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Llama 3.1 8B vs Qwen3 30B A3B Thinking 2507

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 30B A3B Thinking 2507.

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 β€” making it the default choice for on-device AI applications and local prototyping.

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Alibaba

Qwen3 30B A3B Thinking 2507

Qwen3-30B-A3B-Thinking-2507 is a 30B parameter Mixture-of-Experts reasoning model optimized for complex tasks requiring extended multi-step thinking. The model is designed specifically for β€œthinking mode,” where internal reasoning traces are separated...

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Technical Specifications

SpecificationLlama 3.1 8BQwen3 30B A3B Thinking 2507
ProviderMetaAlibaba
Context Window131,072 tokens131,072 tokens
Agent Suitability74/100N/A
Time to First Token (TTFT)80 msN/A
Deployment Modelself hostableself hostable
Production Stabilitystablestable
API AvailableYesYes
Released Date2024-07-232025-08-28

API Pricing Comparison

Input Price per Million Tokens

Llama 3.1 8B

$0.04

Qwen3 30B A3B Thinking 2507

$0.13

Output Price per Million Tokens

Llama 3.1 8B

$0.04

Qwen3 30B A3B Thinking 2507

$1.56

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

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

Qwen3 30B A3B Thinking 2507 Quirks & Gotchas

No developer gotchas reported.