Model Comparison

Gemma 3 27B vs Ministral 3 (14B Reasoning 2512)

Ministral 3 (14B Reasoning 2512) significantly outperforms across most benchmarks. Gemma 3 27B is 1.6x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

Gemma 3 27B outperforms in 0 benchmarks, while Ministral 3 (14B Reasoning 2512) is better at 2 benchmarks (GPQA, LiveCodeBench).

Ministral 3 (14B Reasoning 2512) significantly outperforms across most benchmarks.

Mon Jun 01 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Gemma 3 27B costs less

For input processing, Gemma 3 27B ($0.10/1M tokens) is 2.0x cheaper than Ministral 3 (14B Reasoning 2512) ($0.20/1M tokens).

For output processing, Gemma 3 27B ($0.20/1M tokens) costs the same as Ministral 3 (14B Reasoning 2512) ($0.20/1M tokens).

In conclusion, Ministral 3 (14B Reasoning 2512) is more expensive than Gemma 3 27B.*

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

Lowest available price from all providers
Mon Jun 01 2026 • llm-stats.com
Google
Gemma 3 27B
Input tokens$0.10
Output tokens$0.20
Best providerDeepinfra
Mistral AI
Ministral 3 (14B Reasoning 2512)
Input tokens$0.20
Output tokens$0.20
Best providerMistral
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

13.0B diff

Gemma 3 27B has 13.0B more parameters than Ministral 3 (14B Reasoning 2512), making it 92.9% larger.

Google
Gemma 3 27B
27.0Bparameters
Mistral AI
Ministral 3 (14B Reasoning 2512)
14.0Bparameters
27.0B
Gemma 3 27B
14.0B
Ministral 3 (14B Reasoning 2512)

Context Window

Maximum input and output token capacity

Ministral 3 (14B Reasoning 2512) accepts 262,100 input tokens compared to Gemma 3 27B's 131,072 tokens. Ministral 3 (14B Reasoning 2512) can generate longer responses up to 262,100 tokens, while Gemma 3 27B is limited to 131,072 tokens.

Google
Gemma 3 27B
Input131,072 tokens
Output131,072 tokens
Mistral AI
Ministral 3 (14B Reasoning 2512)
Input262,100 tokens
Output262,100 tokens
Mon Jun 01 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Gemma 3 27B and Ministral 3 (14B Reasoning 2512) support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

Gemma 3 27B

Text
Images
Audio
Video

Ministral 3 (14B Reasoning 2512)

Text
Images
Audio
Video

License

Usage and distribution terms

Gemma 3 27B is licensed under Gemma, while Ministral 3 (14B Reasoning 2512) uses Apache 2.0.

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

Gemma 3 27B

Gemma

Open weights

Ministral 3 (14B Reasoning 2512)

Apache 2.0

Open weights

Release Timeline

When each model was launched

Gemma 3 27B was released on 2025-03-12, while Ministral 3 (14B Reasoning 2512) was released on 2025-12-04.

Ministral 3 (14B Reasoning 2512) is 9 months newer than Gemma 3 27B.

Gemma 3 27B

Mar 12, 2025

1.2 years ago

Ministral 3 (14B Reasoning 2512)

Dec 4, 2025

5 months ago

8mo 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

Gemma 3 27B is available from DeepInfra, Novita. Ministral 3 (14B Reasoning 2512) is available from Mistral AI.

Gemma 3 27B

deepinfra logo
Deepinfra
Input Price:Input: $0.10/1MOutput Price:Output: $0.20/1M
novita logo
Novita
Input Price:Input: $0.11/1MOutput Price:Output: $0.20/1M

Ministral 3 (14B Reasoning 2512)

mistral logo
Mistral
Input Price:Input: $0.20/1MOutput Price:Output: $0.20/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Google
Less expensive input tokens
Mistral AI
Larger context window (262,100 tokens)
Higher GPQA score (71.2% vs 42.4%)
Higher LiveCodeBench score (64.6% vs 29.7%)

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemma 3 27B
Mistral AI
Ministral 3 (14B Reasoning 2512)

FAQ

Common questions about Gemma 3 27B vs Ministral 3 (14B Reasoning 2512).

Which is better, Gemma 3 27B or Ministral 3 (14B Reasoning 2512)?

Ministral 3 (14B Reasoning 2512) significantly outperforms across most benchmarks. Gemma 3 27B is made by Google and Ministral 3 (14B Reasoning 2512) is made by Mistral AI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Gemma 3 27B compare to Ministral 3 (14B Reasoning 2512) in benchmarks?

Gemma 3 27B scores GSM8k: 95.9%, IFEval: 90.4%, MATH: 89.0%, HumanEval: 87.8%, BIG-Bench Hard: 87.6%. Ministral 3 (14B Reasoning 2512) scores AIME 2024: 89.8%, AIME 2025: 85.0%, GPQA: 71.2%, LiveCodeBench: 64.6%.

Is Gemma 3 27B cheaper than Ministral 3 (14B Reasoning 2512)?

Gemma 3 27B is 2.0x cheaper for input tokens. Gemma 3 27B costs $0.10/M input and $0.20/M output via deepinfra. Ministral 3 (14B Reasoning 2512) costs $0.20/M input and $0.20/M output via mistral.

What are the context window sizes for Gemma 3 27B and Ministral 3 (14B Reasoning 2512)?

Gemma 3 27B supports 131K tokens and Ministral 3 (14B 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 Gemma 3 27B and Ministral 3 (14B Reasoning 2512)?

Key differences include context window (131K vs 262K), input pricing ($0.10 vs $0.20/M), licensing (Gemma vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemma 3 27B and Ministral 3 (14B Reasoning 2512)?

Gemma 3 27B is developed by Google and Ministral 3 (14B Reasoning 2512) is developed by Mistral AI.