o4-mini vs DeepSeek-R1
OpenAI's o4-mini against DeepSeek's DeepSeek-R1 — pricing, benchmarks, context, and best use cases compared side by side.
DeepSeek-R1 leads on quality (Elo 1360 vs 1350) and is also 50% cheaper — a clear value winner. o4-mini offers a larger context window (200K vs 64K).
| Input Price | $1.10/1M | $0.55/1M |
| Output Price | $4.40/1M | $2.19/1M |
| Blended Price | $2.75/1M | $1.37/1M |
| LMSYS Elo | 1350 | 1360 |
| Context Window | 200,000 | 64,000 |
| Provider | OpenAI | DeepSeek |
Pricing breakdown
When comparing LLM API pricing, DeepSeek-R1 charges $0.55 per 1M input tokens compared to o4-mini's $1.10 — a 50% difference. For output tokens, DeepSeek-R1 costs $2.19/1M versus $4.40/1M for o4-mini. On a blended basis (averaging input and output), DeepSeek-R1 comes in at $1.37/1M tokens versus $2.75/1M for o4-mini.
Quality & benchmarks
On the LMSYS Chatbot Arena leaderboard — a crowd-sourced benchmark based on blind human preference voting — DeepSeek-R1 scores 1360 Elo compared to o4-mini's 1350, a 10-point advantage. While DeepSeek-R1 has the edge, both models are competitive. DeepSeek-R1 excels at cost-effective reasoning, self-hosted deployments, and math/code tasks, while o4-mini is well-suited for cost-effective reasoning, coding assistance, and structured problem-solving.
Context window comparison
o4-mini 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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