Jamba 1.5 Large vs QwQ 32B

Compare Jamba 1.5 Large and QwQ 32B: 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 QwQ 32B
CategoryEnterpriseReasoning
Parameters398B (94B active)32B
Context Window256K128K
Input Price$0.08/1M tokens$0.03/1M tokens
Output Price$0.14/1M tokens$0.06/1M tokens
Latency~500ms~400ms

Choose Jamba 1.5 Large when:

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

256K context, SSM-Transformer hybrid, Good summarization

Choose QwQ 32B when:

  • ✓ Math reasoning
  • ✓ Logic tasks
  • ✓ Analysis
Key Strengths:

Strong reasoning, Compact for reasoning, Cost-efficient

Verdict: Jamba 1.5 Large vs QwQ 32B

For cost efficiency, QwQ 32B wins at $0.03/1M input tokens. For speed, QwQ 32B is faster at ~400ms. Jamba 1.5 Large excels at Full text processing while QwQ 32B is better for Math reasoning. 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. QwQ 32B costs $0.03 input and $0.06 output. QwQ 32B is 2.7x 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. QwQ 32B offers 128K context at ~400ms. 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. QwQ 32B (Reasoning) works best for: Math reasoning, Logic tasks, 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 Jamba 1.5 Large
response_a = client.chat.completions.create(
    model="jamba-1-5-large",
    messages=[{"role": "user", "content": "Your question here"}]
)

# Use QwQ 32B
response_b = client.chat.completions.create(
    model="qwq-32b",
    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 QwQ 32B?

Jamba 1.5 Large (Enterprise, 398B (94B active)) offers 256K context. QwQ 32B (Reasoning, 32B) offers Strong reasoning. Choose Jamba 1.5 Large for Full text processing or QwQ 32B for Math reasoning.

How much does Jamba 1.5 Large cost vs QwQ 32B?

Jamba 1.5 Large: $0.08/1M input, $0.14/1M output. QwQ 32B: $0.03/1M input, $0.06/1M 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 QwQ 32B 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.