AI model comparison

Llama 3.3 70B Instruct vs GPT-4o-mini

Pricing, context window, benchmarks, and features compared side by side. Or skip the guesswork and send one prompt to both.

The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out).

Input / 1M
$0.22
Output / 1M
$0.50
Context
131K

GPT-4o mini is OpenAI's newest model after [GPT-4 Omni](/models/openai/gpt-4o), supporting both text and image inputs with text outputs.

Input / 1M
$0.15
Output / 1M
$0.60
Context
128K

At a glance

Quick verdict

How the two models stack up on the things people ask about most.

Lower price

openai logo

GPT-4o-mini

1.2x cheaper for a typical chat

Higher intelligence score

meta-llama logo

Llama 3.3 70B Instruct

7.7 vs 6.7 on Artificial Analysis

Larger context window

meta-llama logo

Llama 3.3 70B Instruct

131K vs 128K tokens

Newer release

meta-llama logo

Llama 3.3 70B Instruct

Released December 6, 2024

Benchmarks

Benchmark scores

Independent scores from Artificial Analysis. Higher is better.

Intelligence index

meta-llama logoLlama 3.3 70B Instruct7.7
openai logoGPT-4o-mini6.7

Coding index

meta-llama logoLlama 3.3 70B Instruct11.9
openai logoGPT-4o-mini11.4

Agentic index

meta-llama logoLlama 3.3 70B InstructNot available
openai logoGPT-4o-miniNot available

Pricing

Llama 3.3 70B Instruct vs GPT-4o-mini API pricing

Per-token API rates. Cheaper option highlighted.

Metricmeta-llama logoLlama 3.3 70B Instructopenai logoGPT-4o-mini
Input tokensPer 1M tokens$0.22$0.15
Output tokensPer 1M tokens$0.50$0.60
Cached input (read)Per 1M tokens$0.11$0.08
Cache writePer 1M tokensNot availableNot available

What it costs in practice

Estimated cost per 1,000 requests at standard rates. Coding and long-document figures also show the cost when the input is already cached.

Chat message

2K in, 500 out

meta-llama logoLlama 3.3 70B Instruct$0.69
openai logoGPT-4o-mini$0.60

Coding task

30K in, 4K out

meta-llama logoLlama 3.3 70B Instruct$8.60$5.30 cached
openai logoGPT-4o-mini$6.90$4.65 cached

Long document summary

150K in, 2K out

meta-llama logoLlama 3.3 70B Instruct$34$17.50 cached
openai logoGPT-4o-mini$23.70$12.45 cached

Specs

Context window and capabilities

How much each model can read, how much it can write, and what it accepts as input.

Metricmeta-llama logoLlama 3.3 70B Instructopenai logoGPT-4o-mini
Context window131K tokens128K tokens
Max output16K tokens16K tokens
Input typesTextFile, Image, Text
Output typesTextText
Reasoning effort levelsNot availableNot available
Default reasoning effortNot availableNot available
Release dateDecember 6, 2024July 18, 2024

Features

Supported features

API features available for each model.

Metricmeta-llama logoLlama 3.3 70B Instructopenai logoGPT-4o-mini
Tool callingSupportedSupported
Structured outputsSupportedSupported
JSON modeSupportedSupported
ReasoningNot supportedNot supported
TemperatureSupportedSupported
Stop sequencesSupportedSupported
Deterministic seedSupportedSupported
Verbosity controlNot supportedNot supported

Our take

GPT-4o-mini is 1.2x cheaper for a typical chat. Llama 3.3 70B Instruct scores higher on the Artificial Analysis Intelligence Index (7.7 vs 6.7). Llama 3.3 70B Instruct has the larger context window (131K vs 128K tokens). The right pick depends on your workload, so the quickest way to settle it is to send the same prompt to both and compare.

FAQ

Frequently asked questions

Is Llama 3.3 70B Instruct or GPT-4o-mini cheaper?

GPT-4o-mini is cheaper for a typical chat (2K input tokens and 500 output tokens). GPT-4o-mini costs $0.15 per 1M input tokens and $0.60 per 1M output tokens, while Llama 3.3 70B Instruct costs $0.22 per 1M input tokens and $0.50 per 1M output tokens.

Which has a bigger context window, Llama 3.3 70B Instruct or GPT-4o-mini?

Llama 3.3 70B Instruct supports up to 131K tokens of context, compared with 128K for GPT-4o-mini.

Is Llama 3.3 70B Instruct smarter than GPT-4o-mini?

On the Artificial Analysis Intelligence Index, Llama 3.3 70B Instruct scores 7.7 and GPT-4o-mini scores 6.7, putting Llama 3.3 70B Instruct ahead. Benchmarks don't capture everything, so the best test is running your own prompts through both.

Can I use Llama 3.3 70B Instruct and GPT-4o-mini at the same time?

Yes. Shortcut Chat sends one prompt to multiple models at once, so you can see Llama 3.3 70B Instruct and GPT-4o-mini answer side by side and keep the better response.

meta-llama logoopenai logo

Why choose? Ask both.

Send one prompt to Llama 3.3 70B Instruct and GPT-4o-mini at the same time. Compare the answers side by side and keep the best one.