BGE Large v1.5 vs Jamba 1.5 Mini
Compare BGE Large v1.5 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 | BGE Large v1.5 | Jamba 1.5 Mini |
|---|---|---|
| Category | Embedding | Compact |
| Parameters | 326M | 52B (12B active) |
| Context Window | 512 | 256K |
| Input Price | $0.001/1M tokens | $0.02/1M tokens |
| Output Price | N/A/1M tokens | $0.04/1M tokens |
| Latency | ~15ms | ~200ms |
Choose BGE Large v1.5 when:
- ✓ Budget RAG
- ✓ Knowledge bases
- ✓ Document clustering
Very low cost, Good multilingual, Fast
Choose Jamba 1.5 Mini when:
- ✓ Long document Q&A
- ✓ Budget apps
- ✓ Summarization
256K context, Low cost, SSM efficiency
Verdict: BGE Large v1.5 vs Jamba 1.5 Mini
For cost efficiency, BGE Large v1.5 wins at $0.001/1M input tokens. For speed, BGE Large v1.5 is faster at ~15ms. BGE Large v1.5 excels at Budget RAG 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
BGE Large v1.5 costs $0.001/1M input tokens and N/A/1M output tokens. Jamba 1.5 Mini costs $0.02 input and $0.04 output. BGE Large v1.5 is 20.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.
Performance & Context
BGE Large v1.5 has a 512 context window with ~15ms latency. Jamba 1.5 Mini offers 256K context at ~200ms. Jamba 1.5 Mini has the larger context window.
Best For
BGE Large v1.5 (Embedding) is optimized for: Budget RAG, Knowledge bases, Document clustering. 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 BGE Large v1.5
response_a = client.chat.completions.create(
model="bge-large-v1-5",
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, BGE Large v1.5 or Jamba 1.5 Mini?
BGE Large v1.5 (Embedding, 326M) offers Very low cost. Jamba 1.5 Mini (Compact, 52B (12B active)) offers 256K context. Choose BGE Large v1.5 for Budget RAG or Jamba 1.5 Mini for Long document Q&A.
How much does BGE Large v1.5 cost vs Jamba 1.5 Mini?
BGE Large v1.5: $0.001/1M 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 BGE Large v1.5 and Jamba 1.5 Mini by changing the model parameter. No code changes needed.
Related Comparisons
Last updated: 2026-05-21. Pricing and specifications may change. Check pricing page for latest rates.