Jamba 1.5 Mini vs Cohere Rerank 3.5

Compare Jamba 1.5 Mini 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

All AI21 models All Cohere models What is an LLM API? Python Quickstart What is inference?
Feature Jamba 1.5 Mini Cohere Rerank 3.5
CategoryCompactReranking
Parameters52B (12B active)~600M
Context Window256K4K
Input Price$0.02/1M tokens$0.002/search/1M tokens
Output Price$0.04/1M tokensN/A/1M tokens
Latency~200ms~25ms

Choose Jamba 1.5 Mini when:

  • ✓ Long document Q&A
  • ✓ Budget apps
  • ✓ Summarization
Key Strengths:

256K context, Low cost, SSM efficiency

Choose Cohere Rerank 3.5 when:

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

Higher quality, Multilingual, Fast

Verdict: Jamba 1.5 Mini vs Cohere Rerank 3.5

For cost efficiency, Cohere Rerank 3.5 wins at $0.002/search/1M input tokens. For speed, Jamba 1.5 Mini is faster at ~200ms. Jamba 1.5 Mini excels at Long document Q&A 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

Jamba 1.5 Mini costs $0.02/1M input tokens and $0.04/1M output tokens. Cohere Rerank 3.5 costs $0.002/search input and N/A output. Cohere Rerank 3.5 is 10.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

Jamba 1.5 Mini has a 256K context window with ~200ms latency. Cohere Rerank 3.5 offers 4K context at ~25ms. Jamba 1.5 Mini has the larger context window.

Best For

Jamba 1.5 Mini (Compact) is optimized for: Long document Q&A, Budget apps, Summarization. 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 Jamba 1.5 Mini
response_a = client.chat.completions.create(
    model="jamba-1-5-mini",
    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, Jamba 1.5 Mini or Cohere Rerank 3.5?

Jamba 1.5 Mini (Compact, 52B (12B active)) offers 256K context. Cohere Rerank 3.5 (Reranking, ~600M) offers Higher quality. Choose Jamba 1.5 Mini for Long document Q&A or Cohere Rerank 3.5 for Search reranking.

How much does Jamba 1.5 Mini cost vs Cohere Rerank 3.5?

Jamba 1.5 Mini: $0.02/1M input, $0.04/1M 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 Jamba 1.5 Mini and Cohere Rerank 3.5 by changing the model parameter. No code changes needed.

Related Comparisons

Jamba 1.5 Mini vs GPT-4.1 Nano Jamba 1.5 Mini vs GPT-4o Mini Jamba 1.5 Mini vs Claude Haiku 3.5 Jamba 1.5 Mini vs Gemma 3 12B Jamba 1.5 Mini vs Gemma 3 4B Jamba 1.5 Mini vs Gemini 2.5 Flash Lite

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