Model Comparison

Qwen3.5-397B-A17B vs Gemma 4 31B

Qwen3.5-397B-A17B significantly outperforms across most benchmarks. Gemma 4 31B is 6.6x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

7 benchmarks

Qwen3.5-397B-A17B outperforms in 7 benchmarks (AIME 2026, GPQA, Humanity's Last Exam, LiveCodeBench v6, MMLU-Pro, MMMLU, t2-bench), while Gemma 4 31B is better at 0 benchmarks.

Qwen3.5-397B-A17B significantly outperforms across most benchmarks.

Sat Apr 18 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Gemma 4 31B costs less

For input processing, Qwen3.5-397B-A17B ($0.60/1M tokens) is 4.3x more expensive than Gemma 4 31B ($0.14/1M tokens).

For output processing, Qwen3.5-397B-A17B ($3.60/1M tokens) is 9.0x more expensive than Gemma 4 31B ($0.40/1M tokens).

In conclusion, Qwen3.5-397B-A17B is more expensive than Gemma 4 31B.*

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

Lowest available price from all providers

Sat Apr 18 2026 • llm-stats.com

Qwen3.5-397B-A17B

Input tokens$0.60

Output tokens$3.60

Best providerNovita

Gemma 4 31B

Input tokens$0.14

Output tokens$0.40

Best providerNovita

Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

366.3B diff

Qwen3.5-397B-A17B has 366.3B more parameters than Gemma 4 31B, making it 1193.2% larger.

Qwen3.5-397B-A17B

397.0Bparameters

Gemma 4 31B

30.7Bparameters

397.0B

Qwen3.5-397B-A17B

30.7B

Gemma 4 31B

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 Qwen3.5-397B-A17B is limited to 64,000 tokens.

Qwen3.5-397B-A17B

Input262,144 tokens

Output64,000 tokens

Gemma 4 31B

Input262,144 tokens

Output131,072 tokens

Sat Apr 18 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Qwen3.5-397B-A17B and Gemma 4 31B support multimodal inputs.

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

Qwen3.5-397B-A17B

Text

Images

Audio

Video

Gemma 4 31B

Text

Images

Audio

Video

License

Usage and distribution terms

Both models are licensed under Apache 2.0.

Both models share the same licensing terms, providing consistent usage rights.

Qwen3.5-397B-A17B

Apache 2.0

Open weights

Gemma 4 31B

Apache 2.0

Open weights

Release Timeline

When each model was launched

Qwen3.5-397B-A17B was released on 2026-02-16, while Gemma 4 31B was released on 2026-04-02.

Gemma 4 31B is 2 months newer than Qwen3.5-397B-A17B.

Qwen3.5-397B-A17B

Feb 16, 2026

2 months ago

Gemma 4 31B

Apr 2, 2026

2 weeks ago

1mo newer

Knowledge Cutoff

When training data ends

Gemma 4 31B has a documented knowledge cutoff of 2025-01-01, while Qwen3.5-397B-A17B'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 Qwen3.5-397B-A17B's cutoff date.

Qwen3.5-397B-A17B

—

Gemma 4 31B

Jan 2025

Provider Availability

Qwen3.5-397B-A17B is available from Novita. Gemma 4 31B is available from Novita.

Qwen3.5-397B-A17B

Novita

Input Price:Input: $0.60/1MOutput Price:Output: $3.60/1M

Gemma 4 31B

Novita

Input Price:Input: $0.14/1MOutput Price:Output: $0.40/1M

* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Qwen3.5-397B-A17B

View details

Alibaba Cloud / Qwen Team

Higher AIME 2026 score (91.3% vs 89.2%)

Higher GPQA score (88.4% vs 84.3%)

Higher Humanity's Last Exam score (28.7% vs 26.5%)

Higher LiveCodeBench v6 score (83.6% vs 80.0%)

Higher MMLU-Pro score (87.8% vs 85.2%)

Higher MMMLU score (88.5% vs 88.4%)

Higher t2-bench score (86.7% vs 86.4%)

Gemma 4 31B

View details

Google

Less expensive input tokens

Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature	Qwen3.5-397B-A17B	Gemma 4 31B

FAQ

Common questions about Qwen3.5-397B-A17B vs Gemma 4 31B

Qwen3.5-397B-A17B significantly outperforms across most benchmarks. Qwen3.5-397B-A17B is made by Alibaba Cloud / Qwen Team and Gemma 4 31B is made by Google. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

Qwen3.5-397B-A17B scores MMLU-Redux: 94.9%, HMMT 2025: 94.8%, C-Eval: 93.0%, HMMT25: 92.7%, IFEval: 92.6%. Gemma 4 31B scores AIME 2026: 89.2%, MMMLU: 88.4%, t2-bench: 86.4%, MathVision: 85.6%, MMLU-Pro: 85.2%.

Gemma 4 31B is 4.3x cheaper for input tokens. Qwen3.5-397B-A17B costs $0.60/M input and $3.60/M output via novita. Gemma 4 31B costs $0.14/M input and $0.40/M output via novita.

Qwen3.5-397B-A17B supports 262K tokens and Gemma 4 31B supports 262K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

Key differences include input pricing ($0.60 vs $0.14/M). See the full comparison above for benchmark-by-benchmark results.

Qwen3.5-397B-A17B is developed by Alibaba Cloud / Qwen Team and Gemma 4 31B is developed by Google.

Qwen3.5-397B-A17B vs Gemma 4 31B

Performance Benchmarks

Arena Performance

Pricing Analysis

Model Size

Context Window

Input Capabilities

Qwen3.5-397B-A17B

Gemma 4 31B

License

Release Timeline

Knowledge Cutoff

Provider Availability

Qwen3.5-397B-A17B

Gemma 4 31B

Outputs Comparison

Key Takeaways

Qwen3.5-397B-A17B

Gemma 4 31B

Detailed Comparison

FAQ

Which is better, Qwen3.5-397B-A17B or Gemma 4 31B?

How does Qwen3.5-397B-A17B compare to Gemma 4 31B in benchmarks?

Is Qwen3.5-397B-A17B cheaper than Gemma 4 31B?

What are the context window sizes for Qwen3.5-397B-A17B and Gemma 4 31B?

What are the main differences between Qwen3.5-397B-A17B and Gemma 4 31B?

Who makes Qwen3.5-397B-A17B and Gemma 4 31B?