Llama 3.2 11B Vision vs Jamba 1.5 Large

Compare Llama 3.2 11B Vision and Jamba 1.5 Large: pricing, performance, context window, latency, and best use cases. Side-by-side comparison on XALEN.

Updated 2026-05-21 · By Abhishek Raj · Our methodology

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Feature Llama 3.2 11B Vision Jamba 1.5 Large
CategoryVisionEnterprise
Parameters11B398B (94B active)
Context Window128K256K
Input Price$0.02/1M tokens$0.08/1M tokens
Output Price$0.04/1M tokens$0.14/1M tokens
Latency~200ms~500ms

Choose Llama 3.2 11B Vision when:

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

Low cost vision, Fast, Compact

Choose Jamba 1.5 Large when:

  • ✓ Full text processing
  • ✓ Comprehensive reports
  • ✓ Long analysis
Key Strengths:

256K context, SSM-Transformer hybrid, Good summarization

Verdict: Llama 3.2 11B Vision vs Jamba 1.5 Large

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 3.2 11B Vision excels at Image classification while Jamba 1.5 Large is better for Full text processing. 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 11B Vision costs $0.02/1M input tokens and $0.04/1M output tokens. Jamba 1.5 Large costs $0.08 input and $0.14 output. Llama 3.2 11B Vision is 4.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

Llama 3.2 11B Vision has a 128K context window with ~200ms latency. Jamba 1.5 Large offers 256K context at ~500ms. Jamba 1.5 Large has the larger context window.

Best For

Llama 3.2 11B Vision (Vision) is optimized for: Image classification, OCR, Simple visual Q&A. Jamba 1.5 Large (Enterprise) works best for: Full text processing, Comprehensive reports, Long analysis.

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 11B Vision
response_a = client.chat.completions.create(
    model="llama-3-2-11b-vision",
    messages=[{"role": "user", "content": "Your question here"}]
)

# Use Jamba 1.5 Large
response_b = client.chat.completions.create(
    model="jamba-1-5-large",
    messages=[{"role": "user", "content": "Your question here"}]
)

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Get API Key Try in Playground

Frequently Asked Questions

Which is better, Llama 3.2 11B Vision or Jamba 1.5 Large?

Llama 3.2 11B Vision (Vision, 11B) offers Low cost vision. Jamba 1.5 Large (Enterprise, 398B (94B active)) offers 256K context. Choose Llama 3.2 11B Vision for Image classification or Jamba 1.5 Large for Full text processing.

How much does Llama 3.2 11B Vision cost vs Jamba 1.5 Large?

Llama 3.2 11B Vision: $0.02/1M input, $0.04/1M output. Jamba 1.5 Large: $0.08/1M input, $0.14/1M 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 11B Vision and Jamba 1.5 Large 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.