Llama 3.1 405B vs Jina Embeddings v3

Compare Llama 3.1 405B and Jina Embeddings v3: 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 Jina AI models What is an LLM API? Python Quickstart What is inference?
Feature Llama 3.1 405B Jina Embeddings v3
CategoryOpen SourceEmbedding
Parameters405B~300M
Context Window128K8K
Input Price$0.08/1M tokens$0.002/1M tokens
Output Price$0.14/1M tokensN/A/1M tokens
Latency~600ms~15ms

Choose Llama 3.1 405B when:

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

Largest open model, Highest open-source quality

Choose Jina Embeddings v3 when:

  • ✓ Multilingual search
  • ✓ Cross-language RAG
  • ✓ Semantic matching
Key Strengths:

Strong multilingual, Good for RAG, Flexible dimensions

Verdict: Llama 3.1 405B vs Jina Embeddings v3

For cost efficiency, Jina Embeddings v3 wins at $0.002/1M input tokens. For speed, Jina Embeddings v3 is faster at ~15ms. Llama 3.1 405B excels at Premium tasks while Jina Embeddings v3 is better for Multilingual search. 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. Jina Embeddings v3 costs $0.002 input and N/A output. Jina Embeddings v3 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. Jina Embeddings v3 offers 8K context at ~15ms. 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. Jina Embeddings v3 (Embedding) works best for: Multilingual search, Cross-language RAG, Semantic matching.

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 Jina Embeddings v3
response_b = client.chat.completions.create(
    model="jina-embeddings-v3",
    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 Jina Embeddings v3?

Llama 3.1 405B (Open Source, 405B) offers Largest open model. Jina Embeddings v3 (Embedding, ~300M) offers Strong multilingual. Choose Llama 3.1 405B for Premium tasks or Jina Embeddings v3 for Multilingual search.

How much does Llama 3.1 405B cost vs Jina Embeddings v3?

Llama 3.1 405B: $0.08/1M input, $0.14/1M output. Jina Embeddings v3: $0.002/1M 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 Jina Embeddings v3 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.