| Signal | R1 | Delta | MiMo-V2-Pro |
|---|---|---|---|
Capabilities | 50 | -17 | |
Benchmarks | 73 | +1 | |
Pricing | 98 | +1 | |
Context window size | 76 | -19 | |
Recency | 53 | -47 | |
Output Capacity | 70 | -15 | |
| Overall Result | 2 wins | of 6 | 4 wins |
Score History
73
current score
MiMo-V2-Pro
right now
73.4
current score
DeepSeek
Xiaomi
R1 saves you $55.00/month
That's $660.00/year compared to MiMo-V2-Pro at your current usage level of 100K calls/month.
| Metric | R1 | MiMo-V2-Pro | Winner |
|---|---|---|---|
| Overall Score | 73 | 73 | MiMo-V2-Pro |
| Rank | #40 | #38 | MiMo-V2-Pro |
| Quality Rank | #40 | #38 | MiMo-V2-Pro |
| Adoption Rank | #40 | #38 | MiMo-V2-Pro |
| Parameters | -- | -- | -- |
| Context Window | 64K | 1049K | MiMo-V2-Pro |
| Pricing | $0.70/$2.50/M | $1.00/$3.00/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 67 | MiMo-V2-Pro |
| Benchmarks | 73 | 73 | R1 |
| Pricing | 98 | 97 | R1 |
| Context window size | 76 | 96 | MiMo-V2-Pro |
| Recency | 53 | 100 | MiMo-V2-Pro |
| Output Capacity | 70 | 85 | MiMo-V2-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%). Learn more about our methodology.
Scores 73/100 (rank #40), placing it in the top 87% of all 290 models tracked.
Scores 73/100 (rank #38), placing it in the top 87% 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.
R1 offers 20% better value per quality point. At 1M tokens/day, you'd spend $48.00/month with R1 vs $60.00/month with MiMo-V2-Pro - a $12.00 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
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 (1049K 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
R1 and MiMo-V2-Pro are extremely close in overall performance (only 0.4000000000000057 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
R1
Marginally better benchmark scores; both are excellent
Best for Cost
R1
20% lower pricing; better value at scale
Best for Reliability
R1
Higher uptime and faster response speeds
Best for Prototyping
R1
Stronger community support and better developer experience
Best for Production
R1
Wider enterprise adoption and proven at scale
by DeepSeek
| Capability | R1 | MiMo-V2-Pro |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
DeepSeek
Xiaomi
R1 saves you $1.14/month
That's 21% cheaper than MiMo-V2-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 | R1 | MiMo-V2-Pro |
|---|---|---|
| Context Window | 64K | 1.0M |
| Max Output Tokens | 16,000 | 131,072 |
| Open Source | Yes | No |
| Created | Jan 20, 2025 | Mar 18, 2026 |
MiMo-V2-Pro scores 73/100 (rank #38) compared to R1's 73/100 (rank #40), giving it a 0-point advantage. MiMo-V2-Pro is the stronger overall choice, though R1 may excel in specific areas like cost efficiency.
R1 is ranked #40 and MiMo-V2-Pro is ranked #38 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 MiMo-V2-Pro's $3.00/M output tokens - 1.2x more expensive. Input token pricing: R1 at $0.70/M vs MiMo-V2-Pro at $1.00/M.
MiMo-V2-Pro has a larger context window of 1,048,576 tokens compared to R1's 64,000 tokens. A larger context window means the model can process longer documents and conversations.