Jamba 1.5 Large vs Gemma 3 1B

Compare Jamba 1.5 Large and Gemma 3 1B: 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 Jamba 1.5 Large Gemma 3 1B
CategoryEnterpriseCompact
Parameters398B (94B active)1B
Context Window256K32K
Input Price$0.08/1M tokens$0.003/1M tokens
Output Price$0.14/1M tokens$0.006/1M tokens
Latency~500ms~20ms

Choose Jamba 1.5 Large when:

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

256K context, SSM-Transformer hybrid, Good summarization

Choose Gemma 3 1B when:

  • ✓ Edge inference
  • ✓ Classification
  • ✓ Routing
Key Strengths:

Tiny footprint, Fastest inference, Edge-ready

Verdict: Jamba 1.5 Large vs Gemma 3 1B

For cost efficiency, Gemma 3 1B wins at $0.003/1M input tokens. For speed, Gemma 3 1B is faster at ~20ms. Jamba 1.5 Large excels at Full text processing while Gemma 3 1B is better for Edge inference. 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 Large costs $0.08/1M input tokens and $0.14/1M output tokens. Gemma 3 1B costs $0.003 input and $0.006 output. Gemma 3 1B is 26.7x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

Jamba 1.5 Large has a 256K context window with ~500ms latency. Gemma 3 1B offers 32K context at ~20ms. Jamba 1.5 Large has the larger context window.

Best For

Jamba 1.5 Large (Enterprise) is optimized for: Full text processing, Comprehensive reports, Long analysis. Gemma 3 1B (Compact) works best for: Edge inference, Classification, Routing.

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

# Use Gemma 3 1B
response_b = client.chat.completions.create(
    model="gemma-3-1b",
    messages=[{"role": "user", "content": "Your question here"}]
)

Start Building with XALEN

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Get API Key Try in Playground

Frequently Asked Questions

Which is better, Jamba 1.5 Large or Gemma 3 1B?

Jamba 1.5 Large (Enterprise, 398B (94B active)) offers 256K context. Gemma 3 1B (Compact, 1B) offers Tiny footprint. Choose Jamba 1.5 Large for Full text processing or Gemma 3 1B for Edge inference.

How much does Jamba 1.5 Large cost vs Gemma 3 1B?

Jamba 1.5 Large: $0.08/1M input, $0.14/1M output. Gemma 3 1B: $0.003/1M input, $0.006/1M 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 Large and Gemma 3 1B 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.