โ† Back to Model Hub/SIDE-BY-SIDE REVIEW
SHARE THIS:

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

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,...

View Full Specs
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...

View Full Specs

Technical Specifications

SpecificationDeepSeek V4 ProLlama 3.2 11B Vision Instruct
ProviderDeepSeekMeta
Context Window1,048,576 tokens131,072 tokens
Agent Suitability94/100N/A
Time to First Token (TTFT)280 msN/A
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 Instruct

$0.34

Output Price per Million Tokens

DeepSeek V4 Pro

$0.87

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
8850.0%vsN/A
DeepSeek V4 Pro
Llama 3.2 11B Vision Instruct
HumanEvalPython coding & logic synthesis
8900.0%vsN/A
DeepSeek V4 Pro
Llama 3.2 11B Vision Instruct
MATHComplex mathematical problem solving
7460.0%vsN/A
DeepSeek V4 Pro
Llama 3.2 11B Vision Instruct
GPQAGraduate-level expert reasoning
4900.0%vsN/A
DeepSeek V4 Pro
Llama 3.2 11B Vision Instruct
HellaSwagCommonsense reasoning and inference
8750.0%vsN/A
DeepSeek V4 Pro
Llama 3.2 11B Vision Instruct
MT-BenchMulti-turn conversation flow quality
918.0%vsN/A
DeepSeek V4 Pro
Llama 3.2 11B Vision Instruct

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 Instruct Quirks & Gotchas

No developer gotchas reported.