Model Comparison

GLM-5 vs Ministral 3 (8B Reasoning 2512)Which is better in 2026?

Comparing GLM-5 and Ministral 3 (8B Reasoning 2512) across benchmarks, pricing, and capabilities.

Verdict: GLM-5 vs Ministral 3 (8B Reasoning 2512) — which is better?

GLM-5 (by Zhipu AI) and Ministral 3 (8B Reasoning 2512) (by Mistral AI) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

On price, Ministral 3 (8B Reasoning 2512) is roughly 10.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Ministral 3 (8B Reasoning 2512) also accepts a larger context window (262,100 input tokens), making it the stronger choice for long documents and large codebases.

Choose GLM-5 if…

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

Choose Ministral 3 (8B Reasoning 2512) if…

  • cost matters — it's about 10.3x cheaper per token
  • you process long inputs — it offers a 262,100 token context window
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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

GLM-5 and Ministral 3 (8B Reasoning 2512)don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Ministral 3 (8B Reasoning 2512) costs less

For input processing, GLM-5 ($1.00/1M tokens) is 6.7x more expensive than Ministral 3 (8B Reasoning 2512) ($0.15/1M tokens).

For output processing, GLM-5 ($3.20/1M tokens) is 21.3x more expensive than Ministral 3 (8B Reasoning 2512) ($0.15/1M tokens).

In conclusion, GLM-5 is more expensive than Ministral 3 (8B Reasoning 2512).*

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

Lowest available price from all providers
Tue Jun 23 2026 • llm-stats.com
Zhipu AI
GLM-5
Input tokens$1.00
Output tokens$3.20
Best providerFriendliAI
Mistral AI
Ministral 3 (8B Reasoning 2512)
Input tokens$0.15
Output tokens$0.15
Best providerMistral
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

736.0B diff

GLM-5 has 736.0B more parameters than Ministral 3 (8B Reasoning 2512), making it 9200.0% larger.

Zhipu AI
GLM-5
744.0Bparameters
Mistral AI
Ministral 3 (8B Reasoning 2512)
8.0Bparameters
744.0B
GLM-5
8.0B
Ministral 3 (8B Reasoning 2512)

Context Window

Maximum input and output token capacity

Ministral 3 (8B Reasoning 2512) accepts 262,100 input tokens compared to GLM-5's 200,000 tokens. Ministral 3 (8B Reasoning 2512) can generate longer responses up to 262,100 tokens, while GLM-5 is limited to 128,000 tokens.

Zhipu AI
GLM-5
Input200,000 tokens
Output128,000 tokens
Mistral AI
Ministral 3 (8B Reasoning 2512)
Input262,100 tokens
Output262,100 tokens
Tue Jun 23 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Ministral 3 (8B Reasoning 2512) supports multimodal inputs, whereas GLM-5 does not.

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

GLM-5

Text
Images
Audio
Video

Ministral 3 (8B Reasoning 2512)

Text
Images
Audio
Video

License

Usage and distribution terms

GLM-5 is licensed under MIT, while Ministral 3 (8B Reasoning 2512) uses Apache 2.0.

License differences may affect how you can use these models in commercial or open-source projects.

GLM-5

MIT

Open weights

Ministral 3 (8B Reasoning 2512)

Apache 2.0

Open weights

Release Timeline

When each model was launched

GLM-5 was released on 2026-02-11, while Ministral 3 (8B Reasoning 2512) was released on 2025-12-04.

GLM-5 is 2 months newer than Ministral 3 (8B Reasoning 2512).

GLM-5

Feb 11, 2026

4 months ago

2mo newer
Ministral 3 (8B Reasoning 2512)

Dec 4, 2025

6 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

Provider Availability

GLM-5 is available from FriendliAI, ZAI. Ministral 3 (8B Reasoning 2512) is available from Mistral AI.

GLM-5

friendli logo
FriendliAI
Input Price:Input: $1.00/1MOutput Price:Output: $3.20/1M
z logo
Unknown Organization
Input Price:Input: $1.00/1MOutput Price:Output: $3.20/1M

Ministral 3 (8B Reasoning 2512)

mistral logo
Mistral
Input Price:Input: $0.15/1MOutput Price:Output: $0.15/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Zhipu AI

No standout differentiators in the data we have for this pair.

Mistral AI
Larger context window (262,100 tokens)
Supports multimodal inputs
Less expensive input tokens
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
Zhipu AI
GLM-5
Mistral AI
Ministral 3 (8B Reasoning 2512)

FAQ

Common questions about GLM-5 vs Ministral 3 (8B Reasoning 2512).

Which is better, GLM-5 or Ministral 3 (8B Reasoning 2512)?

GLM-5 (Zhipu AI) and Ministral 3 (8B Reasoning 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 compare to Ministral 3 (8B Reasoning 2512) in benchmarks?

GLM-5 scores t2-bench: 89.7%, SWE-Bench Verified: 77.8%, BrowseComp: 75.9%, MCP Atlas: 67.8%, Terminal-Bench 2.0: 56.2%. Ministral 3 (8B Reasoning 2512) scores AIME 2024: 86.0%, AIME 2025: 78.7%, GPQA: 66.8%, LiveCodeBench: 61.6%.

Is GLM-5 cheaper than Ministral 3 (8B Reasoning 2512)?

Ministral 3 (8B Reasoning 2512) is 6.7x cheaper for input tokens. GLM-5 costs $1.00/M input and $3.20/M output via friendli. Ministral 3 (8B Reasoning 2512) costs $0.15/M input and $0.15/M output via mistral.

What are the context window sizes for GLM-5 and Ministral 3 (8B Reasoning 2512)?

GLM-5 supports 200K tokens and Ministral 3 (8B Reasoning 2512) supports 262K 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 and Ministral 3 (8B Reasoning 2512)?

Key differences include context window (200K vs 262K), input pricing ($1.00 vs $0.15/M), multimodal support (no vs yes), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-5 and Ministral 3 (8B Reasoning 2512)?

GLM-5 is developed by Zhipu AI and Ministral 3 (8B Reasoning 2512) is developed by Mistral AI.

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