Gemma 3 1B vs DeepSeek R1 Distill 32B
Compare Gemma 3 1B and DeepSeek R1 Distill 32B: 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 1B | DeepSeek R1 Distill 32B |
|---|---|---|
| Category | Compact | Reasoning |
| Parameters | 1B | 32B |
| Context Window | 32K | 128K |
| Input Price | $0.003/1M tokens | $0.03/1M tokens |
| Output Price | $0.006/1M tokens | $0.06/1M tokens |
| Latency | ~20ms | ~250ms |
Choose Gemma 3 1B when:
- ✓ Edge inference
- ✓ Classification
- ✓ Routing
Tiny footprint, Fastest inference, Edge-ready
Choose DeepSeek R1 Distill 32B when:
- ✓ Production reasoning
- ✓ Analysis
- ✓ Structured tasks
Good reasoning, Moderate cost, Fast
Verdict: Gemma 3 1B vs DeepSeek R1 Distill 32B
For cost efficiency, Gemma 3 1B wins at $0.003/1M input tokens. For speed, Gemma 3 1B is faster at ~20ms. Gemma 3 1B excels at Edge inference while DeepSeek R1 Distill 32B is better for Production reasoning. 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 1B costs $0.003/1M input tokens and $0.006/1M output tokens. DeepSeek R1 Distill 32B costs $0.03 input and $0.06 output. Gemma 3 1B is 10.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.
Performance & Context
Gemma 3 1B has a 32K context window with ~20ms latency. DeepSeek R1 Distill 32B offers 128K context at ~250ms. DeepSeek R1 Distill 32B has the larger context window.
Best For
Gemma 3 1B (Compact) is optimized for: Edge inference, Classification, Routing. DeepSeek R1 Distill 32B (Reasoning) works best for: Production reasoning, Analysis, Structured tasks.
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 1B
response_a = client.chat.completions.create(
model="gemma-3-1b",
messages=[{"role": "user", "content": "Your question here"}]
)
# Use DeepSeek R1 Distill 32B
response_b = client.chat.completions.create(
model="deepseek-r1-distill-32b",
messages=[{"role": "user", "content": "Your question here"}]
)
Frequently Asked Questions
Which is better, Gemma 3 1B or DeepSeek R1 Distill 32B?
Gemma 3 1B (Compact, 1B) offers Tiny footprint. DeepSeek R1 Distill 32B (Reasoning, 32B) offers Good reasoning. Choose Gemma 3 1B for Edge inference or DeepSeek R1 Distill 32B for Production reasoning.
How much does Gemma 3 1B cost vs DeepSeek R1 Distill 32B?
Gemma 3 1B: $0.003/1M input, $0.006/1M output. DeepSeek R1 Distill 32B: $0.03/1M input, $0.06/1M 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 1B and DeepSeek R1 Distill 32B 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.