Model Comparison
Qwen3.6-27B vs Gemma 4 31BWhich is better in 2026?
Qwen3.6-27B shows notably better performance in the majority of benchmarks. Gemma 4 31B is 7.0x cheaper per token.
Verdict: Qwen3.6-27B vs Gemma 4 31B — which is better?
Qwen3.6-27B (by Alibaba Cloud / Qwen Team) and Gemma 4 31B (by Google) 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.
Qwen3.6-27B outperforms in 5 benchmarks (AIME 2026, GDPval-AA, GPQA, LiveCodeBench v6, MMLU-Pro), while Gemma 4 31B is better at 2 benchmarks (Humanity's Last Exam, MMMU-Pro). Qwen3.6-27B shows notably better performance in the majority of benchmarks.
On price, Gemma 4 31B is roughly 7.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Choose Qwen3.6-27B if…
- you want the strongest raw capability — it leads on 5 of 7 shared benchmarks
- you want the most recent training data — it shipped Apr 2026
Choose Gemma 4 31B if…
- cost matters — it's about 7.0x cheaper per token
Performance Benchmarks
Comparative analysis across standard metrics
Qwen3.6-27B outperforms in 5 benchmarks (AIME 2026, GDPval-AA, GPQA, LiveCodeBench v6, MMLU-Pro), while Gemma 4 31B is better at 2 benchmarks (Humanity's Last Exam, MMMU-Pro).
Qwen3.6-27B shows notably better performance in the majority of benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, Qwen3.6-27B ($0.60/1M tokens) is 4.6x more expensive than Gemma 4 31B ($0.13/1M tokens).
For output processing, Qwen3.6-27B ($3.60/1M tokens) is 9.5x more expensive than Gemma 4 31B ($0.38/1M tokens).
In conclusion, Qwen3.6-27B is more expensive than Gemma 4 31B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Gemma 4 31B has 2.9B more parameters than Qwen3.6-27B, making it 10.5% larger.
Context Window
Maximum input and output token capacity
Both models have the same input context window of 262,144 tokens. Gemma 4 31B can generate longer responses up to 131,072 tokens, while Qwen3.6-27B is limited to 65,536 tokens.
Input Capabilities
Supported data types and modalities
Both Qwen3.6-27B and Gemma 4 31B support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Qwen3.6-27B
Gemma 4 31B
License
Usage and distribution terms
Both models are licensed under Apache 2.0.
Both models share the same licensing terms, providing consistent usage rights.
Apache 2.0
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
Qwen3.6-27B was released on 2026-04-21, while Gemma 4 31B was released on 2026-04-02.
Qwen3.6-27B is 1 month newer than Gemma 4 31B.
Apr 21, 2026
2 months ago
2w newerApr 2, 2026
3 months ago
Knowledge Cutoff
When training data ends
Gemma 4 31B has a documented knowledge cutoff of 2025-01-01, while Qwen3.6-27B's cutoff date is not specified.
We can confirm Gemma 4 31B's training data extends to 2025-01-01, but cannot make a direct comparison without Qwen3.6-27B's cutoff date.
—
Jan 2025
Provider Availability
Qwen3.6-27B is available from Novita. Gemma 4 31B is available from DeepInfra, FriendliAI, Novita, Together.
Qwen3.6-27B
Gemma 4 31B
Outputs Comparison
Key Takeaways
Qwen3.6-27B
View detailsAlibaba Cloud / Qwen Team
Gemma 4 31B
View detailsDetailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against Qwen3.6-27B and Gemma 4 31B side-by-side, then vote on the output you prefer.
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FAQ
Common questions about Qwen3.6-27B vs Gemma 4 31B.