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GPT-5.5 vs Llama 3.2 11B Vision 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 GPT-5.5 and Llama 3.2 11B Vision Instruct.

OpenAI

GPT-5.5

GPT-5.5 is OpenAI’s frontier model designed for complex professional workloads, building on GPT-5.4 with stronger reasoning, higher reliability, and improved token efficiency on hard tasks. It features a 1M+ token...

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Meta

Llama 3.2 11B Vision Instruct

Llama 3.2 11B Vision is a multimodal model with 11 billion parameters, designed to handle tasks combining visual and textual data. It excels in tasks such as image captioning and...

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Technical Specifications

SpecificationGPT-5.5Llama 3.2 11B Vision Instruct
ProviderOpenAIMeta
Context Window1,050,000 tokens131,072 tokens
Agent Suitability95/100N/A
Time to First Token (TTFT)380 msN/A
Deployment Modelmanaged apiself hostable
Production Stabilitystablestable
API AvailableYesYes
Released Date2026-04-242024-09-25

API Pricing Comparison

Input Price per Million Tokens

GPT-5.5

$5.00

Llama 3.2 11B Vision Instruct

$0.34

Output Price per Million Tokens

GPT-5.5

$30.00

Llama 3.2 11B Vision Instruct

$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
9420.0%vsN/A
GPT-5.5
Llama 3.2 11B Vision Instruct
HumanEvalPython coding & logic synthesis
9680.0%vsN/A
GPT-5.5
Llama 3.2 11B Vision Instruct
MATHComplex mathematical problem solving
9350.0%vsN/A
GPT-5.5
Llama 3.2 11B Vision Instruct
GPQAGraduate-level expert reasoning
8420.0%vsN/A
GPT-5.5
Llama 3.2 11B Vision Instruct
HellaSwagCommonsense reasoning and inference
9900.0%vsN/A
GPT-5.5
Llama 3.2 11B Vision Instruct
MT-BenchMulti-turn conversation flow quality
970.0%vsN/A
GPT-5.5
Llama 3.2 11B Vision Instruct

GPT-5.5 Quirks & Gotchas

  • Best for JSON schema adherence — strict mode available via response_format parameter
  • Requires explicit tool_choice for deterministic function calling

Llama 3.2 11B Vision Instruct Quirks & Gotchas

No developer gotchas reported.