Code Llama 70B vs Meshy v4

Compare Code Llama 70B and Meshy v4: 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 Meshy models What is an LLM API? Python Quickstart What is inference?
Feature Code Llama 70B Meshy v4
CategoryCode3D
Parameters70B~3B
Context Window100KN/A
Input Price$0.04/1M tokens$0.10/model/1M tokens
Output Price$0.06/1M tokensN/A/1M tokens
Latency~300ms~60s

Choose Code Llama 70B when:

  • ✓ Large codebases
  • ✓ Code review
  • ✓ Refactoring
Key Strengths:

100K context, Strong coding, Fill-in-middle

Choose Meshy v4 when:

  • ✓ 3D asset creation
  • ✓ Game assets
  • ✓ Product visualization
Key Strengths:

3D model output, PBR textures, Multiple formats

Verdict: Code Llama 70B vs Meshy v4

For cost efficiency, Code Llama 70B wins at $0.04/1M input tokens. For speed, Code Llama 70B is faster at ~300ms. Code Llama 70B excels at Large codebases while Meshy v4 is better for 3D asset creation. Both are available on XALEN through a single API — try them in the Playground to see which fits your workload.

Detailed Analysis

Pricing Comparison

Code Llama 70B costs $0.04/1M input tokens and $0.06/1M output tokens. Meshy v4 costs $0.10/model input and N/A output. Code Llama 70B is 2.5x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.

Performance & Context

Code Llama 70B has a 100K context window with ~300ms latency. Meshy v4 offers N/A context at ~60s. Code Llama 70B has the larger context window.

Best For

Code Llama 70B (Code) is optimized for: Large codebases, Code review, Refactoring. Meshy v4 (3D) works best for: 3D asset creation, Game assets, Product visualization.

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 Code Llama 70B
response_a = client.chat.completions.create(
    model="codellama-70b",
    messages=[{"role": "user", "content": "Your question here"}]
)

# Use Meshy v4
response_b = client.chat.completions.create(
    model="meshy-4",
    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, Code Llama 70B or Meshy v4?

Code Llama 70B (Code, 70B) offers 100K context. Meshy v4 (3D, ~3B) offers 3D model output. Choose Code Llama 70B for Large codebases or Meshy v4 for 3D asset creation.

How much does Code Llama 70B cost vs Meshy v4?

Code Llama 70B: $0.04/1M input, $0.06/1M output. Meshy v4: $0.10/model/1M input, N/A/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 Code Llama 70B and Meshy v4 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.