Qwen3.5-0.8B vs Qwen3.5-9B Comparison

Comparing Qwen3.5-0.8B and Qwen3.5-9B across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

20 benchmarks

Qwen3.5-0.8B outperforms in 0 benchmarks, while Qwen3.5-9B is better at 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++).

Qwen3.5-9B significantly outperforms across most benchmarks.

Sat Mar 14 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

Sat Mar 14 2026 • llm-stats.com

Qwen3.5-0.8B

Input tokens$0.00

Output tokens$0.00

Best providerUnknown Organization

Qwen3.5-9B

Input tokens$0.00

Output tokens$0.00

Best providerUnknown Organization

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Model Size

Parameter count comparison

8.2B diff

Qwen3.5-9B has 8.2B more parameters than Qwen3.5-0.8B, making it 1025.0% larger.

Qwen3.5-0.8B

0.8Bparameters

Qwen3.5-9B

9.0Bparameters

0.8B

Qwen3.5-0.8B

9.0B

Qwen3.5-9B

Input Capabilities

Supported data types and modalities

Both Qwen3.5-0.8B and Qwen3.5-9B support multimodal inputs.

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

Qwen3.5-0.8B

Text

Images

Audio

Video

Qwen3.5-9B

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.

Qwen3.5-0.8B

Apache 2.0

Open weights

Qwen3.5-9B

Apache 2.0

Open weights

Release Timeline

When each model was launched

Both models were released on 2026-03-02.

They likely represent similar generations of model development.

Qwen3.5-0.8B

Mar 2, 2026

1 weeks ago

Qwen3.5-9B

Mar 2, 2026

1 weeks 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

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Key Takeaways

Qwen3.5-0.8B

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Alibaba Cloud / Qwen Team

Qwen3.5-9B

View details

Alibaba Cloud / Qwen Team

Higher AA-LCR score (63.0% vs 4.7%)

Higher BFCL-V4 score (66.1% vs 25.3%)

Higher C-Eval score (88.2% vs 50.5%)

Higher Global PIQA score (83.2% vs 59.4%)

Higher GPQA score (81.7% vs 11.9%)

Higher IFBench score (64.5% vs 21.0%)

Higher IFEval score (91.5% vs 44.0%)

Higher Include score (75.6% vs 40.6%)

Higher LongBench v2 score (55.2% vs 26.1%)

Higher MAXIFE score (83.4% vs 39.2%)

Higher MMLU-Pro score (82.5% vs 42.3%)

Higher MMLU-ProX score (76.3% vs 34.6%)

Higher MMLU-Redux score (91.1% vs 59.5%)

Higher MMMLU score (81.2% vs 44.3%)

Higher Multi-Challenge score (54.5% vs 18.9%)

Higher NOVA-63 score (55.9% vs 42.4%)

Higher PolyMATH score (57.3% vs 8.2%)

Higher SuperGPQA score (58.2% vs 21.3%)

Higher t2-bench score (79.1% vs 11.6%)

Higher WMT24++ score (72.6% vs 27.2%)

Detailed Comparison

AI Model Comparison Table
Feature	Qwen3.5-0.8B	Qwen3.5-9B