Llama 3.2 3B vs Cohere Rerank 3.5

Compare Llama 3.2 3B 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

All Meta models All Cohere models What is an LLM API? Python Quickstart What is inference?
Feature Llama 3.2 3B Cohere Rerank 3.5
CategoryCompactReranking
Parameters3B~600M
Context Window128K4K
Input Price$0.006/1M tokens$0.002/search/1M tokens
Output Price$0.012/1M tokensN/A/1M tokens
Latency~40ms~25ms

Choose Llama 3.2 3B when:

  • ✓ Mobile apps
  • ✓ Edge inference
  • ✓ Preprocessing
Key Strengths:

Ultra-small, Edge-ready, Minimal latency

Choose Cohere Rerank 3.5 when:

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

Higher quality, Multilingual, Fast

Verdict: Llama 3.2 3B 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. Llama 3.2 3B excels at Mobile apps 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

Llama 3.2 3B costs $0.006/1M input tokens and $0.012/1M output tokens. Cohere Rerank 3.5 costs $0.002/search input and N/A output. Cohere Rerank 3.5 is 3.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

Llama 3.2 3B has a 128K context window with ~40ms latency. Cohere Rerank 3.5 offers 4K context at ~25ms. Llama 3.2 3B has the larger context window.

Best For

Llama 3.2 3B (Compact) is optimized for: Mobile apps, Edge inference, Preprocessing. 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 Llama 3.2 3B
response_a = client.chat.completions.create(
    model="llama-3-2-3b",
    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, Llama 3.2 3B or Cohere Rerank 3.5?

Llama 3.2 3B (Compact, 3B) offers Ultra-small. Cohere Rerank 3.5 (Reranking, ~600M) offers Higher quality. Choose Llama 3.2 3B for Mobile apps or Cohere Rerank 3.5 for Search reranking.

How much does Llama 3.2 3B cost vs Cohere Rerank 3.5?

Llama 3.2 3B: $0.006/1M input, $0.012/1M 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 Llama 3.2 3B 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.