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gpt-5-nano vs llama-3.3-70b-versatile — cost comparison

OpenAI gpt-5-nano vs Groq llama-3.3-70b-versatile — list pricing, worked examples, interactive calculator. Verified 2026-05-15.

TL;DR. gpt-5-nano is cheaper on both input (5.9×) and output (2.0×).

Headline pricing

	gpt-5-nano	llama-3.3-70b-versatile
Input / 1M tokens	$0.10	$0.59
Output / 1M tokens	$0.40	$0.79
Cache write / 1M tokens	—	—
Cache read / 1M tokens	—	—

Sources: OpenAI, Groq. Verified 2026-05-15. Re-verify before relying on these numbers for budget commits.

Worked examples (per call, list pricing)

Workload shape	gpt-5-nano	llama-3.3-70b-versatile	Cheaper
1k in + 500 out (tool call)	$0.000300	$0.000985	gpt-5-nano (3.3× cheaper)
10k in + 1k out (RAG)	$0.0014	$0.0067	gpt-5-nano (4.8× cheaper)
100k in + 1k out (long doc)	$0.0104	$0.0598	gpt-5-nano (5.7× cheaper)
2k in + 4k out (long gen)	$0.0018	$0.0043	gpt-5-nano (2.4× cheaper)

Interactive calculator

Calls per month

Prompt tokens / call

Completion tokens / call

(reserved)

How to choose between gpt-5-nano and llama-3.3-70b-versatile

Quality first. Cost only matters if both models clear your quality bar. Run a 30-call eval on real prompts before committing to the cheaper option. If quality is unequal, the price difference is a distraction.
Match price to call shape. gpt-5-nano costs $0.10 in / $0.40 out. llama-3.3-70b-versatile costs $0.59 in / $0.79 out. Workloads that are completion-heavy weigh output prices more.
Latency may matter more than dollars. Some providers are 5-10× faster at the same price tier. If you're below a few thousand calls/day, latency UX usually beats price.

Track what you're actually spending on each

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Related comparisons

OpenAI full pricing · Groq full pricing · All-provider comparison

About this page. Built and maintained by an autonomous AI agent under KS Elevated Solutions LLC. Pricing data comes from each provider's published pricing page, verified 2026-05-15; the same table is bundled in the tokenmark npm package. No fabricated reviews, ratings, or social proof. See full AI disclosure.