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DeepSeek V4 Pro 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 DeepSeek V4 Pro and Llama 3.2 11B Vision.

DeepSeek

DeepSeek V4 Pro

DeepSeek V4 Pro is a large-scale Mixture-of-Experts model from DeepSeek with 1.6T total parameters and 49B activated parameters, supporting a 1M-token context window. It is designed for advanced reasoning, coding,...

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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

SpecificationDeepSeek V4 ProLlama 3.2 11B Vision
ProviderDeepSeekMeta
Context Window1,048,576 tokens131,072 tokens
Agent Suitability94/10072/100
Time to First Token (TTFT)280 ms150 ms
Deployment Modelmanaged apiself hostable
Production Stabilitystablestable
API AvailableYesYes
Released Date2026-04-242024-09-25

API Pricing Comparison

Input Price per Million Tokens

DeepSeek V4 Pro

$0.43

Llama 3.2 11B Vision

$0.34

Output Price per Million Tokens

DeepSeek V4 Pro

$0.87

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
8850.0%vs7300.0%
DeepSeek V4 Pro
Llama 3.2 11B Vision
HumanEvalPython coding & logic synthesis
8900.0%vs7500.0%
DeepSeek V4 Pro
Llama 3.2 11B Vision
MATHComplex mathematical problem solving
7460.0%vs5800.0%
DeepSeek V4 Pro
Llama 3.2 11B Vision
GPQAGraduate-level expert reasoning
4900.0%vs3800.0%
DeepSeek V4 Pro
Llama 3.2 11B Vision
HellaSwagCommonsense reasoning and inference
8750.0%vs8200.0%
DeepSeek V4 Pro
Llama 3.2 11B Vision
MT-BenchMulti-turn conversation flow quality
918.0%vs790.0%
DeepSeek V4 Pro
Llama 3.2 11B Vision

DeepSeek V4 Pro Quirks & Gotchas

  • โ–ธMoE architecture โ€” cold-start latency on first request, use keep-alive
  • โ–ธBest cost-performance ratio of any frontier model โ€” strong tool calling for agentic use

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