Can I run GPT-3.5 Turbo or Llama V3p1 Nemotron 70b cheaper on another provider?

Some models are available on inference providers like Together AI, Groq, and Fireworks AI at lower prices. Check each model's pricing page for the full provider comparison.

What is the context window difference between GPT-3.5 Turbo and Llama V3p1 Nemotron 70b?

Llama V3p1 Nemotron 70b has a larger context window at 131K tokens vs 16K. This matters for long documents, large codebases, and extended conversation histories.

Compare

GPT-3.5 Turbo vs Llama V3p1 Nemotron 70b

Pricing is only the shared seller matrix below. Best rates and catalog map are separate sections, so no chart is embedded in pricing. Open the calculator for the same workload on each side.

OpenAI

Model

GPT-3.5 Turbo

Tool calling

Best $0.500 in · $1.50 out

Context window 16K

Pricing

Llama V3p1 Nemotron 70b

Best $0.900 in · $0.900 out

Context window 131K

Pricing

GPT-3.5 Turbo is 44% cheaper on input. Llama V3p1 Nemotron 70b is 40% cheaper on output. The best choice depends on your input/output ratio.

Estimate cost

Pricing matrix

Shared sellers only. Each row is a host that lists both models. Dollar amounts are per 1M tokens. Lowest in each pair of columns is emphasized.

Provider	GPT-3.5 Turbo in	GPT-3.5 Turbo out	Llama V3p1 Nemotron 70b in	Llama V3p1 Nemotron 70b out
Azure	$0.500	$1.50	N/A	N/A
Fireworks AI	N/A	N/A	$0.900	$0.900
Github Copilot	N/A	N/A	N/A	N/A
OpenAI	$0.500	$1.50	N/A	N/A
Openrouter	$1.50	$2.00	N/A	N/A
Text Completion Openai	$1.50	$2.00	N/A	N/A
Vercel Ai Gateway	$0.500	$1.50	N/A	N/A

Best listed rates (this pair)

Same "best row in current pricing" logic as model pages: a compact view of the lowest input and output we show for each side. This is not the seller matrix.

Catalog map · OpenAI · Meta

Each chart uses real catalog rows that include both list input and list output ($/1M). Larger green dots are the models on this comparison page; accent dots are other active models from that provider.

OpenAI · input vs output

Scatter chart: X = input $/M, Y = output $/M. This page's models are labeled on the green dots; hover others for detail.

ListedoutputUSD/1M

One dot per catalog row that has both list prices. Green dots are labeled with the models on this page; hover any dot for name and prices. Upper-right means higher cost on both axes ($/1M).

Meta · input vs output

ListedoutputUSD/1M

One dot per catalog row that has both list prices. Green dots are labeled with the models on this page; hover any dot for name and prices. Upper-right means higher cost on both axes ($/1M).

Specifications

Each column header is the full model name. Tint marks the favorable value where we compute a winner.

Spec

GPT-3.5 Turbo

Llama V3p1 Nemotron 70b

Context window: 16,385 tokens; 131,072 tokens
Max output tokens: 4,096 tokens; 131,072 tokens
Vision: No; No
Function calling: Yes; No
Streaming: No; No
Release date: May 2023; N/A

Cost calculator

Same requests, input tokens, and output tokens for both columns. Pick the provider row that matches how you buy.

GPT-3.5 Turbo

Llama V3p1 Nemotron 70b

Requests / day

Input tokens

Output tokens

GPT-3.5 Turbo

Monthly

$375

Annual

$4.6K

Llama V3p1 Nemotron 70b

Monthly

$405

Annual

$4.9K

Save $30/month with GPT-3.5 Turbo

When to pick which

Short takeaways: no cards, just the points. Validate with your own workloads.

Long-context tasks
Use Llama V3p1 Nemotron 70b. Its 131K context window handles large codebases and documents better than 16K.
High-volume text generation
Use Llama V3p1 Nemotron 70b. Output tokens are 40% cheaper, which compounds significantly at scale.
Long output (reports, code files)
Use Llama V3p1 Nemotron 70b. Its 131K max output limit reduces the need to split requests.

Frequently asked questions

GPT-3.5 Turbo is cheaper on input tokens, while Llama V3p1 Nemotron 70b is cheaper on output. The best choice depends on your input/output ratio.

More comparisons

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