| Signal | Gemini 2.5 Pro | Delta | R1 0528 |
|---|---|---|---|
Capabilities | 83 | +17 | |
Benchmarks | 80 | -1 | |
Pricing | 90 | -8 | |
Context window size | 96 | +13 | |
Recency | 80 | +4 | |
Output Capacity | 80 | -- | |
| Overall Result | 3 wins | of 6 | 2 wins |
Score History
80.5
current score
Gemini 2.5 Pro
right now
79.7
current score
DeepSeek
R1 0528 saves you $472.50/month
That's $5670.00/year compared to Gemini 2.5 Pro at your current usage level of 100K calls/month.
| Metric | Gemini 2.5 Pro | R1 0528 | Winner |
|---|---|---|---|
| Overall Score | 81 | 80 | Gemini 2.5 Pro |
| Rank | #21 | #23 | Gemini 2.5 Pro |
| Quality Rank | #21 | #23 | Gemini 2.5 Pro |
| Adoption Rank | #21 | #23 | Gemini 2.5 Pro |
| Parameters | -- | -- | -- |
| Context Window | 1049K | 164K | Gemini 2.5 Pro |
| Pricing | $1.25/$10.00/M | $0.45/$2.15/M | -- |
| Signal Scores | |||
| Capabilities | 83 | 67 | Gemini 2.5 Pro |
| Benchmarks | 80 | 80 | R1 0528 |
| Pricing | 90 | 98 | R1 0528 |
| Context window size | 96 | 83 | Gemini 2.5 Pro |
| Recency | 80 | 76 | Gemini 2.5 Pro |
| Output Capacity | 80 | 80 | Gemini 2.5 Pro |
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%). Here's what the scores mean for these two models:
Scores 81/100 (rank #21), placing it in the top 93% of all 290 models tracked.
Scores 80/100 (rank #23), placing it in the top 92% 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 0528 offers 77% better value per quality point. At 1M tokens/day, you'd spend $39.00/month with R1 0528 vs $168.75/month with Gemini 2.5 Pro - a $129.75 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 0528 also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (1049K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($2.15/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (81/100) 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
Gemini 2.5 Pro and R1 0528 are extremely close in overall performance (only 0.7999999999999972 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
Gemini 2.5 Pro
Marginally better benchmark scores; both are excellent
Best for Cost
R1 0528
77% lower pricing; better value at scale
Best for Reliability
Gemini 2.5 Pro
Higher uptime and faster response speeds
Best for Prototyping
Gemini 2.5 Pro
Stronger community support and better developer experience
Best for Production
Gemini 2.5 Pro
Wider enterprise adoption and proven at scale
by Google
| Capability | Gemini 2.5 Pro | R1 0528 |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
DeepSeek
R1 0528 saves you $10.86/month
That's 76% cheaper than Gemini 2.5 Pro 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 | Gemini 2.5 Pro | R1 0528 |
|---|---|---|
| Context Window | 1.0M | 164K |
| Max Output Tokens | 65,536 | 65,536 |
| Open Source | No | Yes |
| Created | Jun 17, 2025 | May 28, 2025 |
Gemini 2.5 Pro scores 81/100 (rank #21) compared to R1 0528's 80/100 (rank #23), giving it a 1-point advantage. Gemini 2.5 Pro is the stronger overall choice, though R1 0528 may excel in specific areas like cost efficiency.
Gemini 2.5 Pro is ranked #21 and R1 0528 is ranked #23 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 0528 is cheaper at $2.15/M output tokens vs Gemini 2.5 Pro's $10.00/M output tokens - 4.7x more expensive. Input token pricing: Gemini 2.5 Pro at $1.25/M vs R1 0528 at $0.45/M.
Gemini 2.5 Pro has a larger context window of 1,048,576 tokens compared to R1 0528's 163,840 tokens. A larger context window means the model can process longer documents and conversations.