Capability · Comparison
DeepSeek R1 vs OpenAI o1
DeepSeek R1 is the open-weight reasoning model that shocked the industry in early 2025 by matching OpenAI o1-class performance at a fraction of the cost. Two years later, with both models still in active use, the comparison is essentially open-vs-closed: R1 for self-hosted deliberation, o1 for managed deliberation on OpenAI's platform.
Side-by-side
| Criterion | DeepSeek R1 | OpenAI o1 |
|---|---|---|
| License | MIT (open weights) | Closed, API-only |
| Self-hosting | Yes — vLLM, SGLang, TGI | No |
| Context window | 128,000 tokens | 200,000 tokens |
| Math (AIME 2024) As published; both are in the same class. | ~79% | ~83% |
| Coding (Codeforces) | High Expert rating | Grandmaster rating |
| Pricing ($/M input) As of 2026-04; self-host cost depends on your GPUs. | $0.55 (DeepSeek API) | $15 |
| Pricing ($/M output) As of 2026-04; o1 counts reasoning tokens as output. | $2.19 | $60 |
| Multimodal | Text only | Text, vision |
| Distilled variants | R1-Distill (Qwen, Llama) openly available | Not available |
Verdict
DeepSeek R1 democratized test-time-compute reasoning — it's the reason reasoning-style models are now table stakes across the industry. For cost-sensitive or sovereignty-sensitive deployments R1 is the obvious choice, and the distilled 7B/14B/32B variants make edge deployment realistic. o1 remains the more polished product with better vision support and tighter ecosystem integration; for a managed, audit-friendly reasoning endpoint it still wins.
When to choose each
Choose DeepSeek R1 if…
- You want to self-host for cost, sovereignty, or air-gap reasons.
- You need an open-weight model you can fine-tune.
- You need R1-distilled smaller models for edge deployment.
- You're building on an open-weight stack (Llama, Qwen, etc.).
Choose OpenAI o1 if…
- You need vision reasoning, not text-only.
- You need a managed service with enterprise SSO, audit, and SLAs.
- You want first-party tooling (Responses API, structured outputs).
- You're already on OpenAI and consolidation matters.
Frequently asked questions
Is DeepSeek R1 really as good as o1?
On math and code reasoning, yes — they're in the same class. o1 is slightly ahead on the hardest competition benchmarks and has vision support. On text reasoning alone, R1 is broadly comparable.
Can I run R1 on my own hardware?
The full 671B MoE needs 8xH100 or similar. Distilled variants (Qwen-32B, Llama-70B) run on a single 80GB GPU or 2x consumer cards with quantization.
What about o3 or newer DeepSeek models?
o3 has surpassed both on hard benchmarks; DeepSeek's V3/R2 line continues to close the gap. This comparison is still useful as a historical and cost-reference baseline.
Sources
- DeepSeek-R1 paper — accessed 2026-04-20
- OpenAI — o1 model page — accessed 2026-04-20