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Claude Opus 4.7 vs Llama 3.2 11B Vision

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 3.2 11B Vision.

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 3.2 11B Vision

Meta's lightweight open weights vision model, optimized for mobile devices and local deployments. Capable of visual understanding, chart reading, and fast text generation.

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Technical Specifications

SpecificationClaude Opus 4.7Llama 3.2 11B Vision
ProviderAnthropicMeta
Context Window1,000,000 tokens131,072 tokens
Agent Suitability96/10072/100
Time to First Token (TTFT)480 ms150 ms
Deployment Modelmanaged apiself hostable
Production Stabilitystablestable
API AvailableYesYes
Released Date2026-04-162024-09-25

API Pricing Comparison

Input Price per Million Tokens

Claude Opus 4.7

$5.00

Llama 3.2 11B Vision

$0.34

Output Price per Million Tokens

Claude Opus 4.7

$25.00

Llama 3.2 11B Vision

$0.34

Want to test both models live?

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%vs7300.0%
Claude Opus 4.7
Llama 3.2 11B Vision
HumanEvalPython coding & logic synthesis
9610.0%vs7500.0%
Claude Opus 4.7
Llama 3.2 11B Vision
MATHComplex mathematical problem solving
9150.0%vs5800.0%
Claude Opus 4.7
Llama 3.2 11B Vision
GPQAGraduate-level expert reasoning
8420.0%vs3800.0%
Claude Opus 4.7
Llama 3.2 11B Vision
HellaSwagCommonsense reasoning and inference
9880.0%vs8200.0%
Claude Opus 4.7
Llama 3.2 11B Vision
MT-BenchMulti-turn conversation flow quality
975.0%vs790.0%
Claude Opus 4.7
Llama 3.2 11B Vision

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 3.2 11B Vision Quirks & Gotchas

  • โ–ธLightweight vision model for edge/on-device deployments
  • โ–ธLimited tool calling โ€” use Llama 4 for production agentic tasks