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GPT-3.5 Turbo (older v0613) vs Llama 3.1 405B

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 GPT-3.5 Turbo (older v0613) and Llama 3.1 405B.

OpenAI

GPT-3.5 Turbo (older v0613)

GPT-3.5 Turbo is OpenAI's fastest model. It can understand and generate natural language or code, and is optimized for chat and traditional completion tasks. Training data up to Sep 2021.

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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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Technical Specifications

SpecificationGPT-3.5 Turbo (older v0613)Llama 3.1 405B
ProviderOpenAIMeta
Context Window4,095 tokens131,072 tokens
Agent SuitabilityN/A90/100
Time to First Token (TTFT)N/A550 ms
Deployment Modelmanaged apiself hostable
Production Stabilitystablestable
API AvailableYesYes
Released Date2024-01-252024-07-23

API Pricing Comparison

Input Price per Million Tokens

GPT-3.5 Turbo (older v0613)

$1.00

Llama 3.1 405B

$0.80

Output Price per Million Tokens

GPT-3.5 Turbo (older v0613)

$2.00

Llama 3.1 405B

$0.80

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.

GPT-3.5 Turbo (older v0613) Quirks & Gotchas

No developer gotchas reported.

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