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Llama 3.1 405B 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 405B and Qwen3 VL 235B A22B Instruct.

Meta

Llama 3.1 405B

Llama 3.1 405B is Meta's largest open-weight language model and one of the most capable openly available models in the world. With 405 billion parameters, it achieves performance competitive with GPT-4 and Claude Opus across benchmarks spanning general knowledge, mathematics, coding, and multilingual tasks. Llama 3.1 405B is released under Meta's custom commercial license, supporting broad use cases including deployment via major cloud providers (AWS, GCP, Azure) and self-hosted inference with multi-GPU configurations.

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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 405BQwen3 VL 235B A22B Instruct
ProviderMetaAlibaba
Context Window131,072 tokens262,144 tokens
Agent Suitability90/100N/A
Time to First Token (TTFT)550 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 405B

$0.80

Qwen3 VL 235B A22B Instruct

$0.20

Output Price per Million Tokens

Llama 3.1 405B

$0.80

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 405B Quirks & Gotchas

  • โ–ธMassive model โ€” requires 8ร— A100 80GB for FP16 inference
  • โ–ธAvailable via Together AI, Fireworks, and Bedrock as managed API

Qwen3 VL 235B A22B Instruct Quirks & Gotchas

No developer gotchas reported.