API cost decision in 10 seconds

🔥MiniMax M2.7 vs GLM 4.6

Pick MiniMax M2.7 when budget and context both matter.

Page updated:  Data confirmed:  Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick MiniMax M2.7 when budget and context both matter.

On the standard 1M input plus 500K output workload, MiniMax M2.7 is estimated at $0.88 vs $1.3 for GLM 4.6, saving $0.42 (32.4% lower).

Cost-first pickMiniMax M2.7
Context-first pickMiniMax M2.7
Sample savings$0.4232.4%
10x traffic gap$4.21

MiniMax M2.7 is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $4.21. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

MiniMax M2.7 stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shapeToken mixBetter pickMiniMax M2.7GLM 4.6
Input-heavy / RAG5M input + 500K outputMiniMax M2.7$2$3.02
Balanced workload1M input + 1M outputMiniMax M2.7$1.48$2.17
Output-heavy chatbot1M input + 5M outputMiniMax M2.7$6.28$9.13
Cheaper input MiniMax M2.7 $0.279 vs $0.43 / 1M

MiniMax M2.7 is $0.15 cheaper per 1M input tokens (35.1% lower; 1.54x difference).

Cheaper output MiniMax M2.7 $1.2 vs $1.74 / 1M

MiniMax M2.7 is $0.54 cheaper per 1M output tokens (31% lower; 1.45x difference).

Larger context MiniMax M2.7 204.8K vs 202.75K

MiniMax M2.7 has 2.05K more context (1.01x larger).

Sample workload MiniMax M2.7 $0.88 vs $1.3

MiniMax M2.7 is $0.42 cheaper on the standard workload (32.4% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
MiniMax M2.7 Calculating… Estimated API cost
GLM 4.6 Calculating… Estimated API cost
Cheaper for this workload Calculating… Difference: calculating…

This estimate uses normalized public API pricing per 1M tokens. It is a planning aid, not a billing quote. Verify provider pricing, limits, and terms before production use.

Quick Decision

Verdict

MiniMax M2.7 has the lower input price; MiniMax M2.7 has the lower output price; MiniMax M2.7 offers the larger context window. For the 1M input plus 500K output sample, MiniMax M2.7 is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $0.88 for MiniMax M2.7 and $1.3 for GLM 4.6.

Best Fit

Choose MiniMax M2.7 when you care most about lower input-token price, lower output-token price, and larger context window.

Choose GLM 4.6 when its provider, model quality, latency, or availability is more important than the numeric price/context winner.

Decision Notes
  • On the standard 1M input plus 500K output workload, MiniMax M2.7 is estimated at $0.88 vs $1.3 for GLM 4.6, saving $0.42 (32.4% lower).
  • MiniMax M2.7 is $0.42 cheaper on the standard workload (32.4% lower).
  • MiniMax M2.7 is $0.15 cheaper per 1M input tokens (35.1% lower; 1.54x difference).
  • MiniMax M2.7 is $0.54 cheaper per 1M output tokens (31% lower; 1.45x difference).
  • MiniMax M2.7 has 2.05K more context (1.01x larger).
Head-to-Head Specs
Feature🔥MiniMax M2.7
(MiniMax)
GLM 4.6
(Z.ai)
Input Price
prompt tokens per 1M
$0.279$0.43
Completion Price
per 1M tokens
$1.2$1.74
Sample Workload Cost
1M input + 500K output
$0.88$1.3
Context Window204.8K202.75K
Release Date
Popularity#14#63

Use-Case Decision Matrix

Use caseBetter pickWhy
Budget-constrained productionMiniMax M2.7On the standard 1M input plus 500K output workload, MiniMax M2.7 is estimated at $0.88 vs $1.3 for GLM 4.6, saving $0.42 (32.4% lower).
High-volume input processingMiniMax M2.7Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbotsMiniMax M2.7Lower output-token price matters most when assistants generate many completion tokens.
RAG or long-document workMiniMax M2.7A larger context window leaves more room for retrieved passages, conversation history, or source files.

Related Alternatives

Same-provider lower-cost swaps
  • MiniMax M2.5 (free) can replace MiniMax M2.7 when lower sample workload cost matters most: $0.
  • MiniMax M2.5 can replace MiniMax M2.7 when lower sample workload cost matters most: $0.72.
  • MiniMax-01 can replace MiniMax M2.7 when lower sample workload cost matters most: $0.75.
  • MiniMax M2 can replace MiniMax M2.7 when lower sample workload cost matters most: $0.76.
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MiniMax catalog

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Z.ai catalog

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MiniMax M2.7

MiniMax-M2.7 is a next-generation large language model designed for autonomous, real-world productivity and continuous improvement. Built to actively participate in its own evolution, M2.7 integrates advanced agentic capabilities through multi-agent...

GLM 4.6

Compared with GLM-4.5, this generation brings several key improvements: Longer context window: The context window has been expanded from 128K to 200K tokens, enabling the model to handle more complex...