The Broad Channel Intelligence Group's analysis comparing the cost, performance, and geopolitical implications of OpenAI's o1, DeepSeek's R1, and Google's Gemini 2.5.
The enterprise AI market is fracturing along geopolitical and economic lines. OpenAI’s o1 model set the gold standard for reasoning AI, proving that an AI could solve problems at a PhD level. But it came at a premium price.
Now, a Chinese startup named DeepSeek has released R1—a model that matches o1‘s performance in key benchmarks but costs a fraction to run. It achieves this by being optimized exclusively for Chinese-made chips, a direct consequence of U.S. export controls.zignuts+1
For enterprises, this creates a “$20 billion question”: Do you standardize on the premium, U.S.-based o1, or do you embrace the cost revolution offered by the open-source, Chinese-backed R1? This analysis breaks down the choice that will define enterprise AI strategy for the next two years.
The most shocking thing about DeepSeek R1 is not just its price, but how close it comes to o1‘s performance.
| Model | AIME Math Score | Codeforces Ranking | Cost (per 1M input tokens) |
|---|---|---|---|
| OpenAI o1 | ~79-83% | ~89-96th percentile | $15.00 zignuts+1 |
| DeepSeek R1 | ~79% | ~87-96th percentile | $0.55 zignuts+2 |
| Gemini 2.5 Pro | 82% | 85th percentile | $0.075 (Flash version) |
Note: Benchmarks vary slightly between sources, but the trend is clear.
The Takeaway:
DeepSeek R1 offers roughly 95% of OpenAI o1‘s reasoning capability for less than 4% of the cost. This isn’t just a discount; it’s a complete disruption of the AI cost structure. The only model that competes on price is Google’s Gemini 2.5 Flash, which is designed for speed and multimodality, not deep reasoning.meetcody
Expert Quote: “DeepSeek didn’t just build a cheaper model; they proved that world-class AI doesn’t have to depend on NVIDIA’s hardware. They turned a geopolitical constraint into a massive economic advantage.”
DeepSeek R1 is a direct product of the U.S. export controls designed to slow China’s AI progress. Barred from using NVIDIA’s top-tier chips, Chinese firms were forced to innovate on their own hardware, like that from Huawei.
DeepSeek’s masterstroke was optimizing R1 for this alternate chip ecosystem. This creates a critical dilemma for global enterprises:
This decision has massive financial implications. Our analysis shows a company spending $5 million per year on o1‘s API could achieve similar results with DeepSeek R1 for less than $200,000.
There is no single right answer. The choice depends entirely on your organization’s priorities.
You Should Choose OpenAI o1 If:
You Should Choose DeepSeek R1 If:
You Should Choose Gemini 2.5 If:
The release of DeepSeek R1 has irrevocably broken the AI pricing cartel that was forming around a few U.S.-based companies. This will trigger a series of cascading effects over the next 24 months.
R1 that they can control and run on their own infrastructure. For more on this, see our guide to AI Governance Policy Frameworks.R1 will likely trigger a new round of, and more targeted, U.S. export controls aimed at slowing China’s progress in AI software and algorithms, not just hardware.DeepSeek R1 is more than just a new model; it’s a market correction. It proves that reasoning performance is becoming a commodity and that cost efficiency is the new competitive frontier.
For CIOs and enterprise strategists, the recommendation is clear: do not standardize on a single model.
o1, R1, and Gemini 2.5—on non-critical workloads to benchmark their real-world performance for your specific use cases.o1 for your most critical, cutting-edge research; use Gemini for multimodal tasks; and use DeepSeek R1 for the 80% of problems where “good enough” reasoning at a fraction of the cost is the smarter business decision.The companies that master this multi-model approach will out-compete those who lock themselves into a single, expensive ecosystem. To learn more about the landscape of AI, explore our guide to the best AI tools.
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