Claude Sonnet 4.6 vs Llama 3.3 70B Instruct
Direct comparison between anthropic and meta for chat models. Specs, prices, strengths, weaknesses — decide on facts.
At a glance
- · Cheaper: Llama 3.3 70B Instruct
- · Longer context window: Claude Sonnet 4.6 at 200,000 tokens
- · Claude Sonnet 4.6: Best-in-class for code refactoring and multi-step pull requests
- · Llama 3.3 70B Instruct: Open weights available — no vendor lock-in
Spec comparison
| Spec | Claude Sonnet 4.6 | Llama 3.3 70B Instruct |
|---|---|---|
| Provider | anthropic | meta |
| Input per 1M tokens | $3.00 / 1M | $0.72 / 1M |
| Output per 1M tokens | $15.00 / 1M | $0.72 / 1M |
| Context window | 200,000 tok | 128,000 tok |
| Max output | 64,000 tok | 4,096 tok |
| Knowledge cutoff | 2025-07 | 2023-12 |
| Vision | ||
| Tool calling | ||
| Structured output | ||
| Reasoning |
Claude Sonnet 4.6 — strengths
- +Best-in-class for code refactoring and multi-step pull requests
- +Very stable tool-use loops — low hallucination on arguments
- +64k output tokens fit whole files in one response
Llama 3.3 70B Instruct — strengths
- +Open weights available — no vendor lock-in
- +Very cheap per token, widely available across providers
- +Solid all-rounder for classification and simple generation
Claude Sonnet 4.6 — weaknesses
- −Knowledge cutoff July 2025 — no recent web knowledge
- −No native JSON mode — schema enforcement via tool-call trick
Llama 3.3 70B Instruct — weaknesses
- −Knowledge cutoff December 2023 — outdated on recent facts
- −No native vision or audio input
- −Behind Claude Sonnet and GPT-5 across nearly all benchmarks