Model Comparison

DeepSeek-V2.5 vs GLM-4.5V

Comparing DeepSeek-V2.5 and GLM-4.5V across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-V2.5 and GLM-4.5V don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

DeepSeek-V2.5 costs less

For input processing, DeepSeek-V2.5 ($0.14/1M tokens) is 3.9x cheaper than GLM-4.5V ($0.55/1M tokens).

For output processing, DeepSeek-V2.5 ($0.28/1M tokens) is 7.8x cheaper than GLM-4.5V ($2.19/1M tokens).

In conclusion, GLM-4.5V is more expensive than DeepSeek-V2.5.*

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

Lowest available price from all providers
Mon Apr 13 2026 • llm-stats.com
DeepSeek
DeepSeek-V2.5
Input tokens$0.14
Output tokens$0.28
Best providerDeepSeek
Zhipu AI
GLM-4.5V
Input tokens$0.55
Output tokens$2.19
Best providerFireworks
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

128.0B diff

DeepSeek-V2.5 has 128.0B more parameters than GLM-4.5V, making it 118.5% larger.

DeepSeek
DeepSeek-V2.5
236.0Bparameters
Zhipu AI
GLM-4.5V
108.0Bparameters
236.0B
DeepSeek-V2.5
108.0B
GLM-4.5V

Context Window

Maximum input and output token capacity

GLM-4.5V accepts 131,072 input tokens compared to DeepSeek-V2.5's 8,192 tokens. GLM-4.5V can generate longer responses up to 131,072 tokens, while DeepSeek-V2.5 is limited to 8,192 tokens.

DeepSeek
DeepSeek-V2.5
Input8,192 tokens
Output8,192 tokens
Zhipu AI
GLM-4.5V
Input131,072 tokens
Output131,072 tokens
Mon Apr 13 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

GLM-4.5V supports multimodal inputs, whereas DeepSeek-V2.5 does not.

GLM-4.5V can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V2.5

Text
Images
Audio
Video

GLM-4.5V

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V2.5 is licensed under deepseek, while GLM-4.5V uses MIT.

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

DeepSeek-V2.5

deepseek

Open weights

GLM-4.5V

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek-V2.5 was released on 2024-05-08, while GLM-4.5V was released on 2025-08-11.

GLM-4.5V is 15 months newer than DeepSeek-V2.5.

DeepSeek-V2.5

May 8, 2024

1.9 years ago

GLM-4.5V

Aug 11, 2025

8 months ago

1.3yr 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

DeepSeek-V2.5 is available from DeepSeek, DeepInfra, Hyperbolic. GLM-4.5V is available from Fireworks, Novita.

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

GLM-4.5V

fireworks logo
Fireworks
Input Price:Input: $0.55/1MOutput Price:Output: $2.19/1M
novita logo
Novita
Input Price:Input: $0.60/1MOutput Price:Output: $2.20/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

DeepSeek
Less expensive input tokens
Less expensive output tokens
Zhipu AI
Larger context window (131,072 tokens)
Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V2.5
Zhipu AI
GLM-4.5V

FAQ

Common questions about DeepSeek-V2.5 vs GLM-4.5V

DeepSeek-V2.5 (DeepSeek) and GLM-4.5V (Zhipu AI) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
DeepSeek-V2.5 scores GSM8k: 95.1%, MT-Bench: 90.2%, HumanEval: 89.0%, BBH: 84.3%, AlignBench: 80.4%.
DeepSeek-V2.5 is 3.9x cheaper for input tokens. DeepSeek-V2.5 costs $0.14/M input and $0.28/M output via deepseek. GLM-4.5V costs $0.55/M input and $2.19/M output via fireworks.
DeepSeek-V2.5 supports 8K tokens and GLM-4.5V supports 131K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (8K vs 131K), input pricing ($0.14 vs $0.55/M), multimodal support (no vs yes), licensing (deepseek vs MIT). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-V2.5 is developed by DeepSeek and GLM-4.5V is developed by Zhipu AI.