Llama 4 MaverickAPI Pricing

Llama 4 API Pricing: Open-Source Costs and Hosting Options

Meta's Llama 4 is open-weight and free to download, but running it still costs money. Here's what you'll pay for hosted API access versus self-hosting, and how LLMWise fits in.

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Credit-based pay-per-use with token-settled billing. No monthly subscription. Paid credits never expire.

Replace multiple AI subscriptions with one wallet that includes routing, failover, and optimization.

First success in 60 seconds

Step 01Sign up in 10 secondsGet 20 free credits Step 02Open your dashboardCreate API key Step 03Send first requestRun a sample

Why teams start here first

No monthly subscription

Pay-as-you-go credits

Start with trial credits, then buy only what you consume.

Failover safety

Production-ready routing

Auto fallback across providers when latency, quality, or reliability changes.

Data control

Your policy, your choice

BYOK and zero-retention mode keep training and storage scope explicit.

Single API experience

One key, multi-provider access

Use Chat/Compare/Blend/Judge/Failover from one dashboard.

Meta API pricing (reference)

Kept as reference for model evaluation. LLMWise pricing shown below uses credit reserves plus token-settled billing.

Tier	Input / 1M tokens	Output / 1M tokens	Context	Note
Llama 4 Maverick	$0.20	$0.60	256K tokens	Meta's flagship open model. Mixture-of-experts architecture with strong multilingual and coding performance. Available on most inference providers.
Llama 4 Scout	$0.08	$0.30	256K tokens	Lightweight model optimized for speed and cost. Excellent for edge deployment, classification, and high-throughput workloads.
Llama 4 Behemoth	$3.50	$10.00	256K tokens	Largest Llama model (2T parameters). Rivals GPT-5.2 and Opus 4.6 on reasoning benchmarks. Only available via select providers due to compute requirements.

User-facing pricing uses credit reserves + token settlement

Evidence snapshot

Llama 4 Maverick pricing analysis

Current Llama 4 Maverick billing context: compare providers, then run the same workload on LLMWise for request-based credits.

LLMWise usage

Reserve by mode: Chat 1, Compare 2, Blend 4, Judge 5, Failover 1

minimum reserve credits by mode

Pricing tiers

provider options for this model family

LLMWise scenario cost

Similar token cost through LLMWise, but you skip the hosting-provider lock-in. If Together AI has issues, requests route to Fireworks or Groq automatically.

Internal knowledge base with 15K queries/month (avg 1,200 input + 500 output tokens). Long context from document retrieval.

Savings result

At 15K queries/month, API access beats self-hosting by 1,000x. The real value of LLMWise here is provider-agnostic access to Llama without tying yourself to one inference host.

based on workload mix and routing auto-mode

Usage starts-to-finish

Example: Product support workload

If your team sends 20 support messages a day in Chat mode, the minimum reserve is around 600 credits each month (starts at 1 reserve credit/request). Final usage settles by model and token volume.

Workflow

20 req/day

Chat mode / starts at 1 reserve credit

Monthly estimate

~600+ credits

reserve floor before settlement

What you get

Predictable

same behavior, single model switch

Try this scenario in your dashboard

Why people use LLMWise

API key setup

Single LLMWise key - access Llama 4 alongside GPT-5.2, Claude, Gemini, and more

See Meta comparison

Choose a hosting provider (Together AI, Fireworks, Groq), create account, generate key

Billing model

Consistent credit-based pricing - same model, same cost, regardless of backend provider

See Meta comparison

Varies by provider - per-token, per-second, or reserved GPU billing

Failover

Automatic failover across providers and models - Llama to GPT-5.2 to Claude

See Meta comparison

Tied to one inference provider - if it goes down, you switch manually

Model switching

Unified API + SDKs (OpenAI-style messages) - switch from Llama to any model in one parameter

See Meta comparison

Different providers have different APIs, SDKs, and response formats

Rate limits

Pooled capacity across multiple inference backends - higher effective throughput

See Meta comparison

Provider-dependent, often lower for open models than proprietary APIs

Free tier

20 free trial credits on signup - benchmark Llama against proprietary models instantly

See Meta comparison

Some providers offer limited free tiers (Groq, Together AI)

Cost example

Internal knowledge base with 15K queries/month (avg 1,200 input + 500 output tokens). Long context from document retrieval.

LLMWise total

Similar token cost through LLMWise, but you skip the hosting-provider lock-in. If Together AI has issues, requests route to Fireworks or Groq automatically.

You save

At 15K queries/month, API access beats self-hosting by 1,000x. The real value of LLMWise here is provider-agnostic access to Llama without tying yourself to one inference host.

Optional: reference direct API cost

$8.10/mo with Llama 4 Maverick via Together AI ($3.60 input + $4.50 output). Self-hosting the same volume: ~$8,700/mo for 4x A100s - breakeven at ~16B tokens/month.

Llama 4 Maverick delivers excellent quality at open-source pricing, making it one of the best values in the API market. The challenge is choosing among hosting providers and managing reliability. LLMWise simplifies this by routing Llama requests through the fastest available backend and automatically falling back to proprietary models during outages. For teams that want open-source economics with closed-source reliability, LLMWise is the bridge.

Common questions

How much does Llama 4 API access cost?

Llama 4 Maverick costs approximately $0.20 per million input tokens and $0.60 per million output tokens through managed API providers. Scout is even cheaper at $0.08/$0.30. Prices vary slightly between hosting providers like Together AI, Fireworks, and Groq.

Is Llama 4 free to use?

Llama 4 weights are free to download under Meta's open license, so self-hosting on your own GPUs has no licensing cost. However, you still pay for compute - a single Maverick instance requires 4x A100 GPUs (~$12/hour on cloud providers). Managed API access is far more cost-effective for most teams.

How does Llama 4 Maverick compare to GPT-5.2 on price?

Llama 4 Maverick ($0.20/$0.60 per 1M tokens) is about 15x cheaper than GPT-5.2 ($3.00/$12.00) on input and 20x cheaper on output. Quality is within 5-10% on most benchmarks, making Maverick an excellent choice for cost-sensitive applications where top-tier accuracy isn't critical.

Should I self-host Llama 4 or use an API?

For most teams, managed API access is more cost-effective unless you're processing millions of tokens daily. Self-hosting Llama 4 Maverick requires approximately $8,700/month in GPU costs (4x A100s), which only breaks even at around 30 billion tokens per month. Below that volume, API access is cheaper.

One wallet, enterprise AI controls built in

Credit-based pay-per-use with token-settled billing. No monthly subscription. Paid credits never expire.

Replace multiple AI subscriptions with one wallet that includes routing, failover, and optimization.

Chat, Compare, Blend, Judge, MeshPolicy routing + replay labFailover without extra subscriptions

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