Gemini 2.5 Pro vs Nemotron 4 340B
Compare Gemini 2.5 Pro and Nemotron 4 340B: 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 | Nemotron 4 340B |
|---|---|---|
| Category | Frontier | Open Source |
| Parameters | ~1.5T | 340B |
| Context Window | 2M | 128K |
| Input Price | $0.07/1M tokens | $0.07/1M tokens |
| Output Price | $0.21/1M tokens | $0.12/1M tokens |
| Latency | ~600ms | ~500ms |
Choose Gemini 2.5 Pro when:
- ✓ Classical text analysis
- ✓ Multi-document reports
- ✓ Research
2M context, Strong multimodal, Long text analysis
Choose Nemotron 4 340B when:
- ✓ Data generation
- ✓ Training data
- ✓ Research
Synthetic data generation, Large scale, Good quality
Verdict: Gemini 2.5 Pro vs Nemotron 4 340B
For cost efficiency, Nemotron 4 340B wins at $0.07/1M input tokens. For speed, Nemotron 4 340B is faster at ~500ms. Gemini 2.5 Pro excels at Classical text analysis while Nemotron 4 340B is better for Data generation. 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. Nemotron 4 340B costs $0.07 input and $0.12 output. Both models are similarly priced. XALEN offers batch processing at 50% discount on both models.
Performance & Context
Gemini 2.5 Pro has a 2M context window with ~600ms latency. Nemotron 4 340B offers 128K context at ~500ms. 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. Nemotron 4 340B (Open Source) works best for: Data generation, Training data, Research.
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 Nemotron 4 340B
response_b = client.chat.completions.create(
model="nemotron-4-340b",
messages=[{"role": "user", "content": "Your question here"}]
)Frequently Asked Questions
Which is better, Gemini 2.5 Pro or Nemotron 4 340B?
Gemini 2.5 Pro (Frontier, ~1.5T) offers 2M context. Nemotron 4 340B (Open Source, 340B) offers Synthetic data generation. Choose Gemini 2.5 Pro for Classical text analysis or Nemotron 4 340B for Data generation.
How much does Gemini 2.5 Pro cost vs Nemotron 4 340B?
Gemini 2.5 Pro: $0.07/1M input, $0.21/1M output. Nemotron 4 340B: $0.07/1M input, $0.12/1M 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 Nemotron 4 340B 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.