Model Comparison

Claude Haiku 4.5 vs Qwen3-Next-80B-A3B-Instruct

Claude Haiku 4.5 significantly outperforms across most benchmarks. Qwen3-Next-80B-A3B-Instruct is 4.1x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

5 benchmarks

Claude Haiku 4.5 outperforms in 5 benchmarks (AIME 2025, GPQA, Tau2 Airline, Tau2 Retail, Tau2 Telecom), while Qwen3-Next-80B-A3B-Instruct is better at 0 benchmarks.

Claude Haiku 4.5 significantly outperforms across most benchmarks.

Tue May 26 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Qwen3-Next-80B-A3B-Instruct costs less

For input processing, Claude Haiku 4.5 ($1.00/1M tokens) is 6.7x more expensive than Qwen3-Next-80B-A3B-Instruct ($0.15/1M tokens).

For output processing, Claude Haiku 4.5 ($5.00/1M tokens) is 3.3x more expensive than Qwen3-Next-80B-A3B-Instruct ($1.50/1M tokens).

In conclusion, Claude Haiku 4.5 is more expensive than Qwen3-Next-80B-A3B-Instruct.*

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

Lowest available price from all providers

Tue May 26 2026 • llm-stats.com

Claude Haiku 4.5

Input tokens$1.00

Output tokens$5.00

Best providerAnthropic

Qwen3-Next-80B-A3B-Instruct

Input tokens$0.15

Output tokens$1.50

Best providerNovita

Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

Claude Haiku 4.5 accepts 200,000 input tokens compared to Qwen3-Next-80B-A3B-Instruct's 65,536 tokens. Qwen3-Next-80B-A3B-Instruct can generate longer responses up to 65,536 tokens, while Claude Haiku 4.5 is limited to 64,000 tokens.

Claude Haiku 4.5

Input200,000 tokens

Output64,000 tokens

Qwen3-Next-80B-A3B-Instruct

Input65,536 tokens

Output65,536 tokens

Tue May 26 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Claude Haiku 4.5 supports multimodal inputs, whereas Qwen3-Next-80B-A3B-Instruct does not.

Claude Haiku 4.5 can handle both text and other forms of data like images, making it suitable for multimodal applications.

Claude Haiku 4.5

Text

Images

Audio

Video

Qwen3-Next-80B-A3B-Instruct

Text

Images

Audio

Video

License

Usage and distribution terms

Claude Haiku 4.5 is licensed under a proprietary license, while Qwen3-Next-80B-A3B-Instruct uses Apache 2.0.

License differences may affect how you can use these models in commercial or open-source projects.

Claude Haiku 4.5

Proprietary

Closed source

Qwen3-Next-80B-A3B-Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

Claude Haiku 4.5 was released on 2025-10-15, while Qwen3-Next-80B-A3B-Instruct was released on 2025-09-10.

Claude Haiku 4.5 is 1 month newer than Qwen3-Next-80B-A3B-Instruct.

Claude Haiku 4.5

Oct 15, 2025

7 months ago

1mo newer

Qwen3-Next-80B-A3B-Instruct

Sep 10, 2025

8 months ago

Knowledge Cutoff

When training data ends

Claude Haiku 4.5 has a documented knowledge cutoff of 2025-02-01, while Qwen3-Next-80B-A3B-Instruct's cutoff date is not specified.

We can confirm Claude Haiku 4.5's training data extends to 2025-02-01, but cannot make a direct comparison without Qwen3-Next-80B-A3B-Instruct's cutoff date.

Claude Haiku 4.5

Feb 2025

Qwen3-Next-80B-A3B-Instruct

—

Provider Availability

Claude Haiku 4.5 is available from Anthropic, Vertex AI. Qwen3-Next-80B-A3B-Instruct is available from Novita.

Claude Haiku 4.5

Anthropic

Input Price:Input: $1.00/1MOutput Price:Output: $5.00/1M

Unknown Organization

Input Price:Input: $1.00/1MOutput Price:Output: $5.00/1M

Qwen3-Next-80B-A3B-Instruct

Novita

Input Price:Input: $0.15/1MOutput Price:Output: $1.50/1M

* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Claude Haiku 4.5

View details

Anthropic

Larger context window (200,000 tokens)

Supports multimodal inputs

Higher AIME 2025 score (80.7% vs 69.5%)

Higher GPQA score (73.0% vs 72.9%)

Higher Tau2 Airline score (63.6% vs 45.5%)

Higher Tau2 Retail score (83.2% vs 57.3%)

Higher Tau2 Telecom score (83.0% vs 13.2%)

Qwen3-Next-80B-A3B-Instruct

View details

Alibaba Cloud / Qwen Team

Less expensive input tokens

Less expensive output tokens

Has open weights

Detailed Comparison

AI Model Comparison Table
Feature	Claude Haiku 4.5	Qwen3-Next-80B-A3B-Instruct

FAQ

Common questions about Claude Haiku 4.5 vs Qwen3-Next-80B-A3B-Instruct.

Which is better, Claude Haiku 4.5 or Qwen3-Next-80B-A3B-Instruct?

Claude Haiku 4.5 significantly outperforms across most benchmarks. Claude Haiku 4.5 is made by Anthropic and Qwen3-Next-80B-A3B-Instruct is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Claude Haiku 4.5 compare to Qwen3-Next-80B-A3B-Instruct in benchmarks?

Claude Haiku 4.5 scores Tau2 Retail: 83.2%, MMMLU: 83.0%, Tau2 Telecom: 83.0%, AIME 2025: 80.7%, SWE-Bench Verified: 73.3%. Qwen3-Next-80B-A3B-Instruct scores MMLU-Redux: 90.9%, MultiPL-E: 87.8%, IFEval: 87.6%, WritingBench: 87.3%, Creative Writing v3: 85.3%.

Is Claude Haiku 4.5 cheaper than Qwen3-Next-80B-A3B-Instruct?

Qwen3-Next-80B-A3B-Instruct is 6.7x cheaper for input tokens. Claude Haiku 4.5 costs $1.00/M input and $5.00/M output via anthropic. Qwen3-Next-80B-A3B-Instruct costs $0.15/M input and $1.50/M output via novita.

What are the context window sizes for Claude Haiku 4.5 and Qwen3-Next-80B-A3B-Instruct?

Claude Haiku 4.5 supports 200K tokens and Qwen3-Next-80B-A3B-Instruct supports 66K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Claude Haiku 4.5 and Qwen3-Next-80B-A3B-Instruct?

Key differences include context window (200K vs 66K), input pricing ($1.00 vs $0.15/M), multimodal support (yes vs no), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Claude Haiku 4.5 and Qwen3-Next-80B-A3B-Instruct?

Claude Haiku 4.5 is developed by Anthropic and Qwen3-Next-80B-A3B-Instruct is developed by Alibaba Cloud / Qwen Team.