Models

llama-4-maverick vs llama-4-scout

Output tokens cost $0.20 per million on llama-4-maverick and $0.20 per million on llama-4-scout. Input tokens cost $0.20 per million on llama-4-maverick and $0.20 per million on llama-4-scout. Cached input tokens are billed at $0.20 per million on llama-4-maverick and $0.20 per million on llama-4-scout. Context lengths are 1,048,576 tokens on llama-4-maverick and 131,000 tokens on llama-4-scout. Time to first token (TTFT) measured on AIHubMix is 0.2s on llama-4-maverick and 0.3s on llama-4-scout. Measured output throughput is 97.8 tok/s on llama-4-maverick and 2637.0 tok/s on llama-4-scout. On the LMArena coding leaderboard llama-4-maverick scores 1373 and llama-4-scout scores 1362.

Llamallama-4-maverickLlamallama-4-scout
Llama logo
llama-4-maverick
Llama · text, image → text

Llama 4 Maverick is a high-capacity Mixture-of-Experts (MoE) model from Meta, featuring 400B total parameters and 128 experts, while activating an efficient 17B parameters per inference. Engineered for peak performance, it excels at advanced multimodal tasks. Maverick natively supports text and image input, producing multilingual text and code. With a 1-million-token context window and instruction tuning, it is optimized for complex image reasoning and general-purpose assistant-like interactions. Released under the Llama 4 Community License, Maverick is ideal for research and commercial applications demanding state-of-the-art multimodal understanding and high throughput.

Input$0.20 /M
Output$0.20 /M
Llama logo
llama-4-scout
Llama · text, image → text

Llama 4 Scout is a highly efficient Mixture-of-Experts (MoE) model from Meta, activating 17B out of 109B total parameters per inference. It natively supports multimodal input (text and image) and multilingual output (text and code) across 12 languages. Designed for assistant-style interaction and visual reasoning, Scout features a massive 10-million-token context window. It is instruction-tuned for tasks like multilingual chat and image understanding and is released under the Llama 4 Community License for local or commercial deployment.

Input$0.20 /M
Output$0.20 /M

Pricing & Specifications

Prices are per million tokens. Time to First Token and throughput are rolling averages measured on AIHubMix.

llama-4-maverick
llama-4-scout
Input /M
$0.20
$0.20
Output /M
$0.20
$0.20
Cache read /M
$0.20
$0.20
Context length
1,048,576
131,000
Max output
32,000
131,000
Time to First Token
0.2 s
0.3 s
Throughput
97.8 tok/s
2637.0 tok/s
Modalities
textimage
textimage
Supported Parameters
toolsfunction callingstructured outputs
toolsfunction callingstructured outputs
API Formats

Promotional prices show the discounted rate; see each model page for promotion windows.

Activity Past 30 Days

Daily traffic served through AIHubMix — how demand for each model is trending.

llama-4-maverickllama-4-scout

Tokens / day

-

Requests / day

-

Performance Past 3 Days

Measured on real AIHubMix traffic, hourly buckets. Gaps mean no traffic in that hour.

llama-4-maverickllama-4-scout

Throughput (tok/s)

-

TTFT (s)

-

Uptime (%)

-

LMArena Benchmarks

LMArena ratings by capability (Bradley-Terry, commonly called Elo). Higher is better.

Text
llama-4-maverickllama-4-scout
1260130013401380
Overall
13231327
Coding
13621373
Math
13091319
Hard prompts
13301338
Instruction following
13001314
Multi-turn
13201324
Creative writing
12901307
Longer query
13271334
Chinese
13151330
English
13401341
Vision
llama-4-maverickllama-4-scout
11001120114011601180
Overall
11281147
OCR
11291152
Diagram
11471151
Homework
11491161

Source: LMArena (arena.ai) leaderboard, imported by AIHubMix. Models without published ratings are omitted per chart.

Cost calculator

Estimate your monthly bill for the same workload on each model.

llama-4-maverick
$15.00 /mo
llama-4-scout
$15.00 /mo

Monthly = daily × 30. Discounted rates applied where a promotion is active.

FAQ

Which is cheaper: llama-4-maverick, llama-4-scout?

llama-4-maverick: $0.20/M output tokens; llama-4-scout: $0.20/M. Use the cost calculator above to estimate your own workload.

How do their coding arena scores compare?

llama-4-maverick: 1373; llama-4-scout: 1362 (LMArena coding leaderboard).

Which responds faster?

llama-4-maverick: 0.2s time to first token measured on AIHubMix; see the live performance charts above for how each model behaves across the day.

How large is each context window?

llama-4-maverick accepts 1,048,576 and llama-4-scout accepts 131,000 input tokens. Maximum output per request is 32,000 tokens on llama-4-maverick and 131,000 tokens on llama-4-scout.

Which one generates tokens faster?

llama-4-scout at 2637.0 tok/s and llama-4-maverick at 97.8 tok/s, measured as output throughput on AIHubMix — a separate metric from time to first token.

What inputs and capabilities does each model support?

llama-4-maverick accepts text and image input and supports tool calling, function calling and structured outputs; llama-4-scout accepts text and image input and supports tool calling, function calling and structured outputs.

Can I call llama-4-maverick and llama-4-scout with the same API key?

Yes. AIHubMix serves every model on this page behind one OpenAI-compatible endpoint, so switching between them is a one-line change to the model field — no second account, key or SDK.

Popular comparisons

Related model match-ups readers also look at.