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Claude Opus 4.7 vs Llama 3.3 70B Instruct

How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for Claude Opus 4.7 and Llama 3.3 70B Instruct.

Anthropic

Claude Opus 4.7

Opus 4.7 is the next generation of Anthropic's Opus family, built for long-running, asynchronous agents. Building on the coding and agentic strengths of Opus 4.6, it delivers stronger performance on...

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Meta

Llama 3.3 70B Instruct

The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). The Llama 3.3 instruction tuned text only model...

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Technical Specifications

SpecificationClaude Opus 4.7Llama 3.3 70B Instruct
ProviderAnthropicMeta
Context Window1,000,000 tokens131,072 tokens
Agent Suitability96/100N/A
Time to First Token (TTFT)480 msN/A
Deployment Modelmanaged apiself hostable
Production Stabilitystablestable
API AvailableYesYes
Released Date2026-04-162024-12-06

API Pricing Comparison

Input Price per Million Tokens

Claude Opus 4.7

$5.00

Llama 3.3 70B Instruct

$0.10

Output Price per Million Tokens

Claude Opus 4.7

$25.00

Llama 3.3 70B Instruct

$0.32

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Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.

Benchmark Performance Metrics

Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.

MMLUGeneral knowledge & multi-task understanding
9410.0%vsN/A
Claude Opus 4.7
Llama 3.3 70B Instruct
HumanEvalPython coding & logic synthesis
9610.0%vsN/A
Claude Opus 4.7
Llama 3.3 70B Instruct
MATHComplex mathematical problem solving
9150.0%vsN/A
Claude Opus 4.7
Llama 3.3 70B Instruct
GPQAGraduate-level expert reasoning
8420.0%vsN/A
Claude Opus 4.7
Llama 3.3 70B Instruct
HellaSwagCommonsense reasoning and inference
9880.0%vsN/A
Claude Opus 4.7
Llama 3.3 70B Instruct
MT-BenchMulti-turn conversation flow quality
975.0%vsN/A
Claude Opus 4.7
Llama 3.3 70B Instruct

Claude Opus 4.7 Quirks & Gotchas

  • โ–ธTop-tier agentic coding model โ€” excels at autonomous software engineering
  • โ–ธRequires explicit tool_choice parameter for parallel function calling to work reliably

Llama 3.3 70B Instruct Quirks & Gotchas

No developer gotchas reported.