| Signal | MiniMax M2 | Delta | GLM 4.7 |
|---|---|---|---|
Capabilities | 67 | -- | |
Benchmarks | 72 | -- | |
Pricing | 99 | +1 | |
Context window size | 76 | +0 | |
Recency | 88 | -11 | |
Output Capacity | 88 | +3 | |
| Overall Result | 3 wins | of 6 | 1 wins |
Score History
71.6
current score
GLM 4.7
right now
72.3
current score
MiniMax
Zhipu AI
MiniMax M2 saves you $52.00/month
That's $624.00/year compared to GLM 4.7 at your current usage level of 100K calls/month.
| Metric | MiniMax M2 | GLM 4.7 | Winner |
|---|---|---|---|
| Overall Score | 72 | 72 | GLM 4.7 |
| Rank | #82 | #81 | GLM 4.7 |
| Quality Rank | #82 | #81 | GLM 4.7 |
| Adoption Rank | #82 | #81 | GLM 4.7 |
| Parameters | -- | -- | -- |
| Context Window | 205K | 203K | MiniMax M2 |
| Pricing | $0.26/$1.00/M | $0.40/$1.75/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 67 | MiniMax M2 |
| Benchmarks | 72 | 72 | MiniMax M2 |
| Pricing | 99 | 98 | MiniMax M2 |
| Context window size | 76 | 76 | MiniMax M2 |
| Recency | 88 | 99 | GLM 4.7 |
| Output Capacity | 88 | 85 | MiniMax M2 |
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 72/100 (rank #82), placing it in the top 72% of all 290 models tracked.
Scores 72/100 (rank #81), placing it in the top 72% of all 290 models tracked.
With only a 1-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.
MiniMax M2 offers 42% better value per quality point. At 1M tokens/day, you'd spend $18.82/month with MiniMax M2 vs $32.25/month with GLM 4.7 - a $13.43 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. MiniMax M2 also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (205K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($1.00/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
MiniMax M2 and GLM 4.7 are extremely close in overall performance (only 0.7000000000000028 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
Best for Quality
MiniMax M2
Marginally better benchmark scores; both are excellent
Best for Cost
MiniMax M2
42% lower pricing; better value at scale
Best for Reliability
MiniMax M2
Higher uptime and faster response speeds
Best for Prototyping
MiniMax M2
Stronger community support and better developer experience
Best for Production
MiniMax M2
Wider enterprise adoption and proven at scale
by MiniMax
| Capability | MiniMax M2 | GLM 4.7 |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
MiniMax
Zhipu AI
MiniMax M2 saves you $1.16/month
That's 41% cheaper than GLM 4.7 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 | MiniMax M2 | GLM 4.7 |
|---|---|---|
| Context Window | 205K | 203K |
| Max Output Tokens | 196,608 | 131,072 |
| Open Source | Yes | Yes |
| Created | Oct 23, 2025 | Dec 22, 2025 |