Text Embedding 3 Large vs Jamba 1.5 Mini
Compare Text Embedding 3 Large and Jamba 1.5 Mini: 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 | Text Embedding 3 Large | Jamba 1.5 Mini |
|---|---|---|
| Category | Embedding | Compact |
| Parameters | ~500M | 52B (12B active) |
| Context Window | 8K | 256K |
| Input Price | $0.002/1M tokens | $0.02/1M tokens |
| Output Price | N/A/1M tokens | $0.04/1M tokens |
| Latency | ~20ms | ~200ms |
Choose Text Embedding 3 Large when:
- ✓ Semantic search
- ✓ Knowledge retrieval
- ✓ Similarity matching
3072 dimensions, Superior semantic quality, Matryoshka support
Choose Jamba 1.5 Mini when:
- ✓ Long document Q&A
- ✓ Budget apps
- ✓ Summarization
256K context, Low cost, SSM efficiency
Verdict: Text Embedding 3 Large vs Jamba 1.5 Mini
For cost efficiency, Text Embedding 3 Large wins at $0.002/1M input tokens. For speed, Jamba 1.5 Mini is faster at ~200ms. Text Embedding 3 Large excels at Semantic search while Jamba 1.5 Mini is better for Long document Q&A. Both are available on XALEN through a single API — try them in the Playground to see which fits your workload.
Detailed Analysis
Pricing Comparison
Text Embedding 3 Large costs $0.002/1M input tokens and N/A/1M output tokens. Jamba 1.5 Mini costs $0.02 input and $0.04 output. Text Embedding 3 Large is 10.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.
Performance & Context
Text Embedding 3 Large has a 8K context window with ~20ms latency. Jamba 1.5 Mini offers 256K context at ~200ms. Jamba 1.5 Mini has the larger context window.
Best For
Text Embedding 3 Large (Embedding) is optimized for: Semantic search, Knowledge retrieval, Similarity matching. Jamba 1.5 Mini (Compact) works best for: Long document Q&A, Budget apps, Summarization.
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 Text Embedding 3 Large
response_a = client.chat.completions.create(
model="text-embedding-3-large",
messages=[{"role": "user", "content": "Your question here"}]
)
# Use Jamba 1.5 Mini
response_b = client.chat.completions.create(
model="jamba-1-5-mini",
messages=[{"role": "user", "content": "Your question here"}]
)
Frequently Asked Questions
Which is better, Text Embedding 3 Large or Jamba 1.5 Mini?
Text Embedding 3 Large (Embedding, ~500M) offers 3072 dimensions. Jamba 1.5 Mini (Compact, 52B (12B active)) offers 256K context. Choose Text Embedding 3 Large for Semantic search or Jamba 1.5 Mini for Long document Q&A.
How much does Text Embedding 3 Large cost vs Jamba 1.5 Mini?
Text Embedding 3 Large: $0.002/1M input, N/A/1M output. Jamba 1.5 Mini: $0.02/1M input, $0.04/1M 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 Text Embedding 3 Large and Jamba 1.5 Mini 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.