DeepSeek-R1 vs o3
DeepSeek's DeepSeek-R1 against OpenAI's o3 — pricing, benchmarks, context, and best use cases compared side by side.
o3 leads on quality (Elo 1380 vs 1360), while DeepSeek-R1 compensates with 73% lower pricing. o3 offers a larger context window (200K vs 64K).
| Input Price | $0.55/1M | $2.00/1M |
| Output Price | $2.19/1M | $8.00/1M |
| Blended Price | $1.37/1M | $5.00/1M |
| LMSYS Elo | 1360 | 1380 |
| Context Window | 64,000 | 200,000 |
| Provider | DeepSeek | OpenAI |
Pricing breakdown
When comparing LLM API pricing, DeepSeek-R1 charges $0.55 per 1M input tokens compared to o3's $2.00 — a 72% difference. For output tokens, DeepSeek-R1 costs $2.19/1M versus $8.00/1M for o3. On a blended basis (averaging input and output), DeepSeek-R1 comes in at $1.37/1M tokens versus $5.00/1M for o3.
Quality & benchmarks
On the LMSYS Chatbot Arena leaderboard — a crowd-sourced benchmark based on blind human preference voting — o3 scores 1380 Elo compared to DeepSeek-R1's 1360, a 20-point advantage. While o3 has the edge, both models are competitive. o3 excels at complex reasoning, math, science, and logic-heavy tasks, while DeepSeek-R1 is well-suited for cost-effective reasoning, self-hosted deployments, and math/code tasks.
Context window comparison
o3 provides a significantly larger context window at 200K tokens compared to DeepSeek-R1's 64K tokens — 3.1x more capacity for processing long documents, large codebases, or extended conversations.
Monthly cost estimate
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