E5 Large v2 vs Nemotron 4 340B

Compare E5 Large v2 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 Microsoft models All NVIDIA models What is an LLM API? Python Quickstart What is inference?
Feature E5 Large v2 Nemotron 4 340B
CategoryEmbeddingOpen Source
Parameters335M340B
Context Window512128K
Input Price$0.002/1M tokens$0.07/1M tokens
Output PriceN/A/1M tokens$0.12/1M tokens
Latency~20ms~500ms

Choose E5 Large v2 when:

  • ✓ Classical text search
  • ✓ RAG pipelines
  • ✓ Knowledge retrieval
Key Strengths:

1024 dimensions, Fast, Multi-lingual

Choose Nemotron 4 340B when:

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

Synthetic data generation, Large scale, Good quality

Verdict: E5 Large v2 vs Nemotron 4 340B

For cost efficiency, E5 Large v2 wins at $0.002/1M input tokens. For speed, E5 Large v2 is faster at ~20ms. E5 Large v2 excels at Classical text search 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

E5 Large v2 costs $0.002/1M input tokens and N/A/1M output tokens. Nemotron 4 340B costs $0.07 input and $0.12 output. E5 Large v2 is 35.0x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

E5 Large v2 has a 512 context window with ~20ms latency. Nemotron 4 340B offers 128K context at ~500ms. Nemotron 4 340B has the larger context window.

Best For

E5 Large v2 (Embedding) is optimized for: Classical text search, RAG pipelines, Knowledge retrieval. 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 E5 Large v2
response_a = client.chat.completions.create(
    model="e5-large-v2",
    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, E5 Large v2 or Nemotron 4 340B?

E5 Large v2 (Embedding, 335M) offers 1024 dimensions. Nemotron 4 340B (Open Source, 340B) offers Synthetic data generation. Choose E5 Large v2 for Classical text search or Nemotron 4 340B for Data generation.

How much does E5 Large v2 cost vs Nemotron 4 340B?

E5 Large v2: $0.002/1M input, N/A/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 E5 Large v2 and Nemotron 4 340B by changing the model parameter. No code changes needed.

Related Comparisons

E5 Large v2 vs Text Embedding 3 Large E5 Large v2 vs Gemma 3 27B E5 Large v2 vs Llama 4 Scout E5 Large v2 vs Llama 4 Maverick E5 Large v2 vs Llama 3.3 70B E5 Large v2 vs Llama 3.1 405B

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