o1 vs R1
| Signal | o1 | Delta | R1 |
|---|---|---|---|
Capabilities | 100 | +33 | |
Benchmarks | 77 | +3 | |
Pricing | 40 | -57 | |
Context window size | 76 | +1 | |
Recency | 29 | -6 | |
Output Capacity | 83 | +13 | |
| Overall Result | 4 wins | of 6 | 2 wins |
Score History
74
current score
o1
right now
73.7
current score
o1
OpenAI
R1
DeepSeek
R1 saves you $4305.00/month
That's $51660.00/year compared to o1 at your current usage level of 100K calls/month.
Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Learn more about our methodology.
Scores 74/100 (rank #75), placing it in the top 74% of all 290 models tracked.
Scores 74/100 (rank #76), placing it in the top 74% of all 290 models tracked.
With only a 0-point gap, these models are in the same performance tier. The practical difference in output quality is minimal - your choice should depend on pricing, latency requirements, and specific feature needs.
Choose o1 when you need:
- Multimodal workflows that require image understanding
- Step-by-step reasoning and chain-of-thought problem solving
Choose R1 when you need:
- High-volume production workloads where API costs must be minimized
- Step-by-step reasoning and chain-of-thought problem solving
- Self-hosted deployments where you need full control over the model
R1 offers 96% better value per quality point. At 1M tokens/day, you'd spend $48.00/month with R1 vs $1125.00/month with o1 - a $1077.00 monthly difference.
Both models have comparable response speeds. For most applications, the latency difference is negligible.
When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.
Code generation & review
Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Suitable for user-facing chat with competitive response times. R1 also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (200K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($2.50/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (74/100) correlates with better nuance, coherence, and style in long-form content
Image understanding & OCR
Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly
o1 and R1 are extremely close in overall performance (only 0.29999999999999716 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
By Use Case
Best for Quality
o1
Marginally better benchmark scores; both are excellent
Best for Cost
R1
96% lower pricing; better value at scale
Best for Reliability
o1
Higher uptime and faster response speeds
Best for Prototyping
o1
Stronger community support and better developer experience
Best for Production
o1
Wider enterprise adoption and proven at scale
by OpenAI
- Choose for Quality - Marginally better benchmark scores; both are excellent
- Choose for Reliability - Higher uptime and faster response speeds
- Choose for Prototyping - Stronger community support and better developer experience
- Choose for Production - Wider enterprise adoption and proven at scale
| Capability | o1 | R1 |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Searchdiffers | ||
| Image Output |
o1
OpenAI
R1
DeepSeek
R1 saves you $94.74/month
That's 96% cheaper than o1 at 1,000 tokens/request and 100 requests/day.
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | o1 | R1 |
|---|---|---|
| Context Window | 200K | 164K |
| Max Output Tokens | 100,000 | 16,000 |
| Open Source | No | Yes |
| Created | Dec 17, 2024 | Jan 20, 2025 |