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Yi-1.5 34BvsYi-Large

01.AI vs 01.AI — Side-by-side model comparison

Tied — both models win in equal categories

Head-to-Head Comparison

MetricYi-1.5 34BYi-Large
Provider
Arena Rank
Context Window
4K
32K
Input Pricing
Free (open)/1M tokens
Undisclosed/1M tokens
Output Pricing
Free (open)/1M tokens
Undisclosed/1M tokens
Parameters
34B
Undisclosed
Open Source
Yes
No
Best For
Bilingual tasks, fine-tuning, research
Complex reasoning, multilingual, analysis
Release Date
May 13, 2024
May 13, 2024

Yi-1.5 34B

Yi-1.5 34B is 01.AI's open-source model that delivers impressive performance for its size, particularly on bilingual Chinese-English tasks. At 34 billion parameters, it offers a strong foundation for fine-tuning and custom deployments. The Yi series has been influential in demonstrating that high-quality training data and methods can produce competitive models without requiring the largest compute budgets.

View 01.AI profile →

Yi-Large

Yi-Large is 01.AI's most capable model, founded by AI pioneer Kai-Fu Lee. It delivers strong performance across reasoning, coding, and multilingual tasks, competing with leading global models. Yi-Large is particularly strong on Chinese-English bilingual tasks and has been adopted by numerous enterprises in Asia for production deployments requiring high-quality language understanding.

View 01.AI profile →

Key Differences: Yi-1.5 34B vs Yi-Large

1

Yi-Large supports a larger context window (32K), allowing it to process longer documents in a single request.

2

Yi-1.5 34B is open-source (free to self-host and fine-tune) while Yi-Large is proprietary (API-only access).

Y

When to use Yi-1.5 34B

  • +You need to self-host or fine-tune the model
  • +Your use case involves bilingual tasks, fine-tuning, research
View full Yi-1.5 34B specs →
Y

When to use Yi-Large

  • +You need to process long documents (32K context)
  • +You prefer a managed API without infrastructure overhead
  • +Your use case involves complex reasoning, multilingual, analysis
View full Yi-Large specs →

The Verdict

This is a close matchup. Yi-1.5 34B and Yi-Large each win in different categories, making the choice highly dependent on your use case. Choose Yi-1.5 34B for bilingual tasks, fine-tuning, research. Choose Yi-Large for complex reasoning, multilingual, analysis.

Last compared: March 2026 · Data sourced from public benchmarks and official pricing pages

Frequently Asked Questions

Which is better, Yi-1.5 34B or Yi-Large?
Yi-1.5 34B and Yi-Large are closely matched, each winning in different categories. Yi-1.5 34B excels at bilingual tasks, fine-tuning, research, while Yi-Large is optimized for complex reasoning, multilingual, analysis. We recommend testing both for your specific use case.
How does Yi-1.5 34B pricing compare to Yi-Large?
Yi-1.5 34B charges Free (open) per 1M input tokens and Free (open) per 1M output tokens. Yi-Large charges Undisclosed per 1M input tokens and Undisclosed per 1M output tokens. For high-volume production workloads, the pricing difference can significantly impact total cost of ownership.
What is the context window difference between Yi-1.5 34B and Yi-Large?
Yi-1.5 34B supports a 4K token context window, while Yi-Large supports 32K tokens. Yi-Large can process longer documents, codebases, and conversations in a single request. Context window size matters most for tasks involving long documents, large codebases, or extended conversations.
Can I use Yi-1.5 34B or Yi-Large for free?
Yi-1.5 34B is a paid API model starting at Free (open) per 1M input tokens. Yi-Large is a paid API model starting at Undisclosed per 1M input tokens. Open-source models can be self-hosted for free but require your own GPU infrastructure.
Which model has better benchmarks, Yi-1.5 34B or Yi-Large?
Yi-1.5 34B's arena rank is not yet available, while Yi-Large's rank is not yet available. Note that benchmarks don't capture every use case — we recommend testing both models on your specific tasks.
Is Yi-1.5 34B or Yi-Large better for coding?
Yi-1.5 34B's primary strength is bilingual tasks, fine-tuning, research. Yi-Large's primary strength is complex reasoning, multilingual, analysis. For coding specifically, arena rank and code-specific benchmarks are the best indicators of performance.