Qwen3.5-397B-A17B vs Qwen3.5-0.8B Comparison

Comparing Qwen3.5-397B-A17B and Qwen3.5-0.8B across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

20 benchmarks

Qwen3.5-397B-A17B outperforms in 20 benchmarks (AA-LCR, BFCL-V4, C-Eval, Global PIQA, GPQA, IFBench, IFEval, Include, LongBench v2, MAXIFE, MMLU-Pro, MMLU-ProX, MMLU-Redux, MMMLU, Multi-Challenge, NOVA-63, PolyMATH, SuperGPQA, t2-bench, WMT24++), while Qwen3.5-0.8B is better at 0 benchmarks.

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

Tue Mar 17 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

Tue Mar 17 2026 • llm-stats.com

Qwen3.5-397B-A17B

Input tokens$0.60

Output tokens$3.60

Best providerNovita

Qwen3.5-0.8B

Input tokens$0.00

Output tokens$0.00

Best providerUnknown Organization

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Model Size

Parameter count comparison

396.2B diff

Qwen3.5-397B-A17B has 396.2B more parameters than Qwen3.5-0.8B, making it 49525.0% larger.

Qwen3.5-397B-A17B

397.0Bparameters

Qwen3.5-0.8B

0.8Bparameters

397.0B

Qwen3.5-397B-A17B

0.8B

Qwen3.5-0.8B

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

Qwen3.5-0.8B

Input- tokens

Output- tokens

Tue Mar 17 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Qwen3.5-397B-A17B and Qwen3.5-0.8B 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

Qwen3.5-0.8B

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

Qwen3.5-0.8B

Apache 2.0

Open weights

Release Timeline

When each model was launched

Qwen3.5-397B-A17B was released on 2026-02-16, while Qwen3.5-0.8B was released on 2026-03-02.

Qwen3.5-0.8B is 0 month newer than Qwen3.5-397B-A17B.

Qwen3.5-397B-A17B

Feb 16, 2026

4 weeks ago

Qwen3.5-0.8B

Mar 2, 2026

2 weeks ago

2w 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

Qwen3.5-397B-A17B

View details

Alibaba Cloud / Qwen Team

Larger context window (262,144 tokens)

Higher AA-LCR score (68.7% vs 4.7%)

Higher BFCL-V4 score (72.9% vs 25.3%)

Higher C-Eval score (93.0% vs 50.5%)

Higher Global PIQA score (89.8% vs 59.4%)

Higher GPQA score (88.4% vs 11.9%)

Higher IFBench score (76.5% vs 21.0%)

Higher IFEval score (92.6% vs 44.0%)

Higher Include score (85.6% vs 40.6%)

Higher LongBench v2 score (63.2% vs 26.1%)

Higher MAXIFE score (88.2% vs 39.2%)

Higher MMLU-Pro score (87.8% vs 42.3%)

Higher MMLU-ProX score (84.7% vs 34.6%)

Higher MMLU-Redux score (94.9% vs 59.5%)

Higher MMMLU score (88.5% vs 44.3%)

Higher Multi-Challenge score (67.6% vs 18.9%)

Higher NOVA-63 score (59.1% vs 42.4%)

Higher PolyMATH score (73.3% vs 8.2%)

Higher SuperGPQA score (70.4% vs 21.3%)

Higher t2-bench score (86.7% vs 11.6%)

Higher WMT24++ score (78.9% vs 27.2%)

Qwen3.5-0.8B

View details

Alibaba Cloud / Qwen Team

Detailed Comparison

AI Model Comparison Table
Feature	Qwen3.5-397B-A17B	Qwen3.5-0.8B