Model Comparison

Qwen3.5-397B-A17B vs Qwen3 VL 32B Thinking

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

Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

9 benchmarks

Qwen3.5-397B-A17B outperforms in 9 benchmarks (GPQA, IFEval, Include, LiveCodeBench v6, MMLU-Pro, MMLU-ProX, MMLU-Redux, PolyMATH, SuperGPQA), while Qwen3 VL 32B Thinking is better at 0 benchmarks.

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

Thu Apr 16 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers

Thu Apr 16 2026 • llm-stats.com

Qwen3.5-397B-A17B

Input tokens$0.60

Output tokens$3.60

Best providerNovita

Qwen3 VL 32B Thinking

Input tokens$0.00

Output tokens$0.00

Best providerUnknown Organization

Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

364.0B diff

Qwen3.5-397B-A17B has 364.0B more parameters than Qwen3 VL 32B Thinking, making it 1103.0% larger.

Qwen3.5-397B-A17B

397.0Bparameters

Qwen3 VL 32B Thinking

33.0Bparameters

397.0B

Qwen3.5-397B-A17B

33.0B

Qwen3 VL 32B Thinking

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).

Qwen3.5-397B-A17B

Input262,144 tokens

Output64,000 tokens

Qwen3 VL 32B Thinking

Input- tokens

Output- tokens

Thu Apr 16 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Qwen3.5-397B-A17B and Qwen3 VL 32B Thinking 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 VL 32B Thinking

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 VL 32B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

Qwen3.5-397B-A17B was released on 2026-02-16, while Qwen3 VL 32B Thinking was released on 2025-09-22.

Qwen3.5-397B-A17B is 5 months newer than Qwen3 VL 32B Thinking.

Qwen3.5-397B-A17B

Feb 16, 2026

1 months ago

4mo newer

Qwen3 VL 32B Thinking

Sep 22, 2025

6 months 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

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Qwen3.5-397B-A17B

View details

Alibaba Cloud / Qwen Team

Larger context window (262,144 tokens)

Higher GPQA score (88.4% vs 73.1%)

Higher IFEval score (92.6% vs 87.8%)

Higher Include score (85.6% vs 76.3%)

Higher LiveCodeBench v6 score (83.6% vs 65.6%)

Higher MMLU-Pro score (87.8% vs 82.1%)

Higher MMLU-ProX score (84.7% vs 77.2%)

Higher MMLU-Redux score (94.9% vs 91.9%)

Higher PolyMATH score (73.3% vs 52.0%)

Higher SuperGPQA score (70.4% vs 59.0%)

Detailed Comparison

AI Model Comparison Table
Feature	Qwen3.5-397B-A17B	Qwen3 VL 32B Thinking

FAQ

Common questions about Qwen3.5-397B-A17B vs Qwen3 VL 32B Thinking

Qwen3.5-397B-A17B significantly outperforms across most benchmarks. Qwen3.5-397B-A17B is made by Alibaba Cloud / Qwen Team and Qwen3 VL 32B Thinking 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 VL 32B Thinking scores DocVQAtest: 96.1%, ScreenSpot: 95.7%, MMLU-Redux: 91.9%, MMBench-V1.1: 90.8%, CharXiv-D: 90.2%.

Qwen3.5-397B-A17B supports 262K tokens and Qwen3 VL 32B Thinking supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

Qwen3.5-397B-A17B vs Qwen3 VL 32B Thinking

Performance Benchmarks

Arena Performance

Pricing Analysis

Model Size

Context Window

Input Capabilities

Qwen3.5-397B-A17B

Qwen3 VL 32B Thinking

License

Release Timeline

Knowledge Cutoff

Outputs Comparison

Key Takeaways

Qwen3.5-397B-A17B

Qwen3 VL 32B Thinking

Detailed Comparison

FAQ

Which is better, Qwen3.5-397B-A17B or Qwen3 VL 32B Thinking?

How does Qwen3.5-397B-A17B compare to Qwen3 VL 32B Thinking in benchmarks?

What are the context window sizes for Qwen3.5-397B-A17B and Qwen3 VL 32B Thinking?