Llama 3.2 90B Vision vs Jamba 1.5 Large

Compare Llama 3.2 90B 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

All Meta models All AI21 models What is an LLM API? Python Quickstart What is inference?
Feature Llama 3.2 90B Vision Jamba 1.5 Large
CategoryVisionEnterprise
Parameters90B398B (94B active)
Context Window128K256K
Input Price$0.06/1M tokens$0.08/1M tokens
Output Price$0.10/1M tokens$0.14/1M tokens
Latency~500ms~500ms

Choose Llama 3.2 90B Vision when:

  • ✓ Chart image analysis
  • ✓ Document scanning
  • ✓ Visual Q&A
Key Strengths:

Vision + language, Open weights, Good reasoning

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 90B Vision vs Jamba 1.5 Large

For cost efficiency, Llama 3.2 90B Vision wins at $0.06/1M input tokens. For speed, Jamba 1.5 Large is faster at ~500ms. Llama 3.2 90B Vision excels at Chart image analysis 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 90B Vision costs $0.06/1M input tokens and $0.10/1M output tokens. Jamba 1.5 Large costs $0.08 input and $0.14 output. Llama 3.2 90B Vision is 1.3x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

Llama 3.2 90B Vision has a 128K context window with ~500ms latency. Jamba 1.5 Large offers 256K context at ~500ms. Jamba 1.5 Large has the larger context window.

Best For

Llama 3.2 90B Vision (Vision) is optimized for: Chart image analysis, Document scanning, 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 90B Vision
response_a = client.chat.completions.create(
    model="llama-3-2-90b-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"}]
)

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 3.2 90B Vision or Jamba 1.5 Large?

Llama 3.2 90B Vision (Vision, 90B) offers Vision + language. Jamba 1.5 Large (Enterprise, 398B (94B active)) offers 256K context. Choose Llama 3.2 90B Vision for Chart image analysis or Jamba 1.5 Large for Full text processing.

How much does Llama 3.2 90B Vision cost vs Jamba 1.5 Large?

Llama 3.2 90B Vision: $0.06/1M input, $0.10/1M 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 90B Vision and Jamba 1.5 Large by changing the model parameter. No code changes needed.

Related Comparisons

Llama 3.2 90B Vision vs Vedika Vision Llama 3.2 90B Vision vs Llama 3.2 11B Vision Llama 3.2 90B Vision vs Qwen 2.5 VL 72B Llama 3.2 90B Vision vs Qwen 2.5 VL 7B Llama 3.2 90B Vision vs Pixtral Large Llama 3.2 90B Vision vs Pixtral 12B

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