Qwen 2.5 72B Turbo vs Cohere Embed v4

Compare Qwen 2.5 72B Turbo and Cohere Embed v4: 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 Qwen 2.5 72B Turbo Cohere Embed v4
CategoryOpen SourceEmbedding
Parameters72B~400M
Context Window128K128K
Input Price$0.04/1M tokens$0.001/1M tokens
Output Price$0.08/1M tokensN/A/1M tokens
Latency~300ms~15ms

Choose Qwen 2.5 72B Turbo when:

  • ✓ Pan-India apps
  • ✓ Multilingual Q&A
  • ✓ Content generation
Key Strengths:

Strong Asian languages, Good reasoning, Fast inference

Choose Cohere Embed v4 when:

  • ✓ Long document RAG
  • ✓ Multimodal search
  • ✓ Large knowledge bases
Key Strengths:

128K context, Multimodal embedding, Matryoshka

Verdict: Qwen 2.5 72B Turbo vs Cohere Embed v4

For cost efficiency, Cohere Embed v4 wins at $0.001/1M input tokens. For speed, Cohere Embed v4 is faster at ~15ms. Qwen 2.5 72B Turbo excels at Pan-India apps while Cohere Embed v4 is better for Long document RAG. Both are available on XALEN through a single API — try them in the Playground to see which fits your workload.

Detailed Analysis

Pricing Comparison

Qwen 2.5 72B Turbo costs $0.04/1M input tokens and $0.08/1M output tokens. Cohere Embed v4 costs $0.001 input and N/A output. Cohere Embed v4 is 40.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

Qwen 2.5 72B Turbo has a 128K context window with ~300ms latency. Cohere Embed v4 offers 128K context at ~15ms. Both have identical context windows.

Best For

Qwen 2.5 72B Turbo (Open Source) is optimized for: Pan-India apps, Multilingual Q&A, Content generation. Cohere Embed v4 (Embedding) works best for: Long document RAG, Multimodal search, Large knowledge bases.

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 Qwen 2.5 72B Turbo
response_a = client.chat.completions.create(
    model="qwen-2-5-72b-turbo",
    messages=[{"role": "user", "content": "Your question here"}]
)

# Use Cohere Embed v4
response_b = client.chat.completions.create(
    model="embed-v4",
    messages=[{"role": "user", "content": "Your question here"}]
)

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Get API Key Try in Playground

Frequently Asked Questions

Which is better, Qwen 2.5 72B Turbo or Cohere Embed v4?

Qwen 2.5 72B Turbo (Open Source, 72B) offers Strong Asian languages. Cohere Embed v4 (Embedding, ~400M) offers 128K context. Choose Qwen 2.5 72B Turbo for Pan-India apps or Cohere Embed v4 for Long document RAG.

How much does Qwen 2.5 72B Turbo cost vs Cohere Embed v4?

Qwen 2.5 72B Turbo: $0.04/1M input, $0.08/1M output. Cohere Embed v4: $0.001/1M 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 Qwen 2.5 72B Turbo and Cohere Embed v4 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.