| Signal | GPT-4o | Delta | R1 |
|---|---|---|---|
Capabilities | 67 | +17 | |
Benchmarks | 82 | +5 | |
Pricing | 10 | +8 | |
Context window size | 81 | +5 | |
Recency | 9 | -46 | |
Output Capacity | 70 | +0 | |
| Overall Result | 5 wins | of 6 | 1 wins |
3
days ranked higher
0
days
27
days ranked higher
OpenAI
DeepSeek
R1 saves you $555.00/month
That's $6660.00/year compared to GPT-4o at your current usage level of 100K calls/month.
| Metric | GPT-4o | R1 | Winner |
|---|---|---|---|
| Overall Score | 64 | 68 | R1 |
| Rank | #193 | #167 | R1 |
| Quality Rank | #193 | #167 | R1 |
| Adoption Rank | #193 | #167 | R1 |
| Parameters | -- | -- | -- |
| Context Window | 128K | 64K | GPT-4o |
| Pricing | $2.50/$10.00/M | $0.70/$2.50/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 50 | GPT-4o |
| Benchmarks | 82 | 77 | GPT-4o |
| Pricing | 10 | 3 | GPT-4o |
| Context window size | 81 | 76 | GPT-4o |
| Recency | 9 | 55 | R1 |
| Output Capacity | 70 | 70 | GPT-4o |
Our composite score (0–100) combines six weighted signals: benchmark performance (25%), pricing efficiency (25%), context window size (15%), model recency (15%), output capacity (10%), and capability versatility (10%). Here's what the scores mean for these two models:
Scores 64/100 (rank #193), placing it in the top 34% of all 290 models tracked.
Scores 68/100 (rank #167), placing it in the top 43% of all 290 models tracked.
With only a 4-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 74% better value per quality point. At 1M tokens/day, you'd spend $48.00/month with R1 vs $187.50/month with GPT-4o - a $139.50 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 (128K 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 (68/100) 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
R1 has a moderate advantage with a 4-point lead in composite score. It wins on more signal dimensions, but GPT-4o has specific strengths that could make it the better choice for certain workflows.
Best for Quality
GPT-4o
Marginally better benchmark scores; both are excellent
Best for Cost
R1
74% lower pricing; better value at scale
Best for Reliability
GPT-4o
Higher uptime and faster response speeds
Best for Prototyping
GPT-4o
Stronger community support and better developer experience
Best for Production
GPT-4o
Wider enterprise adoption and proven at scale
by OpenAI
| Capability | GPT-4o | R1 |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
OpenAI
DeepSeek
R1 saves you $12.24/month
That's 74% cheaper than GPT-4o 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 | GPT-4o | R1 |
|---|---|---|
| Context Window | 128K | 64K |
| Max Output Tokens | 16,384 | 16,000 |
| Open Source | No | Yes |
| Created | May 13, 2024 | Jan 20, 2025 |
R1 scores 68/100 (rank #167) compared to GPT-4o's 64/100 (rank #193), giving it a 4-point advantage. R1 is the stronger overall choice, though GPT-4o may excel in specific areas like certain benchmarks.
GPT-4o is ranked #193 and R1 is ranked #167 out of 290+ AI models. Rankings use a composite score combining benchmark performance (25%), pricing (25%), context window (15%), recency (15%), output capacity (10%), and versatility (10%). Scores update hourly.
R1 is cheaper at $2.50/M output tokens vs GPT-4o's $10.00/M output tokens - 4.0x more expensive. Input token pricing: GPT-4o at $2.50/M vs R1 at $0.70/M.
GPT-4o has a larger context window of 128,000 tokens compared to R1's 64,000 tokens. A larger context window means the model can process longer documents and conversations.