The Battle for Search is heating up in 2025, following the release of DeepSeek-R1 in January. DeepSeek offers a free, open-source alternative to ChatGPT with advanced reasoning capabilities.
Our Battle for Search blog series has followed the clash between Google and ChatGPT. Now that DeepSeek has entered the race, how has this changed the industry?
DeepSeek-V3: The Next Disruptor Has Arrived
Since hitting the market in January, DeepSeek has been shaking up the LLM and SEO-sphere as we know it. Within hours of its release, it toppled ChatGPT from its top spot in the Apple App Store, and sent U.S. tech stocks plummeting.
In March 2025 its latest evolution, DeepSeek-V3, was released with almost no fanfare – no launch event, no blog post. Yet the release has rattled the industry. With 685 billion parameters and a “mixture-of-experts” system that activates only the most relevant components, DeepSeek-V3 achieves high performance with far lower resource use.
This is a major shift. Running state-of-the-art models previously required industrial-scale GPU clusters. Now, companies can run a full-scale LLM locally without giving up data, control, or speed.
“Tested the new DeepSeek V3 on my internal bench… it has a huge jump in all metrics. It is now the best non-reasoning model, dethroning Claude Sonnet 3.5.”
– AI researcher Xeophon on X.com
That kind of local performance breaks the mould for how AI is deployed – and threatens to make expensive proprietary models look outdated fast.
ChatGPT vs. DeepSeek
Generative AI now sits at the centre of how businesses create content and compete for search traffic. But not all AI solutions are equal. For teams relying on these tools to drive rankings and revenue, choosing the wrong model can mean wasted spend, stale content, and slipping search visibility.
On one side, platforms like ChatGPT offer high-performance capabilities but tie users to paywalls, limited flexibility, and opaque systems. On the other, open-source models like DeepSeek-R1 and the newly launched DeepSeek-V3 offer greater freedom and cost savings, but demand technical know-how and deeper oversight.
For eCommerce teams and search-focused marketers, the choice has real consequences. And the decision can’t be made in isolation. Google’s algorithm updates, user intent shifts, and the flood of AI-generated content are making traditional SEO tactics harder to rely on. Businesses need AI strategies built for long-term outcomes, not shortcuts.
At Kia Ora Digital, we’ve helped hundreds of clients to manage this shift. We’ve seen what works and what breaks under pressure.
What Happens When AI-Driven SEO Goes Off Track?
AI has already disrupted how content is written and how it ranks. But jumping into it without a plan has backfired for many. Some of the most common traps include:
- Loss of content uniqueness – When everyone uses the same AI models, Google starts to detect patterns and downrank them.
- Over-reliance on third-party tools – Monthly fees stack up, and you lose control over how models behave or evolve.
- Opaque systems – Models like ChatGPT don’t explain how they produce answers. That means you can’t predict how they’ll perform in search.
- Search penalties for low-value content – Google has signalled that AI content is fine, as long as it’s genuinely helpful. Most generative content misses that mark.
The businesses we’ve worked with have avoided these traps by grounding their SEO strategy in quality, originality, and long-term trends, with AI serving the strategy, not dictating it.
DeepSeek-R1: An Open-Source Alternative
DeepSeek-R1 offers something very few language models do: full access and control.
Built by Chinese AI startup DeepSeek, R1 has proven it can hold its own in high-reasoning tasks – from complex code generation to long-form logic. So why are people paying attention?
- No black boxes – It’s open-source, so the model can be reviewed, modified, and tested in real environments.
- No subscription walls – Businesses can run the model locally and avoid rising cloud platform fees.
- Higher content precision – With more control comes better fine-tuning. You can shape how the model writes, and ensure it meets quality benchmarks.
- SEO edge – Unlike off-the-shelf solutions, DeepSeek-R1 gives experienced marketers a way to create content that doesn’t look or sound like everyone else’s.
These factors make it more than a cost-cutting tool – it’s a strategic play for teams that want ownership over their content production stack.
What This Means for SEO-Driven Businesses
DeepSeek’s rise is about more than speed and cost. It’s a sign that SEO is entering a new phase – one shaped by model performance, control, and the ability to respond quickly to search algorithm changes.
How Kia Ora Digital Approaches AI and SEO
- Custom AI Strategies for eCommerce SEO – We specialise in optimising eCommerce websites for search, ensuring that AI-generated content aligns with best practices.
- Revenue Forecasting for AI-Driven SEO – Understanding the financial impact of AI-driven search strategies is crucial. Our revenue forecasting tool helps businesses to measure the ROI of AI-powered SEO efforts.
- AI-Powered Content Optimisation – We analyse how different AI models, including DeepSeek-R1, can be integrated into content strategies to ensure high engagement and ranking potential.
- Avoiding SEO Pitfalls of AI-Generated Content – Not all AI-generated content is created equal. We help businesses navigate the challenges of AI-driven content production, ensuring that their strategies remain aligned with Google’s evolving search policies.
We’re now testing DeepSeek-V3 internally and exploring how it can support long-form content, search analysis, and keyword testing at scale. It’s not a silver bullet – but for the right teams, it’s a powerful option.
What You Should Be Doing Next
Search is shifting. Google is leaning harder into AI. Closed systems are getting more expensive. The open-source movement is gaining speed. Here’s what you should be doing now:
- Review how your content is being produced. Is it distinctive, accurate, and valuable to the user?
- Consider the risks of relying on closed AI systems. Can you afford to lose control?
- Explore local deployment of AI tools, especially if you handle sensitive data or need custom workflows.
- Talk to partners who’ve already made these transitions. The difference between a working strategy and a failed one is often just experience.
DeepSeek’s Future: R2 and the Challenge to GPT-5
DeepSeek is expected to release R2 – a reasoning-focused version of V3 – as early as May 2025. If it lives up to R1’s benchmark, it may become a true rival to GPT-5 before it even ships.
But serious questions remain. DeepSeek’s rise has been clouded by data security issues, censorship flags, and questions over whether it used OpenAI’s outputs to train its own models. Governments in Australia, Italy, and potentially the US are considering bans on public sector use. Privacy policies are vague, and a publicised security breach exposed serious holes in its early infrastructure.
For businesses operating in regulated sectors, this is a problem. Running these models locally can help, but it adds complexity.
The bigger picture is clear, though. Open-source AI is accelerating. It’s lowering the cost of entry. It’s creating space for smaller players to compete. And it’s forcing legacy vendors to rethink their assumptions.
The future of search won’t be written by any one company – not OpenAI, not Google, and not DeepSeek. It will be shaped by how businesses use these tools to build content that serves real people with real questions.
AI is just the engine. You still have to steer.
Want help building a search strategy that works with, not against, AI? Find out how we can help your business stay ahead. Say Kia Ora and get in touch with us today.