Claude Opus 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 Opus 4.6 at 200,000 tokens
  • · Claude Opus 4.6: Highest hit rate on SWE-bench among closed-source models
  • · Llama 3.3 70B Instruct: Open weights available — no vendor lock-in

Spec comparison

SpecClaude Opus 4.6Llama 3.3 70B Instruct
Provideranthropicmeta
Input per 1M tokens$5.00 / 1M$0.72 / 1M
Output per 1M tokens$25.00 / 1M$0.72 / 1M
Context window200,000 tok128,000 tok
Max output32,000 tok4,096 tok
Knowledge cutoff2025-072023-12
Vision
Tool calling
Structured output
Reasoning

Claude Opus 4.6 — strengths

  • +Highest hit rate on SWE-bench among closed-source models
  • +Excellent at multi-day agentic tasks without drift
  • +Top performance on multi-repo code analysis

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 Opus 4.6 — weaknesses

  • Substantially pricier per token than Sonnet — rarely worth the markup
  • Higher latency, especially with extended thinking enabled

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  • Knowledge cutoff December 2023 — outdated on recent facts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
Details: Claude Opus 4.6Details: Llama 3.3 70B Instruct