GLM-5.3 vs Ministral 3 (14B Reasoning 2512)
Comparing GLM-5.3 and Ministral 3 (14B Reasoning 2512) across benchmarks, pricing, and capabilities.
Zhipu AI · Mistral AI · Updated for 2026
Which is better?
GLM-5.3 and Ministral 3 (14B Reasoning 2512) trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, Ministral 3 (14B Reasoning 2512) is roughly 10.7x 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-5.3
- you process long inputs — it offers a 1,000,000 token context window
- you want the most recent training data — it shipped Aug 2026
Choose Ministral 3 (14B Reasoning 2512)
- cost matters — it's about 10.7x cheaper per token
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
GLM-5.3 and Ministral 3 (14B Reasoning 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
Pricing Analysis
Price comparison per million tokens
For input processing, GLM-5.3 ($1.40/1M tokens) is 7.0x more expensive than Ministral 3 (14B Reasoning 2512) ($0.20/1M tokens).
For output processing, GLM-5.3 ($4.40/1M tokens) is 22.0x more expensive than Ministral 3 (14B Reasoning 2512) ($0.20/1M tokens).
In conclusion, GLM-5.3 is more expensive than Ministral 3 (14B Reasoning 2512).*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
GLM-5.3 has 739.0B more parameters than Ministral 3 (14B Reasoning 2512), making it 5278.6% larger.
Context Window
Maximum input and output token capacity
GLM-5.3 accepts 1,000,000 input tokens compared to Ministral 3 (14B Reasoning 2512)'s 262,100 tokens. Ministral 3 (14B Reasoning 2512) can generate longer responses up to 262,100 tokens, while GLM-5.3 is limited to 128,000 tokens.
Input Capabilities
Supported data types and modalities
Ministral 3 (14B Reasoning 2512) supports multimodal inputs, whereas GLM-5.3 does not.
Ministral 3 (14B Reasoning 2512) can handle both text and other forms of data like images, making it suitable for multimodal applications.
GLM-5.3
Ministral 3 (14B Reasoning 2512)
Release Timeline
When each model was launched
GLM-5.3 was released on 2026-08-14, while Ministral 3 (14B Reasoning 2512) was released on 2025-12-04.
GLM-5.3 is 8 months newer than Ministral 3 (14B Reasoning 2512).
Aug 14, 2026
1 weeks ago
8mo newerDec 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.
Provider Availability
GLM-5.3 is available from ZAI. Ministral 3 (14B Reasoning 2512) is available from Mistral AI.
GLM-5.3
Ministral 3 (14B Reasoning 2512)
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-5.3 and Ministral 3 (14B Reasoning 2512) side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-5.3 vs Ministral 3 (14B Reasoning 2512).
Related comparisons
More GLM-5.3 comparisons
More Ministral 3 (14B Reasoning 2512) comparisons
- Ministral 3 (14B Reasoning 2512) vs DeepSeek-V4-Flash-Vision-Exp
- Ministral 3 (14B Reasoning 2512) vs Qwen3.8-27B
- Ministral 3 (14B Reasoning 2512) vs DeepSeek-V4-Pro-0813
- Ministral 3 (14B Reasoning 2512) vs Gemini 3.7 Flash
- Ministral 3 (14B Reasoning 2512) vs Grok 4.6
- Ministral 3 (14B Reasoning 2512) vs LFM2.5-VL-3B