Pixtral Large vs Jamba 1.5 Large
Compare Pixtral Large 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
| Feature | Pixtral Large | Jamba 1.5 Large |
|---|---|---|
| Category | Vision | Enterprise |
| Parameters | 124B | 398B (94B active) |
| Context Window | 128K | 256K |
| Input Price | $0.06/1M tokens | $0.08/1M tokens |
| Output Price | $0.10/1M tokens | $0.14/1M tokens |
| Latency | ~450ms | ~500ms |
Choose Pixtral Large when:
- ✓ Image analysis
- ✓ Document understanding
- ✓ Chart reading
Strong vision, Good reasoning, Multilingual
Choose Jamba 1.5 Large when:
- ✓ Full text processing
- ✓ Comprehensive reports
- ✓ Long analysis
256K context, SSM-Transformer hybrid, Good summarization
Verdict: Pixtral Large vs Jamba 1.5 Large
For cost efficiency, Pixtral Large wins at $0.06/1M input tokens. For speed, Pixtral Large is faster at ~450ms. Pixtral Large excels at Image analysis 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
Pixtral Large costs $0.06/1M input tokens and $0.10/1M output tokens. Jamba 1.5 Large costs $0.08 input and $0.14 output. Pixtral Large is 1.3x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.
Performance & Context
Pixtral Large has a 128K context window with ~450ms latency. Jamba 1.5 Large offers 256K context at ~500ms. Jamba 1.5 Large has the larger context window.
Best For
Pixtral Large (Vision) is optimized for: Image analysis, Document understanding, Chart reading. 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 Pixtral Large
response_a = client.chat.completions.create(
model="pixtral-large",
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"}]
)Frequently Asked Questions
Which is better, Pixtral Large or Jamba 1.5 Large?
Pixtral Large (Vision, 124B) offers Strong vision. Jamba 1.5 Large (Enterprise, 398B (94B active)) offers 256K context. Choose Pixtral Large for Image analysis or Jamba 1.5 Large for Full text processing.
How much does Pixtral Large cost vs Jamba 1.5 Large?
Pixtral Large: $0.06/1M input, $0.10/1M 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 Pixtral Large and Jamba 1.5 Large 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.