Llama 3.1 405B vs BGE Reranker v2
Compare Llama 3.1 405B and BGE Reranker v2: 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 | Llama 3.1 405B | BGE Reranker v2 |
|---|---|---|
| Category | Open Source | Reranking |
| Parameters | 405B | 568M |
| Context Window | 128K | 8K |
| Input Price | $0.08/1M tokens | $0.003/1M tokens |
| Output Price | $0.14/1M tokens | N/A/1M tokens |
| Latency | ~600ms | ~30ms |
Choose Llama 3.1 405B when:
- ✓ Premium tasks
- ✓ Research
- ✓ Fine-tuning base
Largest open model, Highest open-source quality
Choose BGE Reranker v2 when:
- ✓ RAG reranking
- ✓ Search improvement
- ✓ Citation accuracy
High precision, Cross-encoder, Improves RAG quality
Verdict: Llama 3.1 405B vs BGE Reranker v2
For cost efficiency, BGE Reranker v2 wins at $0.003/1M input tokens. For speed, BGE Reranker v2 is faster at ~30ms. Llama 3.1 405B excels at Premium tasks while BGE Reranker v2 is better for RAG reranking. Both are available on XALEN through a single API — try them in the Playground to see which fits your workload.
Detailed Analysis
Pricing Comparison
Llama 3.1 405B costs $0.08/1M input tokens and $0.14/1M output tokens. BGE Reranker v2 costs $0.003 input and N/A output. BGE Reranker v2 is 26.7x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.
Performance & Context
Llama 3.1 405B has a 128K context window with ~600ms latency. BGE Reranker v2 offers 8K context at ~30ms. Llama 3.1 405B has the larger context window.
Best For
Llama 3.1 405B (Open Source) is optimized for: Premium tasks, Research, Fine-tuning base. BGE Reranker v2 (Reranking) works best for: RAG reranking, Search improvement, Citation accuracy.
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 Llama 3.1 405B
response_a = client.chat.completions.create(
model="llama-3-1-405b",
messages=[{"role": "user", "content": "Your question here"}]
)
# Use BGE Reranker v2
response_b = client.chat.completions.create(
model="bge-reranker-v2",
messages=[{"role": "user", "content": "Your question here"}]
)
Frequently Asked Questions
Which is better, Llama 3.1 405B or BGE Reranker v2?
Llama 3.1 405B (Open Source, 405B) offers Largest open model. BGE Reranker v2 (Reranking, 568M) offers High precision. Choose Llama 3.1 405B for Premium tasks or BGE Reranker v2 for RAG reranking.
How much does Llama 3.1 405B cost vs BGE Reranker v2?
Llama 3.1 405B: $0.08/1M input, $0.14/1M output. BGE Reranker v2: $0.003/1M input, N/A/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 Llama 3.1 405B and BGE Reranker v2 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.