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Claude Opus 4.5 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 4.5 and Llama 3.2 11B Vision.

Anthropic

Claude Opus 4.5

Claude Opus 4.5 is Anthropic’s frontier reasoning model optimized for complex software engineering, agentic workflows, and long-horizon computer use. It offers strong multimodal capabilities, competitive performance across real-world coding and...

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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 4.5Llama 3.2 11B Vision
ProviderAnthropicMeta
Context Window200,000 tokens131,072 tokens
Agent Suitability93/10072/100
Time to First Token (TTFT)550 ms150 ms
Deployment Modelmanaged apiself hostable
Production Stabilitystablestable
API AvailableYesYes
Released Date2025-11-242024-09-25

API Pricing Comparison

Input Price per Million Tokens

Claude Opus 4.5

$5.00

Llama 3.2 11B Vision

$0.34

Output Price per Million Tokens

Claude Opus 4.5

$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
9280.0%vs7300.0%
Claude Opus 4.5
Llama 3.2 11B Vision
HumanEvalPython coding & logic synthesis
9420.0%vs7500.0%
Claude Opus 4.5
Llama 3.2 11B Vision
MATHComplex mathematical problem solving
8750.0%vs5800.0%
Claude Opus 4.5
Llama 3.2 11B Vision
GPQAGraduate-level expert reasoning
7600.0%vs3800.0%
Claude Opus 4.5
Llama 3.2 11B Vision
HellaSwagCommonsense reasoning and inference
9720.0%vs8200.0%
Claude Opus 4.5
Llama 3.2 11B Vision
MT-BenchMulti-turn conversation flow quality
955.0%vs790.0%
Claude Opus 4.5
Llama 3.2 11B Vision

Claude Opus 4.5 Quirks & Gotchas

  • Deep analytical reasoning — best for structured problem-solving
  • 200K context is limiting compared to 1M of Opus 4.6+ — upgrade for long-document tasks

Llama 3.2 11B Vision Quirks & Gotchas

  • Lightweight vision model for edge/on-device deployments
  • Limited tool calling — use Llama 4 for production agentic tasks