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Model Comparison

Qwen3.5-397B-A17B vs Qwen3.6-27B

Qwen3.5-397B-A17B shows notably better performance in the majority of benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

14 benchmarks

Qwen3.5-397B-A17B outperforms in 9 benchmarks (C-Eval, GPQA, HMMT 2025, HMMT25, Humanity's Last Exam, IMO-AnswerBench, MMLU-Pro, MMLU-Redux, SuperGPQA), while Qwen3.6-27B is better at 5 benchmarks (AIME 2026, LiveCodeBench v6, SWE-bench Multilingual, SWE-Bench Verified, Terminal-Bench 2.0).

Qwen3.5-397B-A17B shows notably better performance in the majority of benchmarks.

Thu Apr 23 2026 • llm-stats.com

Arena Performance

Human preference votes

CallingBox

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Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Thu Apr 23 2026 • llm-stats.com
Alibaba Cloud / Qwen Team
Qwen3.5-397B-A17B
Input tokens$0.60
Output tokens$3.60
Best providerNovita
Alibaba Cloud / Qwen Team
Qwen3.6-27B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
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Model Size

Parameter count comparison

369.2B diff

Qwen3.5-397B-A17B has 369.2B more parameters than Qwen3.6-27B, making it 1329.0% larger.

Alibaba Cloud / Qwen Team
Qwen3.5-397B-A17B
397.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3.6-27B
27.8Bparameters
397.0B
Qwen3.5-397B-A17B
27.8B
Qwen3.6-27B

Context Window

Maximum input and output token capacity

Only Qwen3.5-397B-A17B specifies input context (262,144 tokens). Only Qwen3.5-397B-A17B specifies output context (64,000 tokens).

Alibaba Cloud / Qwen Team
Qwen3.5-397B-A17B
Input262,144 tokens
Output64,000 tokens
Alibaba Cloud / Qwen Team
Qwen3.6-27B
Input- tokens
Output- tokens
Thu Apr 23 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Qwen3.5-397B-A17B and Qwen3.6-27B 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

Qwen3.6-27B

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

Qwen3.6-27B

Apache 2.0

Open weights

Release Timeline

When each model was launched

Qwen3.5-397B-A17B was released on 2026-02-16, while Qwen3.6-27B was released on 2026-04-21.

Qwen3.6-27B is 2 months newer than Qwen3.5-397B-A17B.

Qwen3.5-397B-A17B

Feb 16, 2026

2 months ago

Qwen3.6-27B

Apr 21, 2026

2 days ago

2mo 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

Outputs Comparison

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Key Takeaways

Alibaba Cloud / Qwen Team

Qwen3.5-397B-A17B

View details

Alibaba Cloud / Qwen Team

Larger context window (262,144 tokens)
Higher C-Eval score (93.0% vs 91.4%)
Higher GPQA score (88.4% vs 87.8%)
Higher HMMT 2025 score (94.8% vs 93.8%)
Higher HMMT25 score (92.7% vs 90.7%)
Higher Humanity's Last Exam score (28.7% vs 24.0%)
Higher IMO-AnswerBench score (80.9% vs 80.8%)
Higher MMLU-Pro score (87.8% vs 86.2%)
Higher MMLU-Redux score (94.9% vs 93.5%)
Higher SuperGPQA score (70.4% vs 66.0%)
Alibaba Cloud / Qwen Team

Qwen3.6-27B

View details

Alibaba Cloud / Qwen Team

Higher AIME 2026 score (94.1% vs 91.3%)
Higher LiveCodeBench v6 score (83.9% vs 83.6%)
Higher SWE-bench Multilingual score (71.3% vs 69.3%)
Higher SWE-Bench Verified score (77.2% vs 76.4%)
Higher Terminal-Bench 2.0 score (59.3% vs 52.5%)

Detailed Comparison

AI Model Comparison Table
Feature
Alibaba Cloud / Qwen Team
Qwen3.5-397B-A17B
Alibaba Cloud / Qwen Team
Qwen3.6-27B

FAQ

Common questions about Qwen3.5-397B-A17B vs Qwen3.6-27B

Qwen3.5-397B-A17B shows notably better performance in the majority of benchmarks. Qwen3.5-397B-A17B is made by Alibaba Cloud / Qwen Team and Qwen3.6-27B is made by Alibaba Cloud / Qwen Team. 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%. Qwen3.6-27B scores CountBench: 97.8%, VLMsAreBlind: 97.0%, V*: 94.7%, AIME 2026: 94.1%, HMMT 2025: 93.8%.
Qwen3.5-397B-A17B supports 262K tokens and Qwen3.6-27B supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.