whichLlmmodel
Back to Dashboard

Alibaba Cloud (Qwen)Qwen3.6-35B-A3BVSAnthropicClaude Haiku 4.5

Analysis by:the whichllmmodel Editorial Team|Updated: June 2026

Our Take

We recommend Qwen3.6-35B-A3B over Claude Haiku 4.5 because it holds a clear reasoning lead. Choose Qwen3.6-35B-A3B for offline data control and complex codebases, multi-file repositories, and architectural planning, or Claude Haiku 4.5 only if you prefer using a cloud-hosted API setup for multi-file code and clearly defined tasks.
▶WHY?
Benchmark Calculations & Evidence:
  • Reasoning Accuracy: Both models were evaluated on the GPQA Diamond benchmark. Qwen3.6-35B-A3B scored 86%, while Claude Haiku 4.5 scored 73% (+13.0% gap).
  • Coding Performance: Evaluated on different benchmarks. Qwen3.6-35B-A3B scored 49.5% on SWE-bench Pro (complex codebases, multi-file repositories, and architectural planning), while Claude Haiku 4.5 scored 73.3% on SWE-bench Verified (multi-file code and clearly defined tasks).
  • Hosting Model: Qwen3.6-35B-A3B runs locally for $0 API costs, while Claude Haiku 4.5 is hosted via a cloud-hosted API setup.
    • Was this recommendation helpful?
    Model Specs

    Qwen3.6-35B-A3B

    Open Source
    🤗HF

    Benchmarks & Scores

    Coding (swe-bench-pro)
    49.5%

    complex codebases, multi-file repositories, and architectural planning

    Reasoning (gpqa-diamond)Winner (+13.0%)
    86%

    graduate-level science QA

    Cost & Context

    Cost (per 1M tokens)
    Self HostLocal execution (zero API fees)
    Context WindowLarger
    262.14k tokens
    Model Specs

    Claude Haiku 4.5

    Website

    Benchmarks & Scores

    Coding (swe-bench-verified)
    73.3%

    multi-file code and clearly defined tasks

    Reasoning (gpqa-diamond)
    73%

    graduate-level science QA

    Cost & Context

    Cost (per 1M tokens)
    $2.00Input: $1.00 | Output: $5.00
    Context Window
    200k tokens
    Read our data collection methodology

    Frequently Asked Questions about Qwen3.6-35B-A3B vs Claude Haiku 4.5

    For coding tasks, Qwen3.6-35B-A3B scores 49.5% on swe-bench-pro (complex codebases, multi-file repositories, and architectural planning), while Claude Haiku 4.5 scores 73.3% on swe-bench-verified (multi-file code and clearly defined tasks).

    Related Matchups

    Explore similar comparisons for Qwen3.6-35B-A3B and Claude Haiku 4.5.

    Browse More Comparisons
    Alibaba Cloud (Qwen)Qwen3.6-35B-A3B
    VS
    OpenAIGPT-5.5
    Compare Specs
    AnthropicClaude Haiku 4.5
    VS
    OpenAIGPT-5.6 Sol
    Compare Specs
    Alibaba Cloud (Qwen)Qwen3.6-35B-A3B
    VS
    OpenAIGPT-5.6 Terra
    Compare Specs

    Do you want to find a model for your constraints?

    Use our interactive model finder to filter LLMs by reasoning capability, coding performance, cost, and context length.

    Open Model Finder