MiniMax M2.7 vs GLM 4.6
| Signal | MiniMax M2.7 | Delta | GLM 4.6 |
|---|---|---|---|
Capabilities | 67 | -- | |
Benchmarks | 69 | -1 | |
Pricing | 99 | +1 | |
Context window size | 76 | +0 | |
Recency | 100 | +20 | |
Output Capacity | 88 | +18 | |
| Overall Result | 4 wins | of 6 | 1 wins |
Score History
70
current score
GLM 4.6
right now
70.1
current score
MiniMax M2.7
MiniMax
GLM 4.6
Zhipu AI
MiniMax M2.7 saves you $58.50/month
That's $702.00/year compared to GLM 4.6 at your current usage level of 100K calls/month.
| Metric | MiniMax M2.7 | GLM 4.6 | Winner |
|---|---|---|---|
| Overall Score | 70 | 70 | GLM 4.6 |
| Rank | #96 | #95 | GLM 4.6 |
| Quality Rank | #96 | #95 | GLM 4.6 |
| Adoption Rank | #96 | #95 | GLM 4.6 |
| Parameters | -- | -- | -- |
| Context Window | 205K | 200K | MiniMax M2.7 |
| Pricing | $0.24/$0.96/M | $0.43/$1.75/M | -- |
| Signal Scores | |||
| Capabilities | 67 | 67 | MiniMax M2.7 |
| Benchmarks | 69 | 70 | GLM 4.6 |
| Pricing | 99 | 98 | MiniMax M2.7 |
| Context window size | 76 | 76 | MiniMax M2.7 |
| Recency | 100 | 81 | MiniMax M2.7 |
| Output Capacity | 88 | 70 | MiniMax M2.7 |
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 70/100 (rank #96), placing it in the top 67% of all 290 models tracked.
Scores 70/100 (rank #95), placing it in the top 68% of all 290 models tracked.
With only a 0-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.
Choose MiniMax M2.7 when you need:
- High-volume production workloads where API costs must be minimized
- Step-by-step reasoning and chain-of-thought problem solving
- Self-hosted deployments where you need full control over the model
Choose GLM 4.6 when you need:
- Step-by-step reasoning and chain-of-thought problem solving
- Self-hosted deployments where you need full control over the model
MiniMax M2.7 offers 45% better value per quality point. At 1M tokens/day, you'd spend $18.00/month with MiniMax M2.7 vs $32.70/month with GLM 4.6 - a $14.70 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 M2.7 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 ($0.96/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (70/100) correlates with better nuance, coherence, and style in long-form content
MiniMax M2.7 and GLM 4.6 are extremely close in overall performance (only 0.09999999999999432 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.
By Use Case
Best for Quality
MiniMax M2.7
Marginally better benchmark scores; both are excellent
Best for Cost
MiniMax M2.7
45% lower pricing; better value at scale
Best for Reliability
MiniMax M2.7
Higher uptime and faster response speeds
Best for Prototyping
MiniMax M2.7
Stronger community support and better developer experience
Best for Production
MiniMax M2.7
Wider enterprise adoption and proven at scale
by MiniMax
- Choose for Quality - Marginally better benchmark scores; both are excellent
- Choose for Cost - 45% lower pricing; better value at scale
- Choose for Reliability - Higher uptime and faster response speeds
- Choose for Prototyping - Stronger community support and better developer experience
- Choose for Production - Wider enterprise adoption and proven at scale
| Capability | MiniMax M2.7 | GLM 4.6 |
|---|---|---|
| Vision (Image Input) | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoning | ||
| Web Search | ||
| Image Output |
MiniMax M2.7
MiniMax
GLM 4.6
Zhipu AI
MiniMax M2.7 saves you $1.29/month
That's 45% cheaper than GLM 4.6 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 M2.7 | GLM 4.6 |
|---|---|---|
| Context Window | 205K | 200K |
| Max Output Tokens | 196,608 | 16,384 |
| Open Source | Yes | Yes |
| Created | Mar 18, 2026 | Sep 30, 2025 |