Arctic Large vs Code Llama 70B
Compare Arctic Large and Code Llama 70B: pricing, performance, context window, latency, and best use cases. Side-by-side comparison on XALEN.
Updated 2026-05-21 · By Abhishek Raj · Our methodology
| Feature | Arctic Large | Code Llama 70B |
|---|---|---|
| Category | Enterprise | Code |
| Parameters | 480B (17B active) | 70B |
| Context Window | 128K | 100K |
| Input Price | $0.06/1M tokens | $0.04/1M tokens |
| Output Price | $0.10/1M tokens | $0.06/1M tokens |
| Latency | ~400ms | ~300ms |
Choose Arctic Large when:
- ✓ Data analysis
- ✓ SQL generation
- ✓ Business intelligence
Strong SQL, Data analysis, Enterprise features
Choose Code Llama 70B when:
- ✓ Large codebases
- ✓ Code review
- ✓ Refactoring
100K context, Strong coding, Fill-in-middle
Verdict: Arctic Large vs Code Llama 70B
For cost efficiency, Code Llama 70B wins at $0.04/1M input tokens. For speed, Code Llama 70B is faster at ~300ms. Arctic Large excels at Data analysis while Code Llama 70B is better for Large codebases. Both are available on XALEN through a single API — try them in the Playground to see which fits your workload.
Detailed Analysis
Pricing Comparison
Arctic Large costs $0.06/1M input tokens and $0.10/1M output tokens. Code Llama 70B costs $0.04 input and $0.06 output. Code Llama 70B is 1.5x cheaper on input tokens. XALEN offers batch processing at 50% discount on both models.
Performance & Context
Arctic Large has a 128K context window with ~400ms latency. Code Llama 70B offers 100K context at ~300ms. Arctic Large has the larger context window.
Best For
Arctic Large (Enterprise) is optimized for: Data analysis, SQL generation, Business intelligence. Code Llama 70B (Code) works best for: Large codebases, Code review, Refactoring.
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 Arctic Large
response_a = client.chat.completions.create(
model="arctic-large",
messages=[{"role": "user", "content": "Your question here"}]
)
# Use Code Llama 70B
response_b = client.chat.completions.create(
model="codellama-70b",
messages=[{"role": "user", "content": "Your question here"}]
)
Frequently Asked Questions
Which is better, Arctic Large or Code Llama 70B?
Arctic Large (Enterprise, 480B (17B active)) offers Strong SQL. Code Llama 70B (Code, 70B) offers 100K context. Choose Arctic Large for Data analysis or Code Llama 70B for Large codebases.
How much does Arctic Large cost vs Code Llama 70B?
Arctic Large: $0.06/1M input, $0.10/1M output. Code Llama 70B: $0.04/1M input, $0.06/1M 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 Arctic Large and Code Llama 70B 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.