Yi Large vs Nemotron 4 340B

Compare Yi Large 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

All 01.AI models All NVIDIA models What is an LLM API? Python Quickstart What is inference?
Feature Yi Large Nemotron 4 340B
CategoryOpen SourceOpen Source
Parameters300B340B
Context Window200K128K
Input Price$0.06/1M tokens$0.07/1M tokens
Output Price$0.12/1M tokens$0.12/1M tokens
Latency~450ms~500ms

Choose Yi Large when:

  • ✓ Long document analysis
  • ✓ Research
  • ✓ Complex tasks
Key Strengths:

200K context, Strong analysis, Good reasoning

Choose Nemotron 4 340B when:

  • ✓ Data generation
  • ✓ Training data
  • ✓ Research
Key Strengths:

Synthetic data generation, Large scale, Good quality

Verdict: Yi Large vs Nemotron 4 340B

For cost efficiency, Yi Large wins at $0.06/1M input tokens. For speed, Yi Large is faster at ~450ms. Yi Large excels at Long document 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

Yi Large costs $0.06/1M input tokens and $0.12/1M output tokens. Nemotron 4 340B costs $0.07 input and $0.12 output. Yi Large is 1.2x 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. Nemotron 4 340B offers 128K context at ~500ms. Yi Large has the larger context window.

Best For

Yi Large (Open Source) is optimized for: Long document analysis, Research, Complex tasks. 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 Yi Large
response_a = client.chat.completions.create(
    model="yi-large",
    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"}]
)

Start Building with XALEN

200+ AI models. One API. Pay-as-you-go.

Get API Key Try in Playground

Frequently Asked Questions

Which is better, Yi Large or Nemotron 4 340B?

Yi Large (Open Source, 300B) offers 200K context. Nemotron 4 340B (Open Source, 340B) offers Synthetic data generation. Choose Yi Large for Long document analysis or Nemotron 4 340B for Data generation.

How much does Yi Large cost vs Nemotron 4 340B?

Yi Large: $0.06/1M input, $0.12/1M 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 Yi Large and Nemotron 4 340B by changing the model parameter. No code changes needed.

Related Comparisons

Yi Large vs Gemma 3 27B Yi Large vs Llama 4 Scout Yi Large vs Llama 4 Maverick Yi Large vs Llama 3.3 70B Yi Large vs Llama 3.1 405B Yi Large vs Llama 3.1 70B Turbo

Last updated: 2026-05-21. Pricing and specifications may change. Check pricing page for latest rates.