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Llama 3.2 11B Vision vs Qwen3 VL 235B A22B 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 Llama 3.2 11B Vision and Qwen3 VL 235B A22B Instruct.

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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Alibaba

Qwen3 VL 235B A22B Instruct

Qwen3-VL-235B-A22B Instruct is an open-weight multimodal model that unifies strong text generation with visual understanding across images and video. The Instruct model targets general vision-language use (VQA, document parsing, chart/table...

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Technical Specifications

SpecificationLlama 3.2 11B VisionQwen3 VL 235B A22B Instruct
ProviderMetaAlibaba
Context Window131,072 tokens262,144 tokens
Agent Suitability72/100N/A
Time to First Token (TTFT)150 msN/A
Deployment Modelself hostableself hostable
Production Stabilitystablestable
API AvailableYesYes
Released Date2024-09-252025-09-23

API Pricing Comparison

Input Price per Million Tokens

Llama 3.2 11B Vision

$0.34

Qwen3 VL 235B A22B Instruct

$0.20

Output Price per Million Tokens

Llama 3.2 11B Vision

$0.34

Qwen3 VL 235B A22B Instruct

$0.88

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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
7300.0%vsN/A
Llama 3.2 11B Vision
Qwen3 VL 235B A22B Instruct
HumanEvalPython coding & logic synthesis
7500.0%vsN/A
Llama 3.2 11B Vision
Qwen3 VL 235B A22B Instruct
MATHComplex mathematical problem solving
5800.0%vsN/A
Llama 3.2 11B Vision
Qwen3 VL 235B A22B Instruct
GPQAGraduate-level expert reasoning
3800.0%vsN/A
Llama 3.2 11B Vision
Qwen3 VL 235B A22B Instruct
HellaSwagCommonsense reasoning and inference
8200.0%vsN/A
Llama 3.2 11B Vision
Qwen3 VL 235B A22B Instruct
MT-BenchMulti-turn conversation flow quality
790.0%vsN/A
Llama 3.2 11B Vision
Qwen3 VL 235B A22B Instruct

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

Qwen3 VL 235B A22B Instruct Quirks & Gotchas

No developer gotchas reported.