Mistral Medium 3 vs Nemotron 4 340B

Compare Mistral Medium 3 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 Mistral models All NVIDIA models What is an LLM API? Python Quickstart What is inference?
Feature Mistral Medium 3 Nemotron 4 340B
CategoryOpen SourceOpen Source
Parameters70B340B
Context Window128K128K
Input Price$0.04/1M tokens$0.07/1M tokens
Output Price$0.08/1M tokens$0.12/1M tokens
Latency~300ms~500ms

Choose Mistral Medium 3 when:

  • ✓ Production APIs
  • ✓ Template filling
  • ✓ General purpose
Key Strengths:

Good balance, Strong function calling, Reliable

Choose Nemotron 4 340B when:

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

Synthetic data generation, Large scale, Good quality

Verdict: Mistral Medium 3 vs Nemotron 4 340B

For cost efficiency, Mistral Medium 3 wins at $0.04/1M input tokens. For speed, Mistral Medium 3 is faster at ~300ms. Mistral Medium 3 excels at Production APIs 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

Mistral Medium 3 costs $0.04/1M input tokens and $0.08/1M output tokens. Nemotron 4 340B costs $0.07 input and $0.12 output. Mistral Medium 3 is 1.8x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

Mistral Medium 3 has a 128K context window with ~300ms latency. Nemotron 4 340B offers 128K context at ~500ms. Both have identical context windows.

Best For

Mistral Medium 3 (Open Source) is optimized for: Production APIs, Template filling, General purpose. 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 Mistral Medium 3
response_a = client.chat.completions.create(
    model="mistral-medium-3",
    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, Mistral Medium 3 or Nemotron 4 340B?

Mistral Medium 3 (Open Source, 70B) offers Good balance. Nemotron 4 340B (Open Source, 340B) offers Synthetic data generation. Choose Mistral Medium 3 for Production APIs or Nemotron 4 340B for Data generation.

How much does Mistral Medium 3 cost vs Nemotron 4 340B?

Mistral Medium 3: $0.04/1M input, $0.08/1M 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 Mistral Medium 3 and Nemotron 4 340B by changing the model parameter. No code changes needed.

Related Comparisons

Mistral Medium 3 vs Gemma 3 27B Mistral Medium 3 vs Llama 4 Scout Mistral Medium 3 vs Llama 4 Maverick Mistral Medium 3 vs Llama 3.3 70B Mistral Medium 3 vs Llama 3.1 405B Mistral Medium 3 vs Llama 3.1 70B Turbo

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