Model Comparison

DeepSeek-R1-0528 vs GLM-5Which is better in 2026?

GLM-5 significantly outperforms across most benchmarks. DeepSeek-R1-0528 is 1.7x cheaper per token.

Verdict: DeepSeek-R1-0528 vs GLM-5 — which is better?

DeepSeek-R1-0528 (by DeepSeek) and GLM-5 (by Zhipu AI) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

DeepSeek-R1-0528 outperforms in 0 benchmarks, while GLM-5 is better at 2 benchmarks (BrowseComp, SWE-Bench Verified). GLM-5 significantly outperforms across most benchmarks.

On price, DeepSeek-R1-0528 is roughly 1.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

GLM-5 also accepts a larger context window (200,000 input tokens), making it the stronger choice for long documents and large codebases.

Choose DeepSeek-R1-0528 if…

  • cost matters — it's about 1.7x cheaper per token

Choose GLM-5 if…

  • you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
  • you process long inputs — it offers a 200,000 token context window
  • you want the most recent training data — it shipped Feb 2026

Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

DeepSeek-R1-0528 outperforms in 0 benchmarks, while GLM-5 is better at 2 benchmarks (BrowseComp, SWE-Bench Verified).

GLM-5 significantly outperforms across most benchmarks.

Tue Jul 28 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

DeepSeek-R1-0528 costs less

For input processing, DeepSeek-R1-0528 ($0.50/1M tokens) is 2.0x cheaper than GLM-5 ($1.00/1M tokens).

For output processing, DeepSeek-R1-0528 ($2.15/1M tokens) is 1.5x cheaper than GLM-5 ($3.20/1M tokens).

In conclusion, GLM-5 is more expensive than DeepSeek-R1-0528.*

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

Lowest available price from all providers
Tue Jul 28 2026 • llm-stats.com
DeepSeek
DeepSeek-R1-0528
Input tokens$0.50
Output tokens$2.15
Best providerDeepinfra
Zhipu AI
GLM-5
Input tokens$1.00
Output tokens$3.20
Best providerFriendliAI
Notice missing or incorrect data?Start an Issue

Model Size

Parameter count comparison

73.0B diff

GLM-5 has 73.0B more parameters than DeepSeek-R1-0528, making it 10.9% larger.

DeepSeek
DeepSeek-R1-0528
671.0Bparameters
Zhipu AI
GLM-5
744.0Bparameters
671.0B
DeepSeek-R1-0528
744.0B
GLM-5

Context Window

Maximum input and output token capacity

GLM-5 accepts 200,000 input tokens compared to DeepSeek-R1-0528's 131,072 tokens. DeepSeek-R1-0528 can generate longer responses up to 131,072 tokens, while GLM-5 is limited to 128,000 tokens.

DeepSeek
DeepSeek-R1-0528
Input131,072 tokens
Output131,072 tokens
Zhipu AI
GLM-5
Input200,000 tokens
Output128,000 tokens
Tue Jul 28 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.

DeepSeek-R1-0528

MIT

Open weights

GLM-5

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek-R1-0528 was released on 2025-05-28, while GLM-5 was released on 2026-02-11.

GLM-5 is 9 months newer than DeepSeek-R1-0528.

DeepSeek-R1-0528

May 28, 2025

1.2 years ago

GLM-5

Feb 11, 2026

5 months ago

8mo 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-R1-0528 is available from DeepInfra, DeepSeek, Novita. GLM-5 is available from FriendliAI, ZAI.

DeepSeek-R1-0528

deepinfra logo
Deepinfra
Input Price:Input: $0.50/1MOutput Price:Output: $2.15/1M
deepseek logo
DeepSeek
Input Price:Input: $0.55/1MOutput Price:Output: $2.19/1M
novita logo
Novita
Input Price:Input: $0.70/1MOutput Price:Output: $2.50/1M

GLM-5

friendli logo
FriendliAI
Input Price:Input: $1.00/1MOutput Price:Output: $3.20/1M
z logo
Unknown Organization
Input Price:Input: $1.00/1MOutput Price:Output: $3.20/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Key Takeaways

Less expensive input tokens
Less expensive output tokens
Larger context window (200,000 tokens)
Higher BrowseComp score (75.9% vs 8.9%)
Higher SWE-Bench Verified score (77.8% vs 44.6%)

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against DeepSeek-R1-0528 and GLM-5 side-by-side, then vote on the output you prefer.

DeepSeek-R1-0528
✓ Preferred
GLM-5
Open in Playground
AI Model Comparison Table
Feature
DeepSeek
DeepSeek-R1-0528
Zhipu AI
GLM-5

FAQ

Common questions about DeepSeek-R1-0528 vs GLM-5.

Which is better, DeepSeek-R1-0528 or GLM-5?

GLM-5 significantly outperforms across most benchmarks. DeepSeek-R1-0528 is made by DeepSeek and GLM-5 is made by Zhipu AI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does DeepSeek-R1-0528 compare to GLM-5 in benchmarks?

DeepSeek-R1-0528 scores MMLU-Redux: 93.4%, SimpleQA: 92.3%, AIME 2024: 91.4%, AIME 2025: 87.5%, MMLU-Pro: 85.0%. 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%.

Is DeepSeek-R1-0528 cheaper than GLM-5?

DeepSeek-R1-0528 is 2.0x cheaper for input tokens. DeepSeek-R1-0528 costs $0.50/M input and $2.15/M output via deepinfra. GLM-5 costs $1.00/M input and $3.20/M output via friendli.

What are the context window sizes for DeepSeek-R1-0528 and GLM-5?

DeepSeek-R1-0528 supports 131K tokens and GLM-5 supports 200K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek-R1-0528 and GLM-5?

Key differences include context window (131K vs 200K), input pricing ($0.50 vs $1.00/M). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-R1-0528 and GLM-5?

DeepSeek-R1-0528 is developed by DeepSeek and GLM-5 is developed by Zhipu AI.