Gemini 2.5 Pro vs Voyage Large 2
Compare Gemini 2.5 Pro and Voyage Large 2: 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 | Gemini 2.5 Pro | Voyage Large 2 |
|---|---|---|
| Category | Frontier | Embedding |
| Parameters | ~1.5T | ~500M |
| Context Window | 2M | 16K |
| Input Price | $0.07/1M tokens | $0.002/1M tokens |
| Output Price | $0.21/1M tokens | N/A/1M tokens |
| Latency | ~600ms | ~25ms |
Choose Gemini 2.5 Pro when:
- ✓ Classical text analysis
- ✓ Multi-document reports
- ✓ Research
2M context, Strong multimodal, Long text analysis
Choose Voyage Large 2 when:
- ✓ Code search
- ✓ Long document RAG
- ✓ Semantic matching
16K context, High quality, Good for code
Verdict: Gemini 2.5 Pro vs Voyage Large 2
For cost efficiency, Voyage Large 2 wins at $0.002/1M input tokens. For speed, Voyage Large 2 is faster at ~25ms. Gemini 2.5 Pro excels at Classical text analysis while Voyage Large 2 is better for Code search. Both are available on XALEN through a single API — try them in the Playground to see which fits your workload.
Detailed Analysis
Pricing Comparison
Gemini 2.5 Pro costs $0.07/1M input tokens and $0.21/1M output tokens. Voyage Large 2 costs $0.002 input and N/A output. Voyage Large 2 is 35.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.
Performance & Context
Gemini 2.5 Pro has a 2M context window with ~600ms latency. Voyage Large 2 offers 16K context at ~25ms. Gemini 2.5 Pro has the larger context window.
Best For
Gemini 2.5 Pro (Frontier) is optimized for: Classical text analysis, Multi-document reports, Research. Voyage Large 2 (Embedding) works best for: Code search, Long document RAG, Semantic matching.
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 Gemini 2.5 Pro
response_a = client.chat.completions.create(
model="gemini-2-5-pro",
messages=[{"role": "user", "content": "Your question here"}]
)
# Use Voyage Large 2
response_b = client.chat.completions.create(
model="voyage-large-2",
messages=[{"role": "user", "content": "Your question here"}]
)Frequently Asked Questions
Which is better, Gemini 2.5 Pro or Voyage Large 2?
Gemini 2.5 Pro (Frontier, ~1.5T) offers 2M context. Voyage Large 2 (Embedding, ~500M) offers 16K context. Choose Gemini 2.5 Pro for Classical text analysis or Voyage Large 2 for Code search.
How much does Gemini 2.5 Pro cost vs Voyage Large 2?
Gemini 2.5 Pro: $0.07/1M input, $0.21/1M output. Voyage Large 2: $0.002/1M 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 Gemini 2.5 Pro and Voyage Large 2 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.