. Meyka is not a financial advisory service, and the information provided should not be considered investment or trading advice.
About Author

Huzaifa Zahoor
Co FounderHuzaifa Zahoor is the engineer who built Meyka. He has spent years writing Python, training AI models, and building data pipelines specifically for financial markets. His technical articles have reached over 30,000 readers on Medium, so he knows how to make complex things easy to follow. If this article touches on how the tools work, he is the person who actually built them.
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