Model Comparison
V2-Chat
vs. M2
Comparing 2 AI models · 10 benchmarks · DeepSeek, MiniMax
Recommended Pick
De V2-Chat 4 metric wins Strongest on: Input price, Output price, TTFT
Lowest Price
V2-Chat
$0.00/1M input price
Best Reasoning
M2
56.6 reasoning score
Blends available reasoning benchmarks
Best for Coding
M2
29.2 coding index
Composite Indices
Higher is better; speed and price are normalized
Standard Benchmarks
Only benchmarks with data are shown
Differences That Matter
Price gap
V2-Chat is ∞x cheaper on input tokens than M2.
Reasoning gap
M2 leads V2-Chat by 47.5 points on reasoning.
Top-pick rationale
V2-Chat wins 4 measurable categories, including Input price, Output price, TTFT, Latency.
Response Face-Off
Run one prompt through the selected models and compare response quality with live speed and cost context.
V2-Chat
DeepSeek
TTFT
—
Time
—
tok/s
—
Tokens
—
Cost
—
M2
MiniMax
TTFT
—
Time
—
tok/s
—
Tokens
—
Cost
—
Which answer was more useful?
Full Comparison
| Metric | Top Pick De V2-Chat | Mi M2 |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $0.00/1M | $0.30/1M |
| Output Cost | $0.00/1M | $1.20/1M |
| Blended (3:1) | — | $0.52/1M |
| Specifications | ||
| Organization | DeepSeek | MiniMax |
| Release Date | May 6, 2024 | Oct 26, 2025 |
| Performance & Speed | ||
| Throughput | — | 125.3 tok/s |
| TTFT | — | 1025ms |
| Latency | — | 16992ms |
| Composite Indices | ||
| Value Score | — | 100.0 |
| Reasoning Score | 9.1 | 56.6 |
| Intelligence | 9.1 | 36.1 |
| Coding | — | 29.2 |
| Math | — | 78.3 |
| Standard Benchmarks | ||
| GPQA | — | 77.7% |
| MMLU Pro | — | 82.0% |
| HLE | — | 12.5% |
| LiveCodeBench | — | 82.6% |
| AIME 2025 | — | 78.3% |
| SciCode | — | 36.1% |
| LCR | — | 61.0% |
| IFBench | — | 72.3% |
| TAU-bench v2 | — | 86.8% |
| TerminalBench Hard | — | 25.8% |
Key Takeaways
V2-Chat offers the best value at $0.00/1M, making it ideal for high-volume applications and cost-conscious projects.
M2 has the strongest reasoning profile with a 56.6 reasoning score, combining the available reasoning-heavy benchmarks.
M2 reaches a 29.2 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
V2-Chat
- Cost-sensitive applications
- High-volume processing
M2
- Complex reasoning tasks
- Research & analysis
- Code generation
- Software development
