Model Comparison

Gemma 3 27B vs Qwen2.5 72B Instruct

Both models are evenly matched across the benchmarks. Gemma 3 27B is 2.9x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

8 benchmarks

Gemma 3 27B outperforms in 4 benchmarks (GSM8k, HumanEval, IFEval, MATH), while Qwen2.5 72B Instruct is better at 4 benchmarks (GPQA, LiveCodeBench, MBPP, MMLU-Pro).

Both models are evenly matched across the benchmarks.

Tue Apr 14 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 3.5x cheaper than Qwen2.5 72B Instruct ($0.35/1M tokens).

For output processing, Gemma 3 27B ($0.20/1M tokens) is 2.0x cheaper than Qwen2.5 72B Instruct ($0.40/1M tokens).

In conclusion, Qwen2.5 72B Instruct is more expensive than Gemma 3 27B.*

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

Lowest available price from all providers
Tue Apr 14 2026 • llm-stats.com
Google
Gemma 3 27B
Input tokens$0.10
Output tokens$0.20
Best providerDeepinfra
Alibaba Cloud / Qwen Team
Qwen2.5 72B Instruct
Input tokens$0.35
Output tokens$0.40
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

45.7B diff

Qwen2.5 72B Instruct has 45.7B more parameters than Gemma 3 27B, making it 169.3% larger.

Google
Gemma 3 27B
27.0Bparameters
Alibaba Cloud / Qwen Team
Qwen2.5 72B Instruct
72.7Bparameters
27.0B
Gemma 3 27B
72.7B
Qwen2.5 72B Instruct

Context Window

Maximum input and output token capacity

Both models have the same input context window of 131,072 tokens. Gemma 3 27B can generate longer responses up to 131,072 tokens, while Qwen2.5 72B Instruct is limited to 8,192 tokens.

Google
Gemma 3 27B
Input131,072 tokens
Output131,072 tokens
Alibaba Cloud / Qwen Team
Qwen2.5 72B Instruct
Input131,072 tokens
Output8,192 tokens
Tue Apr 14 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemma 3 27B supports multimodal inputs, whereas Qwen2.5 72B Instruct does not.

Gemma 3 27B can handle both text and other forms of data like images, making it suitable for multimodal applications.

Gemma 3 27B

Text
Images
Audio
Video

Qwen2.5 72B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

Gemma 3 27B is licensed under Gemma, while Qwen2.5 72B Instruct uses Qwen.

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

Gemma 3 27B

Gemma

Open weights

Qwen2.5 72B Instruct

Qwen

Open weights

Release Timeline

When each model was launched

Gemma 3 27B was released on 2025-03-12, while Qwen2.5 72B Instruct was released on 2024-09-19.

Gemma 3 27B is 6 months newer than Qwen2.5 72B Instruct.

Gemma 3 27B

Mar 12, 2025

1.1 years ago

5mo newer
Qwen2.5 72B Instruct

Sep 19, 2024

1.6 years 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

Gemma 3 27B is available from DeepInfra, Novita. Qwen2.5 72B Instruct is available from DeepInfra, Hyperbolic, Fireworks, Together.

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

Qwen2.5 72B Instruct

deepinfra logo
Deepinfra
Input Price:Input: $0.35/1MOutput Price:Output: $0.40/1M
hyperbolic logo
Hyperbolic
Input Price:Input: $0.40/1MOutput Price:Output: $0.40/1M
fireworks logo
Fireworks
Input Price:Input: $0.89/1MOutput Price:Output: $0.89/1M
together logo
Together
Input Price:Input: $1.20/1MOutput Price:Output: $1.20/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Google
Supports multimodal inputs
Less expensive input tokens
Less expensive output tokens
Higher GSM8k score (95.9% vs 95.8%)
Higher HumanEval score (87.8% vs 86.6%)
Higher IFEval score (90.4% vs 84.1%)
Higher MATH score (89.0% vs 83.1%)
Alibaba Cloud / Qwen Team

Qwen2.5 72B Instruct

View details

Alibaba Cloud / Qwen Team

Higher GPQA score (49.0% vs 42.4%)
Higher LiveCodeBench score (55.5% vs 29.7%)
Higher MBPP score (88.2% vs 74.4%)
Higher MMLU-Pro score (71.1% vs 67.5%)

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemma 3 27B
Alibaba Cloud / Qwen Team
Qwen2.5 72B Instruct

FAQ

Common questions about Gemma 3 27B vs Qwen2.5 72B Instruct

Both models are evenly matched across the benchmarks. Gemma 3 27B is made by Google and Qwen2.5 72B Instruct is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
Gemma 3 27B scores GSM8k: 95.9%, IFEval: 90.4%, MATH: 89.0%, HumanEval: 87.8%, BIG-Bench Hard: 87.6%. Qwen2.5 72B Instruct scores GSM8k: 95.8%, MT-Bench: 93.5%, MBPP: 88.2%, MMLU-Redux: 86.8%, HumanEval: 86.6%.
Gemma 3 27B is 3.5x cheaper for input tokens. Gemma 3 27B costs $0.10/M input and $0.20/M output via deepinfra. Qwen2.5 72B Instruct costs $0.35/M input and $0.40/M output via deepinfra.
Gemma 3 27B supports 131K tokens and Qwen2.5 72B Instruct supports 131K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include input pricing ($0.10 vs $0.35/M), multimodal support (yes vs no), licensing (Gemma vs Qwen). See the full comparison above for benchmark-by-benchmark results.
Gemma 3 27B is developed by Google and Qwen2.5 72B Instruct is developed by Alibaba Cloud / Qwen Team.