Gemma 3 4B vs Llama 4 Maverick
Compare Gemma 3 4B and Llama 4 Maverick: 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 4B | Llama 4 Maverick |
|---|---|---|
| Category | Compact | Open Source |
| Parameters | 4B | 400B (17B active) |
| Context Window | 128K | 256K |
| Input Price | $0.008/1M tokens | $0.07/1M tokens |
| Output Price | $0.015/1M tokens | $0.12/1M tokens |
| Latency | ~60ms | ~450ms |
Choose Gemma 3 4B when:
- ✓ Intent detection
- ✓ Keyword extraction
- ✓ Preprocessing
Ultra-small, Fastest inference, Minimal cost
Choose Llama 4 Maverick when:
- ✓ Complex analysis
- ✓ Professional reports
- ✓ Deep reasoning
Superior reasoning, 256K context, Excellent multilingual
Verdict: Gemma 3 4B vs Llama 4 Maverick
For cost efficiency, Gemma 3 4B wins at $0.008/1M input tokens. For speed, Llama 4 Maverick is faster at ~450ms. Gemma 3 4B excels at Intent detection while Llama 4 Maverick is better for Complex 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
Gemma 3 4B costs $0.008/1M input tokens and $0.015/1M output tokens. Llama 4 Maverick costs $0.07 input and $0.12 output. Gemma 3 4B is 8.8x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.
Performance & Context
Gemma 3 4B has a 128K context window with ~60ms latency. Llama 4 Maverick offers 256K context at ~450ms. Llama 4 Maverick has the larger context window.
Best For
Gemma 3 4B (Compact) is optimized for: Intent detection, Keyword extraction, Preprocessing. Llama 4 Maverick (Open Source) works best for: Complex analysis, Professional reports, Deep reasoning.
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 4B
response_a = client.chat.completions.create(
model="gemma-3-4b",
messages=[{"role": "user", "content": "Your question here"}]
)
# Use Llama 4 Maverick
response_b = client.chat.completions.create(
model="llama-4-maverick",
messages=[{"role": "user", "content": "Your question here"}]
)
Frequently Asked Questions
Which is better, Gemma 3 4B or Llama 4 Maverick?
Gemma 3 4B (Compact, 4B) offers Ultra-small. Llama 4 Maverick (Open Source, 400B (17B active)) offers Superior reasoning. Choose Gemma 3 4B for Intent detection or Llama 4 Maverick for Complex analysis.
How much does Gemma 3 4B cost vs Llama 4 Maverick?
Gemma 3 4B: $0.008/1M input, $0.015/1M output. Llama 4 Maverick: $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 4B and Llama 4 Maverick 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.