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GLM-5.3 vs Magistral Small 2506

Comparing GLM-5.3 and Magistral Small 2506 across benchmarks, pricing, and capabilities.

Zhipu AI · Mistral AI · Updated for 2026

Which is better?

GLM-5.3 and Magistral Small 2506 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 Magistral Small 2506

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

At a glance

The differences that matter most.

GLM-5.3
Zhipu AI
Magistral Small 2506
Mistral AI
Benchmark wins
—
—
Input price
$1.40 / M
— / M
Output price
$4.40 / M
— / M
Context window
1,000,000
—
Released
Aug 2026
Jun 2025
License
Unknown
Apache 2.0

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

GLM-5.3 and Magistral Small 2506don'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

729.0B diff

GLM-5.3 has 729.0B more parameters than Magistral Small 2506, making it 3037.5% larger.

Zhipu AI
GLM-5.3
753.0Bparameters
Mistral AI
Magistral Small 2506
24.0Bparameters
753.0B
GLM-5.3
24.0B
Magistral Small 2506

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
Magistral Small 2506
Input- tokens
Output- tokens
Mon Aug 24 2026 • llm-stats.com

Release Timeline

When each model was launched

GLM-5.3 was released on 2026-08-14, while Magistral Small 2506 was released on 2025-06-10.

GLM-5.3 is 14 months newer than Magistral Small 2506.

GLM-5.3

Aug 14, 2026

1 weeks ago

1.2yr newer
Magistral Small 2506

Jun 10, 2025

1.2 years ago

Knowledge Cutoff

When training data ends

Magistral Small 2506 has a documented knowledge cutoff of 2025-06-01, while GLM-5.3's cutoff date is not specified.

We can confirm Magistral Small 2506's training data extends to 2025-06-01, but cannot make a direct comparison without GLM-5.3's cutoff date.

GLM-5.3

—

Magistral Small 2506

Jun 2025

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against GLM-5.3 and Magistral Small 2506 side-by-side, then vote on the output you prefer.

GLM-5.3
✓ Preferred
Magistral Small 2506
Open in Playground

FAQ

Common questions about GLM-5.3 vs Magistral Small 2506.

Which is better, GLM-5.3 or Magistral Small 2506?

GLM-5.3 (Zhipu AI) and Magistral Small 2506 (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 Magistral Small 2506 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%. Magistral Small 2506 scores AIME 2024: 70.7%, GPQA: 68.2%, AIME 2025: 62.8%, LiveCodeBench: 51.3%.

What are the context window sizes for GLM-5.3 and Magistral Small 2506?

GLM-5.3 supports 1.0M tokens and Magistral Small 2506 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 Magistral Small 2506?

Key differences include licensing (Unknown vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-5.3 and Magistral Small 2506?

GLM-5.3 is developed by Zhipu AI and Magistral Small 2506 is developed by Mistral AI.

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