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GLM-5.3 vs Ministral 3 (8B Base 2512)

Comparing GLM-5.3 and Ministral 3 (8B Base 2512) across benchmarks, pricing, and capabilities.

Zhipu AI · Mistral AI · Updated for 2026

Which is better?

GLM-5.3 and Ministral 3 (8B Base 2512) trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.

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

Choose GLM-5.3

  • you want the most recent training data — it shipped Aug 2026

Choose Ministral 3 (8B Base 2512)

  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

Benchmark wins
Input price
$1.40 / M
— / M
Output price
$4.40 / M
— / M
Context window
1,000,000
Released
Aug 2026
Dec 2025
License
Unknown
Apache 2.0

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

GLM-5.3 and Ministral 3 (8B Base 2512)don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Playground indexes and blind preference scores

Model Size

Parameter count comparison

745.0B diff

GLM-5.3 has 745.0B more parameters than Ministral 3 (8B Base 2512), making it 9312.5% larger.

Zhipu AI
GLM-5.3
753.0Bparameters
Mistral AI
Ministral 3 (8B Base 2512)
8.0Bparameters
753.0B
GLM-5.3
8.0B
Ministral 3 (8B Base 2512)

Context Window

Maximum input and output token capacity

Only GLM-5.3 specifies input context (1,000,000 tokens). Only GLM-5.3 specifies output context (128,000 tokens).

Zhipu AI
GLM-5.3
Input1,000,000 tokens
Output128,000 tokens
Mistral AI
Ministral 3 (8B Base 2512)
Input- tokens
Output- tokens
Mon Aug 24 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Ministral 3 (8B Base 2512) supports multimodal inputs, whereas GLM-5.3 does not.

Ministral 3 (8B Base 2512) can handle both text and other forms of data like images, making it suitable for multimodal applications.

GLM-5.3

Text
Images
Audio
Video

Ministral 3 (8B Base 2512)

Text
Images
Audio
Video

Release Timeline

When each model was launched

GLM-5.3 was released on 2026-08-14, while Ministral 3 (8B Base 2512) was released on 2025-12-04.

GLM-5.3 is 8 months newer than Ministral 3 (8B Base 2512).

GLM-5.3

Aug 14, 2026

1 weeks ago

8mo newer
Ministral 3 (8B Base 2512)

Dec 4, 2025

8 months 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

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against GLM-5.3 and Ministral 3 (8B Base 2512) side-by-side, then vote on the output you prefer.

GLM-5.3
✓ Preferred
Ministral 3 (8B Base 2512)
Open in Playground

FAQ

Common questions about GLM-5.3 vs Ministral 3 (8B Base 2512).

Which is better, GLM-5.3 or Ministral 3 (8B Base 2512)?

GLM-5.3 (Zhipu AI) and Ministral 3 (8B Base 2512) (Mistral AI) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does GLM-5.3 compare to Ministral 3 (8B Base 2512) in benchmarks?

GLM-5.3 scores Terminal-Bench 2.1: 88.2%, CyberGym: 84.5%, FrontierSWE: 78.1%, Toolathlon: 73.0%, DeepSWE 1.1: 66.9%. Ministral 3 (8B Base 2512) scores MMLU-Redux: 79.3%, MMLU: 76.1%, Multilingual MMLU: 70.6%, TriviaQA: 68.1%, MATH (CoT): 62.6%.

What are the context window sizes for GLM-5.3 and Ministral 3 (8B Base 2512)?

GLM-5.3 supports 1.0M tokens and Ministral 3 (8B Base 2512) supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between GLM-5.3 and Ministral 3 (8B Base 2512)?

Key differences include multimodal support (no vs yes), licensing (Unknown vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-5.3 and Ministral 3 (8B Base 2512)?

GLM-5.3 is developed by Zhipu AI and Ministral 3 (8B Base 2512) is developed by Mistral AI.