Llama 4 Scout vs IBM Granite 3.1 2B

Compare Llama 4 Scout and IBM Granite 3.1 2B: 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 Meta models All IBM models What is an LLM API? Python Quickstart What is inference?
Feature Llama 4 Scout IBM Granite 3.1 2B
CategoryOpen SourceCompact
Parameters109B (17B active)2B
Context Window512K128K
Input Price$0.05/1M tokens$0.004/1M tokens
Output Price$0.08/1M tokens$0.008/1M tokens
Latency~350ms~30ms

Choose Llama 4 Scout when:

  • ✓ Classical text analysis
  • ✓ Long content
  • ✓ Multi-turn
Key Strengths:

512K context, MoE efficiency, Strong multilingual

Choose IBM Granite 3.1 2B when:

  • ✓ Edge enterprise
  • ✓ Compliance-required
  • ✓ Fast classification
Key Strengths:

Enterprise-grade, Tiny, 128K context

Verdict: Llama 4 Scout vs IBM Granite 3.1 2B

For cost efficiency, IBM Granite 3.1 2B wins at $0.004/1M input tokens. For speed, IBM Granite 3.1 2B is faster at ~30ms. Llama 4 Scout excels at Classical text analysis while IBM Granite 3.1 2B is better for Edge enterprise. Both are available on XALEN through a single API — try them in the Playground to see which fits your workload.

Detailed Analysis

Pricing Comparison

Llama 4 Scout costs $0.05/1M input tokens and $0.08/1M output tokens. IBM Granite 3.1 2B costs $0.004 input and $0.008 output. IBM Granite 3.1 2B is 12.5x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

Llama 4 Scout has a 512K context window with ~350ms latency. IBM Granite 3.1 2B offers 128K context at ~30ms. Llama 4 Scout has the larger context window.

Best For

Llama 4 Scout (Open Source) is optimized for: Classical text analysis, Long content, Multi-turn. IBM Granite 3.1 2B (Compact) works best for: Edge enterprise, Compliance-required, Fast classification.

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 Llama 4 Scout
response_a = client.chat.completions.create(
    model="llama-4-scout",
    messages=[{"role": "user", "content": "Your question here"}]
)

# Use IBM Granite 3.1 2B
response_b = client.chat.completions.create(
    model="granite-3-1-2b",
    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, Llama 4 Scout or IBM Granite 3.1 2B?

Llama 4 Scout (Open Source, 109B (17B active)) offers 512K context. IBM Granite 3.1 2B (Compact, 2B) offers Enterprise-grade. Choose Llama 4 Scout for Classical text analysis or IBM Granite 3.1 2B for Edge enterprise.

How much does Llama 4 Scout cost vs IBM Granite 3.1 2B?

Llama 4 Scout: $0.05/1M input, $0.08/1M output. IBM Granite 3.1 2B: $0.004/1M input, $0.008/1M 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 Llama 4 Scout and IBM Granite 3.1 2B by changing the model parameter. No code changes needed.

Related Comparisons

Llama 4 Scout vs GPT-4.1 Nano Llama 4 Scout vs GPT-4o Mini Llama 4 Scout vs Claude Haiku 3.5 Llama 4 Scout vs Gemma 3 27B Llama 4 Scout vs Gemma 3 12B Llama 4 Scout vs Gemma 3 4B

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