Llama 4 Scout vs E5 Large v2

Compare Llama 4 Scout and E5 Large v2: 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 Microsoft models What is an LLM API? Python Quickstart What is inference?
Feature Llama 4 Scout E5 Large v2
CategoryOpen SourceEmbedding
Parameters109B (17B active)335M
Context Window512K512
Input Price$0.05/1M tokens$0.002/1M tokens
Output Price$0.08/1M tokensN/A/1M tokens
Latency~350ms~20ms

Choose Llama 4 Scout when:

  • ✓ Classical text analysis
  • ✓ Long content
  • ✓ Multi-turn
Key Strengths:

512K context, MoE efficiency, Strong multilingual

Choose E5 Large v2 when:

  • ✓ Classical text search
  • ✓ RAG pipelines
  • ✓ Knowledge retrieval
Key Strengths:

1024 dimensions, Fast, Multi-lingual

Verdict: Llama 4 Scout vs E5 Large v2

For cost efficiency, E5 Large v2 wins at $0.002/1M input tokens. For speed, E5 Large v2 is faster at ~20ms. Llama 4 Scout excels at Classical text analysis while E5 Large v2 is better for Classical text 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 4 Scout costs $0.05/1M input tokens and $0.08/1M output tokens. E5 Large v2 costs $0.002 input and N/A output. E5 Large v2 is 25.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

Llama 4 Scout has a 512K context window with ~350ms latency. E5 Large v2 offers 512 context at ~20ms. Llama 4 Scout has the larger context window.

Best For

Llama 4 Scout (Open Source) is optimized for: Classical text analysis, Long content, Multi-turn. E5 Large v2 (Embedding) works best for: Classical text search, RAG pipelines, Knowledge retrieval.

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 4 Scout
response_a = client.chat.completions.create(
    model="llama-4-scout",
    messages=[{"role": "user", "content": "Your question here"}]
)

# Use E5 Large v2
response_b = client.chat.completions.create(
    model="e5-large-v2",
    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 4 Scout or E5 Large v2?

Llama 4 Scout (Open Source, 109B (17B active)) offers 512K context. E5 Large v2 (Embedding, 335M) offers 1024 dimensions. Choose Llama 4 Scout for Classical text analysis or E5 Large v2 for Classical text search.

How much does Llama 4 Scout cost vs E5 Large v2?

Llama 4 Scout: $0.05/1M input, $0.08/1M output. E5 Large v2: $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 4 Scout and E5 Large v2 by changing the model parameter. No code changes needed.

Related Comparisons

Llama 4 Scout vs Text Embedding 3 Large Llama 4 Scout vs Gemma 3 27B Llama 4 Scout vs Llama 4 Maverick Llama 4 Scout vs Llama 3.3 70B Llama 4 Scout vs Llama 3.1 405B Llama 4 Scout vs Llama 3.1 70B Turbo

Last updated: 2026-05-21. Pricing and specifications may change. Check pricing page for latest rates.