Yi Large vs Cohere Rerank 3.5

Compare Yi Large and Cohere Rerank 3.5: pricing, performance, context window, latency, and best use cases. Side-by-side comparison on XALEN.

Updated 2026-05-21 · By Abhishek Raj · Our methodology

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Feature Yi Large Cohere Rerank 3.5
CategoryOpen SourceReranking
Parameters300B~600M
Context Window200K4K
Input Price$0.06/1M tokens$0.002/search/1M tokens
Output Price$0.12/1M tokensN/A/1M tokens
Latency~450ms~25ms

Choose Yi Large when:

  • ✓ Long document analysis
  • ✓ Research
  • ✓ Complex tasks
Key Strengths:

200K context, Strong analysis, Good reasoning

Choose Cohere Rerank 3.5 when:

  • ✓ Search reranking
  • ✓ RAG improvement
  • ✓ Result quality
Key Strengths:

Higher quality, Multilingual, Fast

Verdict: Yi Large vs Cohere Rerank 3.5

For cost efficiency, Cohere Rerank 3.5 wins at $0.002/search/1M input tokens. For speed, Cohere Rerank 3.5 is faster at ~25ms. Yi Large excels at Long document analysis while Cohere Rerank 3.5 is better for Search reranking. Both are available on XALEN through a single API — try them in the Playground to see which fits your workload.

Detailed Analysis

Pricing Comparison

Yi Large costs $0.06/1M input tokens and $0.12/1M output tokens. Cohere Rerank 3.5 costs $0.002/search input and N/A output. Cohere Rerank 3.5 is 30.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

Yi Large has a 200K context window with ~450ms latency. Cohere Rerank 3.5 offers 4K context at ~25ms. Yi Large has the larger context window.

Best For

Yi Large (Open Source) is optimized for: Long document analysis, Research, Complex tasks. Cohere Rerank 3.5 (Reranking) works best for: Search reranking, RAG improvement, Result quality.

Try Both on XALEN

Both models are available through XALEN's OpenAI-compatible API. Switch between them by changing the model parameter:

from xalen import XALEN

client = XALEN(api_key="xln_test_YOUR_KEY")

# Use Yi Large
response_a = client.chat.completions.create(
    model="yi-large",
    messages=[{"role": "user", "content": "Your question here"}]
)

# Use Cohere Rerank 3.5
response_b = client.chat.completions.create(
    model="rerank-v3-5",
    messages=[{"role": "user", "content": "Your question here"}]
)

Start Building with XALEN

200+ AI models. One API. Pay-as-you-go.

Get API Key Try in Playground

Frequently Asked Questions

Which is better, Yi Large or Cohere Rerank 3.5?

Yi Large (Open Source, 300B) offers 200K context. Cohere Rerank 3.5 (Reranking, ~600M) offers Higher quality. Choose Yi Large for Long document analysis or Cohere Rerank 3.5 for Search reranking.

How much does Yi Large cost vs Cohere Rerank 3.5?

Yi Large: $0.06/1M input, $0.12/1M output. Cohere Rerank 3.5: $0.002/search/1M input, N/A/1M output. Both available on XALEN with batch processing at 50% discount.

Can I use both models on XALEN?

Yes. XALEN provides 200+ models through a single OpenAI-compatible API. Switch between Yi Large and Cohere Rerank 3.5 by changing the model parameter. No code changes needed.

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Last updated: 2026-05-21. Pricing and specifications may change. Check pricing page for latest rates.