Meta Models API Cost Calculator & Comparison

Every Meta model, side by side — current API rates, context window, benchmarks, and a live calculator that ranks them at your exact workload. 14 active models, 14 with public pricing. Prices refreshed daily.

Models tracked

14

Active

14

With public pricing

14

Cheapest input

$0.00/1M

Calculate your Meta API cost at your workload.

Set your workload — every priced model ranks in real time.

Adjust the workload

Every model below updates in real time.

1,00010,00050,000250,0001M10M

Ranked by your monthly bill

No models with public pricing available to compare right now.

Pricing at a glance

Blended $/1M tokens across the lineup.

Blended price uses a 3-to-1 input/output ratio. Green bar = cheapest.

Quick picks

Best Meta model for your use case.

As of April 2026, Meta offers 14 active models via API, ranging from $0/1M to $0.51/1M input tokens. The most context-rich model handles up to 1M tokens. Models support vision, tool use. All prices are USD per 1 million tokens.

Lowest cost

Llama 3.3 70B Instruct

$0/1M input

Largest context

Llama 4 Maverick

1.0M tokens

Vision / multimodal

Llama Guard 4 12B

Image input

Tool use / agents

Llama 4 Scout

Function calling

Quality vs price

Meta benchmarks at a glance.

Each point is one model — X is blended $/1M tokens, Y is the average of available quality benchmarks. Larger bubbles mean larger context windows.

Per-model benchmark scores

ModelAvgScores
Llama 3.1 70B Instruct73.0
MMLU86MMLU Pro66.4GPQA Diamond48HumanEval80.5MATH68IFEval87.5Chatbot Arena Elo1248
Llama 3.2 11B Vision Instruct73.0
MMLU73
Llama 3 70B Instruct68.3
MMLU82HumanEval81.7IFEval81.0BBH50.2MMLU Pro46.7
Llama 3.3 70B Instruct68.2
MMLU86MMLU Pro68.9GPQA Diamond50.5HumanEval88.4MATH77IFEval92.1Chatbot Arena Elo1256BBH56.6SciPredict18.2
Llama 4 Scout65.3
MMLU79.6GPQA Diamond57.2HumanEval74.1MATH50.3
Llama 3.3 70B Instruct64.8
MMLU86MMLU Pro68.9GPQA Diamond50.5HumanEval88.4MATH77SciPredict18.2
Llama 4 Maverick58.2
MMLU85.5GPQA Diamond69.8HumanEval82.4MATH61.2LiveCodeBench43.4AA Intelligence Index18Chatbot Arena Elo1417Humanity's Last Exam5.7
Llama 3.2 3B Instruct55.7
MMLU63.4MATH48
Llama 3.1 8B Instruct54.2
MMLU73MMLU Pro48.3GPQA Diamond30.4HumanEval72.6MATH51.9IFEval80.4Chatbot Arena Elo1175SciPredict14.7
Llama 3 8B Instruct52.1
MMLU66.6HumanEval62.2IFEval74.1BBH28.2MMLU Pro29.6
Llama 3.2 3B Instruct45.0
MMLU63.4GPQA Diamond32.8MATH48IFEval77.4BBH24.1MMLU Pro24.4
Llama 3.2 1B Instruct31.1
MMLU49.3MATH30.6IFEval59.5BBH8.7MMLU Pro7.6

Open weights

Open Models from Meta

Meta ships 14 open-source or open-weights models you can self-host or fine-tune. Each links to its Hugging Face card.

Every model

Every Meta model — pricing, context & capabilities.

ModelContextInput /1MOutput /1M
Llama Guard 4 12B164K$0.18$0.18
Llama 4 Maverick1.0M$0.15$0.6
Llama 4 Scout328K$0.08$0.3
Llama 3.3 70B Instruct131K$0.12$0.38
Llama 3.3 70B Instruct66K$0.0$0.0
Llama 3.2 11B Vision Instruct131K$0.245$0.245
Llama 3.2 1B Instruct60K$0.027$0.2
Llama 3.2 3B Instruct80K$0.051$0.34
Llama 3.2 3B Instruct131K$0.0$0.0
Llama Guard 3 8B131K$0.48$0.03
Llama 3.1 70B Instruct131K$0.4$0.4
Llama 3.1 8B Instruct16K$0.02$0.05
Llama 3 70B Instruct8K$0.51$0.74
Llama 3 8B Instruct8K$0.03$0.04

FAQ

Domande frequenti

Pricing patterns, best-known use cases, and how this provider stacks up.

Get instant answers from our AI agent

Meta API pricing ranges from $0 to $0.51 per 1M input tokens. Output tokens cost more than input on every model. Prices are per 1 million tokens (1M ≈ 750,000 words). Use the calculator above to estimate your monthly spend at your actual workload.
Llama 3.3 70B Instruct is the lowest-priced Meta model with public pricing at $0/1M input tokens. It suits high-volume tasks where cost matters most — classification, extraction, summarization, and similar workloads that don't need frontier reasoning.
Llama 3 70B Instruct is Meta's highest-tier model at $0.51/1M input. It delivers the most sophisticated reasoning, instruction-following, and nuance. For workloads that don't require frontier performance, a mid-tier model typically cuts inference costs substantially.
Llama Guard 4 12B, Llama 4 Maverick, Llama 4 Scout and 11 more support function calling (tool use), required for agentic workflows. Agents need a model that reliably follows structured output schemas — test with your specific tool definitions before committing to production volumes.
Yes — Llama Guard 4 12B, Llama 4 Maverick, Llama 4 Scout, Llama 3.2 11B Vision Instruct accept image input alongside text. You can pass screenshots, photos, charts, and documents for analysis. Vision adds no separate line-item on most Meta models — you're billed for the token equivalent of the image.
Yes — Meta supports prompt caching (discounts for repeated context) and batch processing (accept a delay, cut costs ~50%). These rates appear in the table above under "Cached /1M" and "Batch /1M." Caching pays off quickly if your prompts share a long system prompt or document prefix across many calls.
Meta has historically adjusted prices when launching new model generations, often cutting rates to stay competitive. Buzzi.ai snapshots pricing daily — you can subscribe to price-drop alerts on any Meta model using the "Alert me" button on its detail page.
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