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GLM-4.7 vs GLM-5.3

GLM-5.3 significantly outperforms across most benchmarks. GLM-4.7 is 2.1x cheaper per token.

Zhipu AI · Zhipu AI · Updated for 2026

Which is better?

GLM-4.7 outperforms in 0 benchmarks, while GLM-5.3 is better at 1 benchmark (Humanity's Last Exam). GLM-5.3 significantly outperforms across most benchmarks.

On price, GLM-4.7 is roughly 2.1x 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 GLM-4.7

  • cost matters — it's about 2.1x 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 1 of 1 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.

GLM-4.7
Zhipu AI
GLM-5.3
Zhipu AI
Benchmark wins
0 of 1
1 of 1
Input price
$0.60 / M
$1.40 / M
Output price
$2.20 / M
$4.40 / M
Context window
202,800
1,000,000
Released
Dec 2025
Aug 2026
License
MIT
Unknown

Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

GLM-4.7 outperforms in 0 benchmarks, while GLM-5.3 is better at 1 benchmark (Humanity's Last Exam).

GLM-5.3 significantly outperforms across most benchmarks.

Mon Aug 24 2026 • llm-stats.com

Arena Performance

Playground indexes and blind preference scores

Pricing Analysis

Price comparison per million tokens

GLM-4.7 costs less

For input processing, GLM-4.7 ($0.60/1M tokens) is 2.3x cheaper than GLM-5.3 ($1.40/1M tokens).

For output processing, GLM-4.7 ($2.20/1M tokens) is 2.0x cheaper than GLM-5.3 ($4.40/1M tokens).

In conclusion, GLM-5.3 is more expensive than GLM-4.7.*

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

Lowest available price from all providers
Mon Aug 24 2026 • llm-stats.com
Zhipu AI
GLM-4.7
Input tokens$0.60
Output tokens$2.20
Best providerFireworks
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

395.0B diff

GLM-5.3 has 395.0B more parameters than GLM-4.7, making it 110.3% larger.

Zhipu AI
GLM-4.7
358.0Bparameters
Zhipu AI
GLM-5.3
753.0Bparameters
358.0B
GLM-4.7
753.0B
GLM-5.3

Context Window

Maximum input and output token capacity

GLM-5.3 accepts 1,000,000 input tokens compared to GLM-4.7's 202,800 tokens. GLM-4.7 can generate longer responses up to 131,072 tokens, while GLM-5.3 is limited to 128,000 tokens.

Zhipu AI
GLM-4.7
Input202,800 tokens
Output131,072 tokens
Zhipu AI
GLM-5.3
Input1,000,000 tokens
Output128,000 tokens
Mon Aug 24 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

GLM-4.7 supports multimodal inputs, whereas GLM-5.3 does not.

GLM-4.7 can handle both text and other forms of data like images, making it suitable for multimodal applications.

GLM-4.7

Text
Images
Audio
Video

GLM-5.3

Text
Images
Audio
Video

Release Timeline

When each model was launched

GLM-4.7 was released on 2025-12-22, while GLM-5.3 was released on 2026-08-14.

GLM-5.3 is 8 months newer than GLM-4.7.

GLM-4.7

Dec 22, 2025

8 months ago

GLM-5.3

Aug 14, 2026

1 weeks ago

7mo 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

GLM-4.7 is available from Fireworks, Novita. GLM-5.3 is available from ZAI.

GLM-4.7

fireworks logo
Fireworks
Input Price:Input: $0.60/1MOutput Price:Output: $2.20/1M
novita logo
Novita
Input Price:Input: $0.60/1MOutput Price:Output: $2.20/1M

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 GLM-4.7 and GLM-5.3 side-by-side, then vote on the output you prefer.

GLM-4.7
✓ Preferred
GLM-5.3
Open in Playground

FAQ

Common questions about GLM-4.7 vs GLM-5.3.

Which is better, GLM-4.7 or GLM-5.3?

GLM-5.3 significantly outperforms across most benchmarks. GLM-4.7 is made by Zhipu AI 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 GLM-4.7 compare to GLM-5.3 in benchmarks?

GLM-4.7 scores AIME 2025: 95.7%, Tau-bench: 87.4%, GPQA: 85.7%, LiveCodeBench v6: 84.9%, MMLU-Pro: 84.3%. 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 GLM-4.7 cheaper than GLM-5.3?

GLM-4.7 is 2.3x cheaper for input tokens. GLM-4.7 costs $0.60/M input and $2.20/M output via fireworks. GLM-5.3 costs $1.40/M input and $4.40/M output via z.

What are the context window sizes for GLM-4.7 and GLM-5.3?

GLM-4.7 supports 203K 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 GLM-4.7 and GLM-5.3?

Key differences include context window (203K vs 1.0M), input pricing ($0.60 vs $1.40/M), multimodal support (yes vs no), licensing (MIT vs Unknown). See the full comparison above for benchmark-by-benchmark results.

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