Llama 3.2 90B Vision vs Cohere Rerank 3.5

Compare Llama 3.2 90B Vision and Cohere Rerank 3.5: 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 90B Vision Cohere Rerank 3.5
CategoryVisionReranking
Parameters90B~600M
Context Window128K4K
Input Price$0.06/1M tokens$0.002/search/1M tokens
Output Price$0.10/1M tokensN/A/1M tokens
Latency~500ms~25ms

Choose Llama 3.2 90B Vision when:

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

Vision + language, Open weights, Good reasoning

Choose Cohere Rerank 3.5 when:

  • ✓ Search reranking
  • ✓ RAG improvement
  • ✓ Result quality
Key Strengths:

Higher quality, Multilingual, Fast

Verdict: Llama 3.2 90B Vision vs Cohere Rerank 3.5

For cost efficiency, Cohere Rerank 3.5 wins at $0.002/search/1M input tokens. For speed, Cohere Rerank 3.5 is faster at ~25ms. Llama 3.2 90B Vision excels at Chart image analysis while Cohere Rerank 3.5 is better for Search reranking. 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. Cohere Rerank 3.5 costs $0.002/search input and N/A output. Cohere Rerank 3.5 is 30.0x 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. Cohere Rerank 3.5 offers 4K context at ~25ms. Llama 3.2 90B Vision has the larger context window.

Best For

Llama 3.2 90B Vision (Vision) is optimized for: Chart image analysis, Document scanning, Visual Q&A. Cohere Rerank 3.5 (Reranking) works best for: Search reranking, RAG improvement, Result quality.

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 Cohere Rerank 3.5
response_b = client.chat.completions.create(
    model="rerank-v3-5",
    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 Cohere Rerank 3.5?

Llama 3.2 90B Vision (Vision, 90B) offers Vision + language. Cohere Rerank 3.5 (Reranking, ~600M) offers Higher quality. Choose Llama 3.2 90B Vision for Chart image analysis or Cohere Rerank 3.5 for Search reranking.

How much does Llama 3.2 90B Vision cost vs Cohere Rerank 3.5?

Llama 3.2 90B Vision: $0.06/1M input, $0.10/1M output. Cohere Rerank 3.5: $0.002/search/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 3.2 90B Vision and Cohere Rerank 3.5 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.