Can I run Llama 3.1 70B or Phi 4 Mini Reasoning 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 Llama 3.1 70B and Phi 4 Mini Reasoning?

Phi 4 Mini Reasoning has a larger context window at 131K tokens vs 128K. This matters for long documents, large codebases, and extended conversation histories.

Compare

Llama 3.1 70B vs Phi 4 Mini Reasoning

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.

MetaLlama 3.1

Model

Llama 3.1 70B

Tool calling

Best $0.400 in · $0.400 out

Context window 128K

Pricing

Microsoft

Model

Phi 4 Mini Reasoning

Tool calling

Best $0.080 in · $0.320 out

Context window 131K

Pricing

Phi 4 Mini Reasoning is cheaper across the board — 80% cheaper on input and 20% cheaper on output.

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	Llama 3.1 70B in	Llama 3.1 70B out	Phi 4 Mini Reasoning in	Phi 4 Mini Reasoning out
Azure	N/A	N/A	$0.080	$0.320
DeepInfra	$0.520	$0.750	N/A	N/A
Fireworks AI	$0.900	$0.900	N/A	N/A
Groq	$0.590	$0.790	N/A	N/A
Openrouter	$0.400	$0.400	N/A	N/A
Perplexity	$1.00	$1.00	N/A	N/A
Together AI	$0.880	$0.880	N/A	N/A
Vercel Ai Gateway	$0.720	$0.720	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 · Meta · Microsoft

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.

Meta · 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).

Microsoft · 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

Llama 3.1 70B

Phi 4 Mini Reasoning

Context window: 128,000 tokens; 131,072 tokens
Max output tokens: 4,096 tokens; 4,096 tokens
Vision: No; No
Function calling: Yes; Yes
Streaming: Yes; No
Release date: Jul 2024; N/A

Cost calculator

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

Llama 3.1 70B

Phi 4 Mini Reasoning

Requests / day

Input tokens

Output tokens

Llama 3.1 70B

Monthly

$324

Annual

$3.9K

Phi 4 Mini Reasoning

Monthly

$72

Annual

$876

Save $252/month with Phi 4 Mini Reasoning

When to pick which

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

Long-context tasks
Use Phi 4 Mini Reasoning. Its 131K context window handles large codebases and documents better than 128K.
High-volume text generation
Use Phi 4 Mini Reasoning. Output tokens are 20% cheaper, which compounds significantly at scale.

Frequently asked questions

Phi 4 Mini Reasoning is cheaper on both input and output tokens.

More comparisons

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