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Llama 3.1 8B 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 3.1 8B and Qwen3 VL 235B A22B Instruct.

Meta

Llama 3.1 8B

Llama 3.1 8B is Meta's lightweight open-weight model from the Llama 3.1 generation, optimized for efficient deployment on consumer hardware and edge devices. Despite its compact 8-billion-parameter size, it delivers strong performance on instruction following, text summarization, and lightweight coding tasks. Lllama 3.1 8B is the most downloaded model in the Llama family and runs efficiently on laptops, single GPUs, and CPU via quantization โ€” making it the default choice for on-device AI applications and local prototyping.

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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 3.1 8BQwen3 VL 235B A22B Instruct
ProviderMetaAlibaba
Context Window131,072 tokens262,144 tokens
Agent Suitability74/100N/A
Time to First Token (TTFT)80 msN/A
Deployment Modelself hostableself hostable
Production Stabilitystablestable
API AvailableYesYes
Released Date2024-07-232025-09-23

API Pricing Comparison

Input Price per Million Tokens

Llama 3.1 8B

$0.04

Qwen3 VL 235B A22B Instruct

$0.20

Output Price per Million Tokens

Llama 3.1 8B

$0.04

Qwen3 VL 235B A22B Instruct

$0.88

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.

Llama 3.1 8B Quirks & Gotchas

  • โ–ธPerfect for CPU/edge deployment โ€” runs on Raspberry Pi with quantization
  • โ–ธLimited tool calling vs larger models โ€” best for simple classification and chat

Qwen3 VL 235B A22B Instruct Quirks & Gotchas

No developer gotchas reported.