Model Comparison

GLM-4.6 vs DeepSeek-V2.5

GLM-4.6 significantly outperforms across most benchmarks. DeepSeek-V2.5 is 5.2x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

GLM-4.6 outperforms in 1 benchmarks (SWE-Bench Verified), while DeepSeek-V2.5 is better at 0 benchmarks.

GLM-4.6 significantly outperforms across most benchmarks.

Tue Apr 14 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-4.6 ($0.55/1M tokens) is 3.9x more expensive than DeepSeek-V2.5 ($0.14/1M tokens).

For output processing, GLM-4.6 ($2.00/1M tokens) is 7.1x more expensive than DeepSeek-V2.5 ($0.28/1M tokens).

In conclusion, GLM-4.6 is more expensive than DeepSeek-V2.5.*

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

Lowest available price from all providers
Tue Apr 14 2026 • llm-stats.com
Zhipu AI
GLM-4.6
Input tokens$0.55
Output tokens$2.00
Best providerFireworks
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

121.0B diff

GLM-4.6 has 121.0B more parameters than DeepSeek-V2.5, making it 51.3% larger.

Zhipu AI
GLM-4.6
357.0Bparameters
DeepSeek
DeepSeek-V2.5
236.0Bparameters
357.0B
GLM-4.6
236.0B
DeepSeek-V2.5

Context Window

Maximum input and output token capacity

GLM-4.6 accepts 131,072 input tokens compared to DeepSeek-V2.5's 8,192 tokens. GLM-4.6 can generate longer responses up to 131,072 tokens, while DeepSeek-V2.5 is limited to 8,192 tokens.

Zhipu AI
GLM-4.6
Input131,072 tokens
Output131,072 tokens
DeepSeek
DeepSeek-V2.5
Input8,192 tokens
Output8,192 tokens
Tue Apr 14 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

GLM-4.6 supports multimodal inputs, whereas DeepSeek-V2.5 does not.

GLM-4.6 can handle both text and other forms of data like images, making it suitable for multimodal applications.

GLM-4.6

Text
Images
Audio
Video

DeepSeek-V2.5

Text
Images
Audio
Video

License

Usage and distribution terms

GLM-4.6 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-4.6

MIT

Open weights

DeepSeek-V2.5

deepseek

Open weights

Release Timeline

When each model was launched

GLM-4.6 was released on 2025-09-30, while DeepSeek-V2.5 was released on 2024-05-08.

GLM-4.6 is 17 months newer than DeepSeek-V2.5.

GLM-4.6

Sep 30, 2025

6 months ago

1.4yr 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-4.6 is available from Fireworks, DeepInfra. DeepSeek-V2.5 is available from DeepSeek, DeepInfra, Hyperbolic.

GLM-4.6

fireworks logo
Fireworks
Input Price:Input: $0.55/1MOutput Price:Output: $2.19/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.60/1MOutput Price:Output: $2.00/1M

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

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Key Takeaways

Zhipu AI
Larger context window (131,072 tokens)
Supports multimodal inputs
Higher SWE-Bench Verified score (68.0% vs 16.8%)
DeepSeek
Less expensive input tokens
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
Zhipu AI
GLM-4.6
DeepSeek
DeepSeek-V2.5

FAQ

Common questions about GLM-4.6 vs DeepSeek-V2.5

GLM-4.6 significantly outperforms across most benchmarks. GLM-4.6 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-4.6 scores AIME 2025: 93.9%, LiveCodeBench v6: 82.8%, GPQA: 81.0%, SWE-Bench Verified: 68.0%, BrowseComp: 45.1%. 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. GLM-4.6 costs $0.55/M input and $2.00/M output via fireworks. DeepSeek-V2.5 costs $0.14/M input and $0.28/M output via deepseek.
GLM-4.6 supports 131K 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 (131K vs 8K), input pricing ($0.55 vs $0.14/M), multimodal support (yes vs no), licensing (MIT vs deepseek). See the full comparison above for benchmark-by-benchmark results.
GLM-4.6 is developed by Zhipu AI and DeepSeek-V2.5 is developed by DeepSeek.