Model Comparison

GLM-5 vs MiniMax M2.5

MiniMax M2.5 significantly outperforms across most benchmarks. MiniMax M2.5 is 3.0x cheaper per token.

Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

GLM-5 outperforms in 0 benchmarks, while MiniMax M2.5 is better at 2 benchmarks (BrowseComp, SWE-Bench Verified).

MiniMax M2.5 significantly outperforms across most benchmarks.

Sat Apr 18 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

MiniMax M2.5 costs less

For input processing, GLM-5 ($1.00/1M tokens) is 3.3x more expensive than MiniMax M2.5 ($0.30/1M tokens).

For output processing, GLM-5 ($3.20/1M tokens) is 2.7x more expensive than MiniMax M2.5 ($1.20/1M tokens).

In conclusion, GLM-5 is more expensive than MiniMax M2.5.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Sat Apr 18 2026 • llm-stats.com
Zhipu AI
GLM-5
Input tokens$1.00
Output tokens$3.20
Best providerUnknown Organization
MiniMax
MiniMax M2.5
Input tokens$0.30
Output tokens$1.20
Best providerMiniMax
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

514.0B diff

GLM-5 has 514.0B more parameters than MiniMax M2.5, making it 223.5% larger.

Zhipu AI
GLM-5
744.0Bparameters
MiniMax
MiniMax M2.5
230.0Bparameters
744.0B
GLM-5
230.0B
MiniMax M2.5

Context Window

Maximum input and output token capacity

MiniMax M2.5 accepts 1,000,000 input tokens compared to GLM-5's 200,000 tokens. MiniMax M2.5 can generate longer responses up to 1,000,000 tokens, while GLM-5 is limited to 128,000 tokens.

Zhipu AI
GLM-5
Input200,000 tokens
Output128,000 tokens
MiniMax
MiniMax M2.5
Input1,000,000 tokens
Output1,000,000 tokens
Sat Apr 18 2026 • llm-stats.com

License

Usage and distribution terms

Both models are licensed under MIT.

Both models share the same licensing terms, providing consistent usage rights.

GLM-5

MIT

Open weights

MiniMax M2.5

MIT

Open weights

Release Timeline

When each model was launched

GLM-5 was released on 2026-02-11, while MiniMax M2.5 was released on 2026-02-12.

MiniMax M2.5 is 0 month newer than GLM-5.

GLM-5

Feb 11, 2026

2 months ago

MiniMax M2.5

Feb 12, 2026

2 months ago

1d newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Provider Availability

GLM-5 is available from ZAI. MiniMax M2.5 is available from MiniMax.

GLM-5

z logo
Unknown Organization
Input Price:Input: $1.00/1MOutput Price:Output: $3.20/1M

MiniMax M2.5

minimax logo
MiniMax
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Zhipu AI
MiniMax
Larger context window (1,000,000 tokens)
Less expensive input tokens
Less expensive output tokens
Higher BrowseComp score (76.3% vs 75.9%)
Higher SWE-Bench Verified score (80.2% vs 77.8%)

Detailed Comparison

AI Model Comparison Table
Feature
Zhipu AI
GLM-5
MiniMax
MiniMax M2.5

FAQ

Common questions about GLM-5 vs MiniMax M2.5

MiniMax M2.5 significantly outperforms across most benchmarks. GLM-5 is made by Zhipu AI and MiniMax M2.5 is made by MiniMax. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
GLM-5 scores t2-bench: 89.7%, SWE-Bench Verified: 77.8%, BrowseComp: 75.9%, MCP Atlas: 67.8%, Terminal-Bench 2.0: 56.2%. MiniMax M2.5 scores SWE-Bench Verified: 80.2%, BFCL_v3_MultiTurn: 76.8%, BrowseComp: 76.3%, MEWC: 74.4%, GDPval-MM: 59.0%.
MiniMax M2.5 is 3.3x cheaper for input tokens. GLM-5 costs $1.00/M input and $3.20/M output via z. MiniMax M2.5 costs $0.30/M input and $1.20/M output via minimax.
GLM-5 supports 200K tokens and MiniMax M2.5 supports 1.0M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (200K vs 1.0M), input pricing ($1.00 vs $0.30/M). See the full comparison above for benchmark-by-benchmark results.
GLM-5 is developed by Zhipu AI and MiniMax M2.5 is developed by MiniMax.