Yi Large vs DeepSeek R1 Distill 32B
Compare Yi Large 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 | Yi Large | DeepSeek R1 Distill 32B |
|---|---|---|
| Category | Open Source | Reasoning |
| Parameters | 300B | 32B |
| Context Window | 200K | 128K |
| Input Price | $0.06/1M tokens | $0.03/1M tokens |
| Output Price | $0.12/1M tokens | $0.06/1M tokens |
| Latency | ~450ms | ~250ms |
Choose Yi Large when:
- ✓ Long document analysis
- ✓ Research
- ✓ Complex tasks
200K context, Strong analysis, Good reasoning
Choose DeepSeek R1 Distill 32B when:
- ✓ Production reasoning
- ✓ Analysis
- ✓ Structured tasks
Good reasoning, Moderate cost, Fast
Verdict: Yi Large vs DeepSeek R1 Distill 32B
For cost efficiency, DeepSeek R1 Distill 32B wins at $0.03/1M input tokens. For speed, DeepSeek R1 Distill 32B is faster at ~250ms. Yi Large excels at Long document analysis 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
Yi Large costs $0.06/1M input tokens and $0.12/1M output tokens. DeepSeek R1 Distill 32B costs $0.03 input and $0.06 output. DeepSeek R1 Distill 32B is 2.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.
Performance & Context
Yi Large has a 200K context window with ~450ms latency. DeepSeek R1 Distill 32B offers 128K context at ~250ms. Yi Large has the larger context window.
Best For
Yi Large (Open Source) is optimized for: Long document analysis, Research, Complex tasks. 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 Yi Large
response_a = client.chat.completions.create(
model="yi-large",
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, Yi Large or DeepSeek R1 Distill 32B?
Yi Large (Open Source, 300B) offers 200K context. DeepSeek R1 Distill 32B (Reasoning, 32B) offers Good reasoning. Choose Yi Large for Long document analysis or DeepSeek R1 Distill 32B for Production reasoning.
How much does Yi Large cost vs DeepSeek R1 Distill 32B?
Yi Large: $0.06/1M input, $0.12/1M 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 Yi Large 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.