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DeepSeek-V3.2 (Thinking) vs GLM-5.3

GLM-5.3 significantly outperforms across most benchmarks. DeepSeek-V3.2 (Thinking) is 6.8x cheaper per token.

DeepSeek · Zhipu AI · Updated for 2026

Which is better?

DeepSeek-V3.2 (Thinking) outperforms in 0 benchmarks, while GLM-5.3 is better at 2 benchmarks (Humanity's Last Exam, Toolathlon). GLM-5.3 significantly outperforms across most benchmarks.

On price, DeepSeek-V3.2 (Thinking) is roughly 6.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

GLM-5.3 also accepts a larger context window (1,000,000 input tokens), making it the stronger choice for long documents and large codebases.

Based on current benchmark, pricing, and model metadata for 2026.

Choose DeepSeek-V3.2 (Thinking)

  • cost matters — it's about 6.8x cheaper per token
  • you need open weights you can self-host or fine-tune

Choose GLM-5.3

  • you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
  • you process long inputs — it offers a 1,000,000 token context window
  • you want the most recent training data — it shipped Aug 2026

At a glance

The differences that matter most.

DeepSeek-V3.2 (Thinking)
DeepSeek
GLM-5.3
Zhipu AI
Benchmark wins
0 of 2
2 of 2
Input price
$0.28 / M
$1.40 / M
Output price
$0.42 / M
$4.40 / M
Context window
131,072
1,000,000
Released
Dec 2025
Aug 2026
License
MIT
Unknown

Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

DeepSeek-V3.2 (Thinking) outperforms in 0 benchmarks, while GLM-5.3 is better at 2 benchmarks (Humanity's Last Exam, Toolathlon).

GLM-5.3 significantly outperforms across most benchmarks.

Tue Aug 25 2026 • llm-stats.com

Arena Performance

Playground indexes and blind preference scores

Pricing Analysis

Price comparison per million tokens

DeepSeek-V3.2 (Thinking) costs less

For input processing, DeepSeek-V3.2 (Thinking) ($0.28/1M tokens) is 5.0x cheaper than GLM-5.3 ($1.40/1M tokens).

For output processing, DeepSeek-V3.2 (Thinking) ($0.42/1M tokens) is 10.5x cheaper than GLM-5.3 ($4.40/1M tokens).

In conclusion, GLM-5.3 is more expensive than DeepSeek-V3.2 (Thinking).*

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

Lowest available price from all providers
Tue Aug 25 2026 • llm-stats.com
DeepSeek
DeepSeek-V3.2 (Thinking)
Input tokens$0.28
Output tokens$0.42
Best providerDeepSeek
Zhipu AI
GLM-5.3
Input tokens$1.40
Output tokens$4.40
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

68.0B diff

GLM-5.3 has 68.0B more parameters than DeepSeek-V3.2 (Thinking), making it 9.9% larger.

DeepSeek
DeepSeek-V3.2 (Thinking)
685.0Bparameters
Zhipu AI
GLM-5.3
753.0Bparameters
685.0B
DeepSeek-V3.2 (Thinking)
753.0B
GLM-5.3

Context Window

Maximum input and output token capacity

GLM-5.3 accepts 1,000,000 input tokens compared to DeepSeek-V3.2 (Thinking)'s 131,072 tokens. GLM-5.3 can generate longer responses up to 128,000 tokens, while DeepSeek-V3.2 (Thinking) is limited to 65,536 tokens.

DeepSeek
DeepSeek-V3.2 (Thinking)
Input131,072 tokens
Output65,536 tokens
Zhipu AI
GLM-5.3
Input1,000,000 tokens
Output128,000 tokens
Tue Aug 25 2026 • llm-stats.com

Release Timeline

When each model was launched

DeepSeek-V3.2 (Thinking) was released on 2025-12-01, while GLM-5.3 was released on 2026-08-14.

GLM-5.3 is 9 months newer than DeepSeek-V3.2 (Thinking).

DeepSeek-V3.2 (Thinking)

Dec 1, 2025

8 months ago

GLM-5.3

Aug 14, 2026

1 weeks 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-V3.2 (Thinking) is available from DeepSeek. GLM-5.3 is available from ZAI.

DeepSeek-V3.2 (Thinking)

deepseek logo
DeepSeek
Input Price:Input: $0.28/1MOutput Price:Output: $0.42/1M

GLM-5.3

z logo
Unknown Organization
Input Price:Input: $1.40/1MOutput Price:Output: $4.40/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against DeepSeek-V3.2 (Thinking) and GLM-5.3 side-by-side, then vote on the output you prefer.

DeepSeek-V3.2 (Thinking)
✓ Preferred
GLM-5.3
Open in Playground

FAQ

Common questions about DeepSeek-V3.2 (Thinking) vs GLM-5.3.

Which is better, DeepSeek-V3.2 (Thinking) or GLM-5.3?

GLM-5.3 significantly outperforms across most benchmarks. DeepSeek-V3.2 (Thinking) is made by DeepSeek and GLM-5.3 is made by Zhipu AI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does DeepSeek-V3.2 (Thinking) compare to GLM-5.3 in benchmarks?

DeepSeek-V3.2 (Thinking) scores AIME 2025: 93.1%, HMMT 2025: 90.2%, MMLU-Pro: 85.0%, LiveCodeBench: 83.3%, GPQA: 82.4%. GLM-5.3 scores Terminal-Bench 2.1: 88.2%, CyberGym: 84.5%, FrontierSWE: 78.1%, Toolathlon: 73.0%, DeepSWE 1.1: 66.9%.

Is DeepSeek-V3.2 (Thinking) cheaper than GLM-5.3?

DeepSeek-V3.2 (Thinking) is 5.0x cheaper for input tokens. DeepSeek-V3.2 (Thinking) costs $0.28/M input and $0.42/M output via deepseek. GLM-5.3 costs $1.40/M input and $4.40/M output via z.

What are the context window sizes for DeepSeek-V3.2 (Thinking) and GLM-5.3?

DeepSeek-V3.2 (Thinking) supports 131K tokens and GLM-5.3 supports 1.0M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek-V3.2 (Thinking) and GLM-5.3?

Key differences include context window (131K vs 1.0M), input pricing ($0.28 vs $1.40/M), licensing (MIT vs Unknown). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V3.2 (Thinking) and GLM-5.3?

DeepSeek-V3.2 (Thinking) is developed by DeepSeek and GLM-5.3 is developed by Zhipu AI.

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