Phi-3.5 Mini vs Jamba 1.5 Large

Compare Phi-3.5 Mini 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 Microsoft models All AI21 models What is an LLM API? Python Quickstart What is inference?
Feature Phi-3.5 Mini Jamba 1.5 Large
CategoryCompactEnterprise
Parameters3.8B398B (94B active)
Context Window128K256K
Input Price$0.005/1M tokens$0.08/1M tokens
Output Price$0.01/1M tokens$0.14/1M tokens
Latency~50ms~500ms

Choose Phi-3.5 Mini when:

  • ✓ Simple Q&A
  • ✓ Classification
  • ✓ Edge inference
Key Strengths:

128K context in tiny model, Ultra-low cost, Fast

Choose Jamba 1.5 Large when:

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

256K context, SSM-Transformer hybrid, Good summarization

Verdict: Phi-3.5 Mini vs Jamba 1.5 Large

For cost efficiency, Phi-3.5 Mini wins at $0.005/1M input tokens. For speed, Jamba 1.5 Large is faster at ~500ms. Phi-3.5 Mini excels at Simple Q&A 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

Phi-3.5 Mini costs $0.005/1M input tokens and $0.01/1M output tokens. Jamba 1.5 Large costs $0.08 input and $0.14 output. Phi-3.5 Mini is 16.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

Phi-3.5 Mini has a 128K context window with ~50ms latency. Jamba 1.5 Large offers 256K context at ~500ms. Jamba 1.5 Large has the larger context window.

Best For

Phi-3.5 Mini (Compact) is optimized for: Simple Q&A, Classification, Edge inference. 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 Phi-3.5 Mini
response_a = client.chat.completions.create(
    model="phi-3-5-mini",
    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, Phi-3.5 Mini or Jamba 1.5 Large?

Phi-3.5 Mini (Compact, 3.8B) offers 128K context in tiny model. Jamba 1.5 Large (Enterprise, 398B (94B active)) offers 256K context. Choose Phi-3.5 Mini for Simple Q&A or Jamba 1.5 Large for Full text processing.

How much does Phi-3.5 Mini cost vs Jamba 1.5 Large?

Phi-3.5 Mini: $0.005/1M input, $0.01/1M 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 Phi-3.5 Mini and Jamba 1.5 Large by changing the model parameter. No code changes needed.

Related Comparisons

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

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