Llama 3.1 405B vs Cohere Rerank 3.5

Compare Llama 3.1 405B 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 3.1 405B Cohere Rerank 3.5
CategoryOpen SourceReranking
Parameters405B~600M
Context Window128K4K
Input Price$0.08/1M tokens$0.002/search/1M tokens
Output Price$0.14/1M tokensN/A/1M tokens
Latency~600ms~25ms

Choose Llama 3.1 405B when:

  • ✓ Premium tasks
  • ✓ Research
  • ✓ Fine-tuning base
Key Strengths:

Largest open model, Highest open-source quality

Choose Cohere Rerank 3.5 when:

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

Higher quality, Multilingual, Fast

Verdict: Llama 3.1 405B 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 3.1 405B excels at Premium tasks 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 3.1 405B costs $0.08/1M input tokens and $0.14/1M output tokens. Cohere Rerank 3.5 costs $0.002/search input and N/A output. Cohere Rerank 3.5 is 40.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

Llama 3.1 405B has a 128K context window with ~600ms latency. Cohere Rerank 3.5 offers 4K context at ~25ms. Llama 3.1 405B has the larger context window.

Best For

Llama 3.1 405B (Open Source) is optimized for: Premium tasks, Research, Fine-tuning base. 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 3.1 405B
response_a = client.chat.completions.create(
    model="llama-3-1-405b",
    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 3.1 405B or Cohere Rerank 3.5?

Llama 3.1 405B (Open Source, 405B) offers Largest open model. Cohere Rerank 3.5 (Reranking, ~600M) offers Higher quality. Choose Llama 3.1 405B for Premium tasks or Cohere Rerank 3.5 for Search reranking.

How much does Llama 3.1 405B cost vs Cohere Rerank 3.5?

Llama 3.1 405B: $0.08/1M input, $0.14/1M 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 3.1 405B 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.