| Signal | o4 Mini High | Delta | R1 |
|---|---|---|---|
Capabilities | 100 | +50 | |
Benchmarks | 70 | -3 | |
Pricing | 96 | -2 | |
Context window size | 84 | +8 | |
Recency | 68 | +16 | |
Output Capacity | 83 | +13 | |
| Overall Result | 4 wins | of 6 | 2 wins |
Score History
72.1
current score
R1
right now
73
current score
OpenAI
DeepSeek
R1 saves you $135.00/month
That's $1620.00/year compared to o4 Mini High at your current usage level of 100K calls/month.
| Metric | o4 Mini High | R1 | Winner |
|---|---|---|---|
| Overall Score | 72 | 73 | R1 |
| Rank | #63 | #58 | R1 |
| Quality Rank | #63 | #58 | R1 |
| Adoption Rank | #63 | #58 | R1 |
| Parameters | -- | -- | -- |
| Context Window | 200K | 64K | o4 Mini High |
| Pricing | $1.10/$4.40/M | $0.70/$2.50/M | -- |
| Signal Scores | |||
| Capabilities | 100 | 50 | o4 Mini High |
| Benchmarks | 70 | 73 | R1 |
| Pricing | 96 | 98 | R1 |
| Context window size | 84 | 76 | o4 Mini High |
| Recency | 68 | 53 | o4 Mini High |
| Output Capacity | 83 | 70 | o4 Mini High |
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 72/100 (rank #63), placing it in the top 79% of all 290 models tracked.
Scores 73/100 (rank #58), placing it in the top 80% of all 290 models tracked.
With only a 1-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.
R1 offers 42% better value per quality point. At 1M tokens/day, you'd spend $48.00/month with R1 vs $82.50/month with o4 Mini High - a $34.50 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
Higher benchmark score (0/100) indicates stronger performance on coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Faster response time (speed score 0/100) is critical for user-facing chat. 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 (73/100) 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
o4 Mini High and R1 are extremely close in overall performance (only 0.9000000000000057 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
o4 Mini High
Marginally better benchmark scores; both are excellent
Best for Cost
R1
42% lower pricing; better value at scale
Best for Reliability
o4 Mini High
Higher uptime and faster response speeds
Best for Prototyping
o4 Mini High
Stronger community support and better developer experience
Best for Production
o4 Mini High
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | o4 Mini High | R1 |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoning | ||
| Web Searchdiffers | ||
| Image Output |
OpenAI
DeepSeek
R1 saves you $3.00/month
That's 41% cheaper than o4 Mini High 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 | o4 Mini High | R1 |
|---|---|---|
| Context Window | 200K | 64K |
| Max Output Tokens | 100,000 | 16,000 |
| Open Source | No | Yes |
| Created | Apr 16, 2025 | Jan 20, 2025 |
R1 scores 73/100 (rank #58) compared to o4 Mini High's 72/100 (rank #63), giving it a 1-point advantage. R1 is the stronger overall choice, though o4 Mini High may excel in specific areas like certain benchmarks.
o4 Mini High is ranked #63 and R1 is ranked #58 out of 290+ AI models. Rankings use a composite score combining benchmark performance (90%) from MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations, with capabilities and context window as tiebreakers (10%). Scores update hourly.
R1 is cheaper at $2.50/M output tokens vs o4 Mini High's $4.40/M output tokens - 1.8x more expensive. Input token pricing: o4 Mini High at $1.10/M vs R1 at $0.70/M.
o4 Mini High has a larger context window of 200,000 tokens compared to R1's 64,000 tokens. A larger context window means the model can process longer documents and conversations.