Llama 3.1 70B Turbo vs Llama 3.2 11B Vision

Compare Llama 3.1 70B Turbo and Llama 3.2 11B Vision: 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 Meta models What is an LLM API? Python Quickstart What is inference?
Feature Llama 3.1 70B Turbo Llama 3.2 11B Vision
CategoryOpen SourceVision
Parameters70B11B
Context Window128K128K
Input Price$0.04/1M tokens$0.02/1M tokens
Output Price$0.06/1M tokens$0.04/1M tokens
Latency~250ms~200ms

Choose Llama 3.1 70B Turbo when:

  • ✓ Production APIs
  • ✓ Fast generation
  • ✓ General purpose
Key Strengths:

Fast inference, Good quality, Well-tested

Choose Llama 3.2 11B Vision when:

  • ✓ Image classification
  • ✓ OCR
  • ✓ Simple visual Q&A
Key Strengths:

Low cost vision, Fast, Compact

Verdict: Llama 3.1 70B Turbo vs Llama 3.2 11B Vision

For cost efficiency, Llama 3.2 11B Vision wins at $0.02/1M input tokens. For speed, Llama 3.2 11B Vision is faster at ~200ms. Llama 3.1 70B Turbo excels at Production APIs while Llama 3.2 11B Vision is better for Image classification. 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 70B Turbo costs $0.04/1M input tokens and $0.06/1M output tokens. Llama 3.2 11B Vision costs $0.02 input and $0.04 output. Llama 3.2 11B Vision is 2.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

Llama 3.1 70B Turbo has a 128K context window with ~250ms latency. Llama 3.2 11B Vision offers 128K context at ~200ms. Both have identical context windows.

Best For

Llama 3.1 70B Turbo (Open Source) is optimized for: Production APIs, Fast generation, General purpose. Llama 3.2 11B Vision (Vision) works best for: Image classification, OCR, Simple visual Q&A.

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 70B Turbo
response_a = client.chat.completions.create(
    model="llama-3-1-70b-turbo",
    messages=[{"role": "user", "content": "Your question here"}]
)

# Use Llama 3.2 11B Vision
response_b = client.chat.completions.create(
    model="llama-3-2-11b-vision",
    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 70B Turbo or Llama 3.2 11B Vision?

Llama 3.1 70B Turbo (Open Source, 70B) offers Fast inference. Llama 3.2 11B Vision (Vision, 11B) offers Low cost vision. Choose Llama 3.1 70B Turbo for Production APIs or Llama 3.2 11B Vision for Image classification.

How much does Llama 3.1 70B Turbo cost vs Llama 3.2 11B Vision?

Llama 3.1 70B Turbo: $0.04/1M input, $0.06/1M output. Llama 3.2 11B Vision: $0.02/1M input, $0.04/1M 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 70B Turbo and Llama 3.2 11B Vision by changing the model parameter. No code changes needed.

Related Comparisons

Llama 3.1 70B Turbo vs Vedika Vision Llama 3.1 70B Turbo vs Gemma 3 27B Llama 3.1 70B Turbo vs Llama 4 Scout Llama 3.1 70B Turbo vs Llama 4 Maverick Llama 3.1 70B Turbo vs Llama 3.3 70B Llama 3.1 70B Turbo vs Llama 3.1 405B

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