Model Comparison

GLM-5 vs DeepSeek-V2.5

GLM-5 significantly outperforms across most benchmarks. DeepSeek-V2.5 is 8.9x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

GLM-5 outperforms in 1 benchmarks (SWE-Bench Verified), while DeepSeek-V2.5 is better at 0 benchmarks.

GLM-5 significantly outperforms across most benchmarks.

Thu Apr 16 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

DeepSeek-V2.5 costs less

For input processing, GLM-5 ($1.00/1M tokens) is 7.1x more expensive than DeepSeek-V2.5 ($0.14/1M tokens).

For output processing, GLM-5 ($3.20/1M tokens) is 11.4x more expensive than DeepSeek-V2.5 ($0.28/1M tokens).

In conclusion, GLM-5 is more expensive than DeepSeek-V2.5.*

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

Lowest available price from all providers
Thu Apr 16 2026 • llm-stats.com
Zhipu AI
GLM-5
Input tokens$1.00
Output tokens$3.20
Best providerUnknown Organization
DeepSeek
DeepSeek-V2.5
Input tokens$0.14
Output tokens$0.28
Best providerDeepSeek
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

508.0B diff

GLM-5 has 508.0B more parameters than DeepSeek-V2.5, making it 215.3% larger.

Zhipu AI
GLM-5
744.0Bparameters
DeepSeek
DeepSeek-V2.5
236.0Bparameters
744.0B
GLM-5
236.0B
DeepSeek-V2.5

Context Window

Maximum input and output token capacity

GLM-5 accepts 200,000 input tokens compared to DeepSeek-V2.5's 8,192 tokens. GLM-5 can generate longer responses up to 128,000 tokens, while DeepSeek-V2.5 is limited to 8,192 tokens.

Zhipu AI
GLM-5
Input200,000 tokens
Output128,000 tokens
DeepSeek
DeepSeek-V2.5
Input8,192 tokens
Output8,192 tokens
Thu Apr 16 2026 • llm-stats.com

License

Usage and distribution terms

GLM-5 is licensed under MIT, while DeepSeek-V2.5 uses deepseek.

License differences may affect how you can use these models in commercial or open-source projects.

GLM-5

MIT

Open weights

DeepSeek-V2.5

deepseek

Open weights

Release Timeline

When each model was launched

GLM-5 was released on 2026-02-11, while DeepSeek-V2.5 was released on 2024-05-08.

GLM-5 is 21 months newer than DeepSeek-V2.5.

GLM-5

Feb 11, 2026

2 months ago

1.8yr newer
DeepSeek-V2.5

May 8, 2024

1.9 years ago

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. DeepSeek-V2.5 is available from DeepSeek, DeepInfra, Hyperbolic.

GLM-5

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

DeepSeek-V2.5

deepseek logo
DeepSeek
Input Price:Input: $0.14/1MOutput Price:Output: $0.28/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.70/1MOutput Price:Output: $1.40/1M
hyperbolic logo
Hyperbolic
Input Price:Input: $2.00/1MOutput Price:Output: $2.00/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Zhipu AI
Larger context window (200,000 tokens)
Higher SWE-Bench Verified score (77.8% vs 16.8%)
DeepSeek
Less expensive input tokens
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
Zhipu AI
GLM-5
DeepSeek
DeepSeek-V2.5

FAQ

Common questions about GLM-5 vs DeepSeek-V2.5

GLM-5 significantly outperforms across most benchmarks. GLM-5 is made by Zhipu AI and DeepSeek-V2.5 is made by DeepSeek. 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%. DeepSeek-V2.5 scores GSM8k: 95.1%, MT-Bench: 90.2%, HumanEval: 89.0%, BBH: 84.3%, AlignBench: 80.4%.
DeepSeek-V2.5 is 7.1x cheaper for input tokens. GLM-5 costs $1.00/M input and $3.20/M output via z. DeepSeek-V2.5 costs $0.14/M input and $0.28/M output via deepseek.
GLM-5 supports 200K tokens and DeepSeek-V2.5 supports 8K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (200K vs 8K), input pricing ($1.00 vs $0.14/M), licensing (MIT vs deepseek). See the full comparison above for benchmark-by-benchmark results.
GLM-5 is developed by Zhipu AI and DeepSeek-V2.5 is developed by DeepSeek.