Which is cheaper, GPT-4o or Llama 3.1 8B Instruct?
As of August 20, 2026, Llama 3.1 8B Instruct is 100% cheaper on blended LLM API pricing. Llama 3.1 8B Instruct costs $0.03 per million input tokens and $0.03 per million output tokens ($0.06 blended 1M-in + 1M-out). GPT-4o costs $2.50 / $10.00 per million tokens ($12.50 blended). Sources: https://developers.openai.com/api/docs/pricing and https://llama.meta.com/. The cheapest LLM for your app still depends on how many output tokens you generate.
How much does GPT-4o vs Llama 3.1 8B Instruct cost per million tokens?
GPT-4o OpenAI API pricing is $2.50 input and $10.00 output per million tokens via OpenAI. Llama 3.1 8B Instruct Meta API pricing is $0.03 input and $0.03 output per million tokens via Meta. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.
Which is better for coding, GPT-4o or Llama 3.1 8B Instruct?
GPT-4o leads on HumanEval: GPT-4o at 90.2% vs Llama 3.1 8B Instruct at 72.6%. SWE-bench measures real GitHub fixes; LiveCodeBench measures contest programming.
What is the context window for GPT-4o vs Llama 3.1 8B Instruct?
GPT-4o supports a 128K token context window, while Llama 3.1 8B Instruct supports 131K tokens. Llama 3.1 8B Instruct offers a larger context window. Filling a larger window bills more input tokens, so the cheaper-per-million model can still cost more on long documents.
Which model performs better on benchmarks, GPT-4o or Llama 3.1 8B Instruct?
GPT-4o leads on 8 of 8 shared benchmarks versus Llama 3.1 8B Instruct's 0 wins. Check the comparison table for GPQA Diamond, SWE-bench, MMLU, HLE, and the other evals we track. Token price and benchmark score together are the usual LLM comparison, not either number alone.
Is GPT-4o or Llama 3.1 8B Instruct better for production use?
Both GPT-4o and Llama 3.1 8B Instruct are production API models. For cost-sensitive production traffic, Llama 3.1 8B Instruct has better economics on the blended 1M-in + 1M-out scale. For maximum capability, weight the benchmark table for your domain. Many production stacks route cheap models for drafts and a frontier model for the hard turn, which is usually cheaper than sending everything to the expensive API.
Can I switch between GPT-4o and Llama 3.1 8B Instruct in my app?
Yes. Call GPT-4o through OpenAI and Llama 3.1 8B Instruct through Meta with separate API keys, or through a gateway that already wraps both. Keep prompts in tokens, not characters, when you estimate the invoice. AnotherWrapper templates can swap providers without rewriting auth and billing.
How accurate is this GPT-4o vs Llama 3.1 8B Instruct pricing data?
List rates are the latest published OpenAI API pricing and Meta API pricing, quoted per million tokens. Official rate sheets: https://developers.openai.com/api/docs/pricing and https://llama.meta.com/. Prompt caching, batch APIs, and committed-use discounts can change the invoice. Benchmark scores are from official publications and independent evals, updated as new numbers land.
What is the output token limit for GPT-4o and Llama 3.1 8B Instruct?
GPT-4o supports up to 4K output tokens per request, while Llama 3.1 8B Instruct supports up to 131K output tokens. Output tokens are usually the expensive half of API pricing, so a higher max output cap is a capability, not a discount.
Which model has better throughput, GPT-4o or Llama 3.1 8B Instruct?
GPT-4o runs at approximately 100 tokens/second while Llama 3.1 8B Instruct runs at 42 tokens/second. GPT-4o is faster in raw throughput. Throughput (tokens per second) and time-to-first-token are why two models with the same per-million-token price can still feel different in chat and agents.
How do I switch the models in this GPT-4o vs Llama 3.1 8B Instruct comparison?
Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open GPT-4o or Llama 3.1 8B Instruct from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.
