Gemini 2.5 Pro vs Arctic Large
Compare Gemini 2.5 Pro and Arctic 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 | Gemini 2.5 Pro | Arctic Large |
|---|---|---|
| Category | Frontier | Enterprise |
| Parameters | ~1.5T | 480B (17B active) |
| Context Window | 2M | 128K |
| Input Price | $0.07/1M tokens | $0.06/1M tokens |
| Output Price | $0.21/1M tokens | $0.10/1M tokens |
| Latency | ~600ms | ~400ms |
Choose Gemini 2.5 Pro when:
- ✓ Classical text analysis
- ✓ Multi-document reports
- ✓ Research
2M context, Strong multimodal, Long text analysis
Choose Arctic Large when:
- ✓ Data analysis
- ✓ SQL generation
- ✓ Business intelligence
Strong SQL, Data analysis, Enterprise features
Verdict: Gemini 2.5 Pro vs Arctic Large
For cost efficiency, Arctic Large wins at $0.06/1M input tokens. For speed, Arctic Large is faster at ~400ms. Gemini 2.5 Pro excels at Classical text analysis while Arctic Large is better for Data analysis. 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. Arctic Large costs $0.06 input and $0.10 output. Arctic Large is 1.2x 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. Arctic Large offers 128K context at ~400ms. 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. Arctic Large (Enterprise) works best for: Data analysis, SQL generation, Business intelligence.
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 Arctic Large
response_b = client.chat.completions.create(
model="arctic-large",
messages=[{"role": "user", "content": "Your question here"}]
)Frequently Asked Questions
Which is better, Gemini 2.5 Pro or Arctic Large?
Gemini 2.5 Pro (Frontier, ~1.5T) offers 2M context. Arctic Large (Enterprise, 480B (17B active)) offers Strong SQL. Choose Gemini 2.5 Pro for Classical text analysis or Arctic Large for Data analysis.
How much does Gemini 2.5 Pro cost vs Arctic Large?
Gemini 2.5 Pro: $0.07/1M input, $0.21/1M output. Arctic Large: $0.06/1M input, $0.10/1M 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 Arctic 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.