Cohere Rerank 3.5 vs DeepSeek V2.5

Compare Cohere Rerank 3.5 and DeepSeek V2.5: 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 Cohere Rerank 3.5 DeepSeek V2.5
CategoryRerankingOpen Source
Parameters~600M236B (21B active)
Context Window4K128K
Input Price$0.002/search/1M tokens$0.04/1M tokens
Output PriceN/A/1M tokens$0.07/1M tokens
Latency~25ms~350ms

Choose Cohere Rerank 3.5 when:

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

Higher quality, Multilingual, Fast

Choose DeepSeek V2.5 when:

  • ✓ General purpose
  • ✓ Code generation
  • ✓ Legacy apps
Key Strengths:

Proven model, MoE efficient, Good coding

Verdict: Cohere Rerank 3.5 vs DeepSeek V2.5

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. Cohere Rerank 3.5 excels at Search reranking while DeepSeek V2.5 is better for General purpose. Both are available on XALEN through a single API — try them in the Playground to see which fits your workload.

Detailed Analysis

Pricing Comparison

Cohere Rerank 3.5 costs $0.002/search/1M input tokens and N/A/1M output tokens. DeepSeek V2.5 costs $0.04 input and $0.07 output. Cohere Rerank 3.5 is 20.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

Cohere Rerank 3.5 has a 4K context window with ~25ms latency. DeepSeek V2.5 offers 128K context at ~350ms. DeepSeek V2.5 has the larger context window.

Best For

Cohere Rerank 3.5 (Reranking) is optimized for: Search reranking, RAG improvement, Result quality. DeepSeek V2.5 (Open Source) works best for: General purpose, Code generation, Legacy apps.

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

# Use DeepSeek V2.5
response_b = client.chat.completions.create(
    model="deepseek-v2-5",
    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, Cohere Rerank 3.5 or DeepSeek V2.5?

Cohere Rerank 3.5 (Reranking, ~600M) offers Higher quality. DeepSeek V2.5 (Open Source, 236B (21B active)) offers Proven model. Choose Cohere Rerank 3.5 for Search reranking or DeepSeek V2.5 for General purpose.

How much does Cohere Rerank 3.5 cost vs DeepSeek V2.5?

Cohere Rerank 3.5: $0.002/search/1M input, N/A/1M output. DeepSeek V2.5: $0.04/1M input, $0.07/1M 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 Cohere Rerank 3.5 and DeepSeek V2.5 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.