Gemma 3 27B vs Nemotron 4 340B
Compare Gemma 3 27B 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 | Gemma 3 27B | Nemotron 4 340B |
|---|---|---|
| Category | Open Source | Open Source |
| Parameters | 27B | 340B |
| Context Window | 128K | 128K |
| Input Price | $0.03/1M tokens | $0.07/1M tokens |
| Output Price | $0.05/1M tokens | $0.12/1M tokens |
| Latency | ~180ms | ~500ms |
Choose Gemma 3 27B when:
- ✓ Fast chatbots
- ✓ Content moderation
- ✓ Temple kiosks
Fast inference, Reliable output, Strong English/Hindi
Choose Nemotron 4 340B when:
- ✓ Data generation
- ✓ Training data
- ✓ Research
Synthetic data generation, Large scale, Good quality
Verdict: Gemma 3 27B vs Nemotron 4 340B
For cost efficiency, Gemma 3 27B wins at $0.03/1M input tokens. For speed, Gemma 3 27B is faster at ~180ms. Gemma 3 27B excels at Fast chatbots 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
Gemma 3 27B costs $0.03/1M input tokens and $0.05/1M output tokens. Nemotron 4 340B costs $0.07 input and $0.12 output. Gemma 3 27B is 2.3x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.
Performance & Context
Gemma 3 27B has a 128K context window with ~180ms latency. Nemotron 4 340B offers 128K context at ~500ms. Both have identical context windows.
Best For
Gemma 3 27B (Open Source) is optimized for: Fast chatbots, Content moderation, Temple kiosks. 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 Gemma 3 27B
response_a = client.chat.completions.create(
model="gemma-3-27b",
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, Gemma 3 27B or Nemotron 4 340B?
Gemma 3 27B (Open Source, 27B) offers Fast inference. Nemotron 4 340B (Open Source, 340B) offers Synthetic data generation. Choose Gemma 3 27B for Fast chatbots or Nemotron 4 340B for Data generation.
How much does Gemma 3 27B cost vs Nemotron 4 340B?
Gemma 3 27B: $0.03/1M input, $0.05/1M 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 Gemma 3 27B 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.