| Signal | Anthropic Claude Sonnet Latest | Delta | MiMo-V2.5 |
|---|---|---|---|
Capabilities | 100 | +17 | |
Pricing | 85 | -15 | |
Context window size | 86 | 0 | |
Recency | 100 | -- | |
Output Capacity | 85 | +65 | |
Benchmarks | 0 | -71 | |
| Overall Result | 2 wins | of 6 | 3 wins |
Score History
40
current score
MiMo-V2.5
right now
72.4
current score
~anthropic
Xiaomi
MiMo-V2.5 saves you $1025.50/month
That's $12306.00/year compared to Anthropic Claude Sonnet Latest at your current usage level of 100K calls/month.
| Metric | Anthropic Claude Sonnet Latest | MiMo-V2.5 | Winner |
|---|---|---|---|
| Overall Score | 40 | 72 | MiMo-V2.5 |
| Rank | #193 | #80 | MiMo-V2.5 |
| Quality Rank | #193 | #80 | MiMo-V2.5 |
| Adoption Rank | #193 | #80 | MiMo-V2.5 |
| Parameters | -- | -- | -- |
| Context Window | 1000K | 1049K | MiMo-V2.5 |
| Pricing | $3.00/$15.00/M | $0.10/$0.28/M | -- |
| Signal Scores | |||
| Capabilities | 100 | 83 | Anthropic Claude Sonnet Latest |
| Pricing | 85 | 100 | MiMo-V2.5 |
| Context window size | 86 | 86 | MiMo-V2.5 |
| Recency | 100 | 100 | Anthropic Claude Sonnet Latest |
| Output Capacity | 85 | 20 | Anthropic Claude Sonnet Latest |
| Benchmarks | -- | 71 | MiMo-V2.5 |
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 40/100 (rank #193), placing it in the top 34% of all 290 models tracked.
Scores 72/100 (rank #80), placing it in the top 73% of all 290 models tracked.
MiMo-V2.5 has a 32-point advantage, which typically translates to noticeably stronger performance on complex reasoning, code generation, and multi-step tasks.
MiMo-V2.5 offers 98% better value per quality point. At 1M tokens/day, you'd spend $5.78/month with MiMo-V2.5 vs $270.00/month with Anthropic Claude Sonnet Latest - a $264.23 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. MiMo-V2.5 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 ($0.28/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (72/100) 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
MiMo-V2.5 clearly outperforms Anthropic Claude Sonnet Latest with a significant 32.400000000000006-point lead. For most general use cases, MiMo-V2.5 is the stronger choice. However, Anthropic Claude Sonnet Latest may still excel in niche scenarios.
Best for Quality
Anthropic Claude Sonnet Latest
Marginally better benchmark scores; both are excellent
Best for Cost
MiMo-V2.5
98% lower pricing; better value at scale
Best for Reliability
Anthropic Claude Sonnet Latest
Higher uptime and faster response speeds
Best for Prototyping
Anthropic Claude Sonnet Latest
Stronger community support and better developer experience
Best for Production
Anthropic Claude Sonnet Latest
Wider enterprise adoption and proven at scale
by ~anthropic
| Capability | Anthropic Claude Sonnet Latest | MiMo-V2.5 |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Searchdiffers | ||
| Image Output |
~anthropic
Xiaomi
MiMo-V2.5 saves you $22.88/month
That's 98% cheaper than Anthropic Claude Sonnet Latest 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 | Anthropic Claude Sonnet Latest | MiMo-V2.5 |
|---|---|---|
| Context Window | 1M | 1.0M |
| Max Output Tokens | 128,000 | -- |
| Open Source | No | Yes |
| Created | Apr 27, 2026 | Apr 22, 2026 |
The $15/M output pricing reflects Claude's proprietary architecture and web search capability, which MiMo-V2.5 lacks despite supporting more input modalities (audio/video). For production coding workloads, Claude's #6 ranking versus MiMo's #29 position represents a 23-rank reliability gap that justifies the premium for mission-critical applications.
Claude's 66/100 score and web search capability make it superior for real-time documentation lookups and API integration tasks, worth the $3/M input cost. MiMo-V2.5's audio/video processing is irrelevant for pure coding workflows, and its 62/100 score indicates it will require more prompt engineering to achieve similar code quality.
The 2.3% output difference is negligible - both models can generate entire codebases in a single response. The real differentiator is Claude's web search enabling dynamic package version checking and Stack Overflow integration, which matters more than MiMo's extra 3K tokens for practical development.
Self-hosting MiMo-V2.5 could save $1,500/month in output costs alone (100M tokens at $15/M vs $2/M), but requires GPU infrastructure. Claude's managed service includes the web search capability and consistent #6 performance without DevOps overhead, making it cost-effective for teams under 5 engineers despite the 7.5x markup.
MiMo's video input could analyze screencasts or debug UI issues at $0.40/M input versus Claude's $3/M, a 7.5x savings for visual debugging scenarios. However, the 62 vs 66 score gap means you're trading code generation quality for multimodal features that most IDEs handle better natively.