| Signal | Qwen3 30B A3B Thinking 2507 | Delta | MiMo-V2-Pro |
|---|---|---|---|
Capabilities | 67 | -- | |
Pricing | 0 | -3 | |
Context window size | 81 | -14 | |
Recency | 93 | -7 | |
Output Capacity | 85 | -- | |
Benchmarks | 0 | -73 | |
| Overall Result | 0 wins | of 6 | 4 wins |
0
days higher
0
days
30
days higher
Alibaba
Xiaomi
Qwen3 30B A3B Thinking 2507 saves you $222.00/month
That's $2664.00/year compared to MiMo-V2-Pro at your current usage level of 100K calls/month.
| Metric | Qwen3 30B A3B Thinking 2507 | MiMo-V2-Pro | Winner |
|---|---|---|---|
| Overall Score | 40 | 74 | MiMo-V2-Pro |
| Rank | #204 | #49 | MiMo-V2-Pro |
| Quality Rank | #204 | #49 | MiMo-V2-Pro |
| Adoption Rank | #204 | #49 | MiMo-V2-Pro |
| Parameters | 30B | -- | -- |
| Context Window | 131K | 1049K | MiMo-V2-Pro |
| Pricing | $0.08/$0.40/M | $1.00/$3.00/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 67 | Qwen3 30B A3B Thinking 2507 |
| Pricing | 0 | 3 | MiMo-V2-Pro |
| Context window size | 81 | 96 | MiMo-V2-Pro |
| Recency | 93 | 100 | MiMo-V2-Pro |
| Output Capacity | 85 | 85 | Qwen3 30B A3B Thinking 2507 |
| Benchmarks | -- | 73 | 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%). Here's what the scores mean for these two models:
Scores 40/100 (rank #204), placing it in the top 30% of all 290 models tracked.
Scores 74/100 (rank #49), placing it in the top 83% of all 290 models tracked.
MiMo-V2-Pro has a 34-point advantage, which typically translates to noticeably stronger performance on complex reasoning, code generation, and multi-step tasks.
Qwen3 30B A3B Thinking 2507 offers 88% better value per quality point. At 1M tokens/day, you'd spend $7.20/month with Qwen3 30B A3B Thinking 2507 vs $60.00/month with MiMo-V2-Pro - a $52.80 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. Qwen3 30B A3B Thinking 2507 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 ($0.40/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (74/100) correlates with better nuance, coherence, and style in long-form content
MiMo-V2-Pro clearly outperforms Qwen3 30B A3B Thinking 2507 with a significant 33.5-point lead. For most general use cases, MiMo-V2-Pro is the stronger choice. However, Qwen3 30B A3B Thinking 2507 may still excel in niche scenarios.
Best for Quality
Qwen3 30B A3B Thinking 2507
Marginally better benchmark scores; both are excellent
Best for Cost
Qwen3 30B A3B Thinking 2507
88% lower pricing; better value at scale
Best for Reliability
Qwen3 30B A3B Thinking 2507
Higher uptime and faster response speeds
Best for Prototyping
Qwen3 30B A3B Thinking 2507
Stronger community support and better developer experience
Best for Production
Qwen3 30B A3B Thinking 2507
Wider enterprise adoption and proven at scale
by Alibaba
| Capability | Qwen3 30B A3B Thinking 2507 | MiMo-V2-Pro |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
Alibaba
Xiaomi
Qwen3 30B A3B Thinking 2507 saves you $4.78/month
That's 88% 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 | Qwen3 30B A3B Thinking 2507 | MiMo-V2-Pro |
|---|---|---|
| Context Window | 131K | 1.0M |
| Max Output Tokens | 131,072 | 131,072 |
| Open Source | Yes | No |
| Created | Aug 28, 2025 | Mar 18, 2026 |
MiMo-V2-Pro scores 74/100 (rank #49) compared to Qwen3 30B A3B Thinking 2507's 40/100 (rank #204), giving it a 34-point advantage. MiMo-V2-Pro is the stronger overall choice, though Qwen3 30B A3B Thinking 2507 may excel in specific areas like cost efficiency.
Qwen3 30B A3B Thinking 2507 is ranked #204 and MiMo-V2-Pro is ranked #49 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.
Qwen3 30B A3B Thinking 2507 is cheaper at $0.40/M output tokens vs MiMo-V2-Pro's $3.00/M output tokens - 7.5x more expensive. Input token pricing: Qwen3 30B A3B Thinking 2507 at $0.08/M vs MiMo-V2-Pro at $1.00/M.
MiMo-V2-Pro has a larger context window of 1,048,576 tokens compared to Qwen3 30B A3B Thinking 2507's 131,072 tokens. A larger context window means the model can process longer documents and conversations.