Model Comparison

GLM-5 vs DeepSeek R1 Distill Qwen 1.5B

Comparing GLM-5 and DeepSeek R1 Distill Qwen 1.5B across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

GLM-5 and DeepSeek R1 Distill Qwen 1.5B 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

Cost data unavailable.

Lowest available price from all providers
Wed Apr 15 2026 • llm-stats.com
Zhipu AI
GLM-5
Input tokens$1.00
Output tokens$3.20
Best providerUnknown Organization
DeepSeek
DeepSeek R1 Distill Qwen 1.5B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

742.2B diff

GLM-5 has 742.2B more parameters than DeepSeek R1 Distill Qwen 1.5B, making it 41697.8% larger.

Zhipu AI
GLM-5
744.0Bparameters
DeepSeek
DeepSeek R1 Distill Qwen 1.5B
1.8Bparameters
744.0B
GLM-5
1.8B
DeepSeek R1 Distill Qwen 1.5B

Context Window

Maximum input and output token capacity

Only GLM-5 specifies input context (200,000 tokens). Only GLM-5 specifies output context (128,000 tokens).

Zhipu AI
GLM-5
Input200,000 tokens
Output128,000 tokens
DeepSeek
DeepSeek R1 Distill Qwen 1.5B
Input- tokens
Output- tokens
Wed Apr 15 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

DeepSeek R1 Distill Qwen 1.5B

MIT

Open weights

Release Timeline

When each model was launched

GLM-5 was released on 2026-02-11, while DeepSeek R1 Distill Qwen 1.5B was released on 2025-01-20.

GLM-5 is 13 months newer than DeepSeek R1 Distill Qwen 1.5B.

GLM-5

Feb 11, 2026

2 months ago

1.1yr newer
DeepSeek R1 Distill Qwen 1.5B

Jan 20, 2025

1.2 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

Outputs Comparison

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Key Takeaways

Zhipu AI
Larger context window (200,000 tokens)
DeepSeek

Detailed Comparison

AI Model Comparison Table
Feature
Zhipu AI
GLM-5
DeepSeek
DeepSeek R1 Distill Qwen 1.5B

FAQ

Common questions about GLM-5 vs DeepSeek R1 Distill Qwen 1.5B

GLM-5 (Zhipu AI) and DeepSeek R1 Distill Qwen 1.5B (DeepSeek) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
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 R1 Distill Qwen 1.5B scores MATH-500: 83.9%, AIME 2024: 52.7%, GPQA: 33.8%, LiveCodeBench: 16.9%.
GLM-5 supports 200K tokens and DeepSeek R1 Distill Qwen 1.5B supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
GLM-5 is developed by Zhipu AI and DeepSeek R1 Distill Qwen 1.5B is developed by DeepSeek.