Model Comparison
M2.1
vs. Qwen3.5 122B A10B (Reasoning)
Comparing 2 AI models · 10 benchmarks · MiniMax, Alibaba
Recommended Pick
Al Qwen3.5 122B A10B (Reasoning) 11 metric wins Strongest on: TTFT, Latency, Intelligence
Best Value
M2.1
100.0 value score
62.0 reasoning / $0.52/1M
Lowest Price
M2.1
$0.30/1M input price
Best Reasoning
M2.1
62.0 reasoning score
Blends available reasoning benchmarks
Best for Coding
Qwen3.5 122B A10B (Reasoning)
34.7 coding index
Composite Indices
Higher is better; speed and price are normalized
Standard Benchmarks
Only benchmarks with data are shown
Differences That Matter
Best value
M2.1 has the strongest quality-to-price mix at 100.0 out of 100 value points.
Price gap
M2.1 is 1.3x cheaper on input tokens than Qwen3.5 122B A10B (Reasoning).
Speed gap
M2.1 generates about 1.2x as many tokens per second as Qwen3.5 122B A10B (Reasoning).
Reasoning gap
M2.1 leads Qwen3.5 122B A10B (Reasoning) by 11.8 points on reasoning.
Coding gap
Qwen3.5 122B A10B (Reasoning) leads M2.1 by 1.9 points on coding.
Response Face-Off
Run one prompt through the selected models and compare response quality with live speed and cost context.
M2.1
MiniMax
TTFT
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Time
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tok/s
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Tokens
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Cost
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Qwen3.5 122B A10B (Reasoning)
Alibaba
TTFT
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Time
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tok/s
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Tokens
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Cost
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Which answer was more useful?
Full Comparison
| Metric | Mi M2.1 | Top Pick Al Qwen3.5 122B A10B (Reasoning) |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $0.30/1M | $0.40/1M |
| Output Cost | $1.20/1M | $3.20/1M |
| Blended (3:1) | $0.52/1M | $1.10/1M |
| Specifications | ||
| Organization | MiniMax | Alibaba |
| Release Date | Dec 23, 2025 | Feb 24, 2026 |
| Performance & Speed | ||
| Throughput | 175.2 tok/s | 146.1 tok/s |
| TTFT | 8562ms | 1172ms |
| Latency | 19975ms | 14866ms |
| Composite Indices | ||
| Value Score | 100.0 | 38.7 |
| Reasoning Score | 62.0 | 50.2 |
| Intelligence | 39.4 | 41.6 |
| Coding | 32.8 | 34.7 |
| Math | 82.7 | — |
| Standard Benchmarks | ||
| GPQA | 83.0% | 85.7% |
| MMLU Pro | 87.5% | — |
| HLE | 22.2% | 23.4% |
| LiveCodeBench | 81.0% | — |
| AIME 2025 | 82.7% | — |
| SciCode | 40.7% | 42.0% |
| LCR | 59.0% | 66.7% |
| IFBench | 69.9% | 75.7% |
| TAU-bench v2 | 85.4% | 93.6% |
| TerminalBench Hard | 28.8% | 31.1% |
Key Takeaways
M2.1 offers the best value at $0.30/1M, making it ideal for high-volume applications and cost-conscious projects.
M2.1 has the strongest reasoning profile with a 62.0 reasoning score, combining the available reasoning-heavy benchmarks.
Qwen3.5 122B A10B (Reasoning) reaches a 34.7 coding index, making it the top choice for software development and code generation tasks.
All models support context windows of ∞+ tokens, suitable for processing lengthy documents and maintaining extended conversations.
When to Choose Each Model
M2.1
- Cost-sensitive applications
- High-volume processing
- Complex reasoning tasks
- Research & analysis
Qwen3.5 122B A10B (Reasoning)
- Code generation
- Software development
