Claude 3.5 Haiku vs Qwen2.5-Coder 7B Instruct Comparison

Comparing Claude 3.5 Haiku and Qwen2.5-Coder 7B Instruct across benchmarks, pricing, and capabilities.

Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

Claude 3.5 Haiku outperforms in 2 benchmarks (MATH, MMLU-Pro), while Qwen2.5-Coder 7B Instruct is better at 1 benchmark (HumanEval).

Claude 3.5 Haiku shows notably better performance in the majority of benchmarks.

Mon Mar 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
Mon Mar 16 2026 • llm-stats.com
Anthropic
Claude 3.5 Haiku
Input tokens$0.80
Output tokens$4.00
Best providerAWS Bedrock
Alibaba Cloud / Qwen Team
Qwen2.5-Coder 7B Instruct
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
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Context Window

Maximum input and output token capacity

Only Claude 3.5 Haiku specifies input context (200,000 tokens). Only Claude 3.5 Haiku specifies output context (200,000 tokens).

Anthropic
Claude 3.5 Haiku
Input200,000 tokens
Output200,000 tokens
Alibaba Cloud / Qwen Team
Qwen2.5-Coder 7B Instruct
Input- tokens
Output- tokens
Mon Mar 16 2026 • llm-stats.com

License

Usage and distribution terms

Claude 3.5 Haiku is licensed under a proprietary license, while Qwen2.5-Coder 7B Instruct uses Apache 2.0.

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

Claude 3.5 Haiku

Proprietary

Closed source

Qwen2.5-Coder 7B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

Claude 3.5 Haiku was released on 2024-10-22, while Qwen2.5-Coder 7B Instruct was released on 2024-09-19.

Claude 3.5 Haiku is 1 month newer than Qwen2.5-Coder 7B Instruct.

Claude 3.5 Haiku

Oct 22, 2024

1.4 years ago

1mo newer
Qwen2.5-Coder 7B Instruct

Sep 19, 2024

1.5 years 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

Larger context window (200,000 tokens)
Higher MATH score (69.4% vs 46.6%)
Higher MMLU-Pro score (65.0% vs 40.1%)
Alibaba Cloud / Qwen Team

Qwen2.5-Coder 7B Instruct

View details

Alibaba Cloud / Qwen Team

Has open weights
Higher HumanEval score (88.4% vs 88.1%)

Detailed Comparison

AI Model Comparison Table
Feature
Anthropic
Claude 3.5 Haiku
Alibaba Cloud / Qwen Team
Qwen2.5-Coder 7B Instruct