Llama 4 Maverick

multimodal

The Llama 4 Maverick is a versatile model in the next generation of the Llama 4 family, released in April 2025. Unlike the more compact Scout, the Maverick is designed for those who need to maximize performance and processing power. The model uses MoE architecture with 128 experts, which has 400 billion parameters in total - making it one of the largest scale open source models on the market. However, only 17 billion parameters are active at each step, significantly reducing inference latency and resource requirements. Like all models in the Maverik series, Maverik supports native multimodality, making it easy to input and process images together with image support text.

With its large-scale architecture, Maverick offers consistency and depth of reasoning, accuracy and security of responses. The model performs respectably on complex logical reasoning, math, and programming tasks, outperforming previous generations of LLMs and major competitors on several key metrics.

The model incorporates advanced security features such as Llama Guard 4 (12B) to filter unsafe content and Llama Prompt Guard 2 (22M and 86M) to protect against manipulative or malicious input.

Llama 4 Maverick is ideal for complex enterprise solutions and large-scale projects where deep insight and precise execution are required.


Announce Date: 05.04.2025
Parameters: 402B
Experts: 128
Activated at inference: 17B
Context: 1M
Layers: 48, using full attention: 12
Attention Type: Chunked Attention
VRAM requirements: 268.9 GB using 4 bits quantization
Developer: Meta AI
Transformers Version: 4.51.0
License: LLAMA 4

Public endpoint

Use our pre-built public endpoints for free to test inference and explore Llama 4 Maverick capabilities. You can obtain an API access token on the token management page after registration and verification.
Model Name Context Type GPU TPS Status Link
There are no public endpoints for this model yet.

Private server

Rent your own physically dedicated instance with hourly or long-term monthly billing.

We recommend deploying private instances in the following scenarios:

  • maximize endpoint performance,
  • enable full context for long sequences,
  • ensure top-tier security for data processing in an isolated, dedicated environment,
  • use custom weights, such as fine-tuned models or LoRA adapters.

Recommended configurations for hosting Llama 4 Maverick

Prices:
Name vCPU RAM, MB Disk, GB GPU Price, hour
teslaa100-4.16.256.480
250,000.0
tensor
16 262144 480 4 $9.17 Launch
h200-2.24.256.320
250,000.0
tensor
24 262144 320 2 $9.42 Launch
teslaa100-4.32.384.320.nvlink
1,048,576.0
tensor
32 393216 320 4 $9.50 Launch
h200-3.32.512.480
1,048,576.0
pipeline
32 524288 480 3 $14.36 Launch
teslah100-4.16.256.480
250,000.0
tensor
16 262144 480 4 $14.99 Launch
teslah100-4.44.512.320
1,048,576.0
tensor
44 524288 320 4 $15.65 Launch
h200-4.32.768.480
1,048,576.0
tensor
32 786432 480 4 $19.23 Launch
Prices:
Name vCPU RAM, MB Disk, GB GPU Price, hour
teslaa100-6.44.512.480.nvlink
250,000.0
pipeline
44 524288 480 6 $14.10 Launch
teslaa100-8.44.512.480.nvlink
1,048,576.0
tensor
44 524288 480 8 $18.35 Launch
h200-4.32.768.480
1,048,576.0
tensor
32 786432 480 4 $19.23 Launch
Prices:
Name vCPU RAM, MB Disk, GB GPU Price, hour
teslaa10-1.16.32.160
250,000.0
16 32768 160 1 $0.53 Launch
teslat4-2.16.32.160
250,000.0
tensor
16 32768 160 2 $0.54 Launch
teslaa2-2.16.32.160
250,000.0
tensor
16 32768 160 2 $0.57 Launch
rtx2080ti-2.12.64.160
250,000.0
tensor
12 65536 160 2 $0.69 Launch
rtx3090-1.16.24.160
250,000.0
16 24576 160 1 $0.88 Launch
rtx4090-1.16.32.160
250,000.0
16 32768 160 1 $1.15 Launch
teslav100-1.12.64.160
250,000.0
12 65536 160 1 $1.20 Launch
rtxa5000-2.16.64.160.nvlink
250,000.0
tensor
16 65536 160 2 $1.23 Launch
teslaa10-3.16.96.160
1,048,576.0
pipeline
16 98304 160 3 $1.34 Launch
rtx3080-3.16.64.160
250,000.0
pipeline
16 65536 160 3 $1.43 Launch
rtx5090-1.16.64.160
250,000.0
16 65536 160 1 $1.59 Launch
teslaa10-4.16.64.160
1,048,576.0
tensor
16 65536 160 4 $1.62 Launch
teslaa2-6.32.128.160
1,048,576.0
pipeline
32 131072 160 6 $1.65 Launch
rtx3080-4.16.64.160
250,000.0
tensor
16 65536 160 4 $1.82 Launch
teslav100-2.16.64.240
1,048,576.0
tensor
16 65535 240 2 $2.22 Launch
rtxa5000-4.16.128.160.nvlink
1,048,576.0
tensor
16 131072 160 4 $2.34 Launch
teslaa100-1.16.64.160
1,048,576.0
16 65536 160 1 $2.37 Launch
rtx3090-3.16.96.160
1,048,576.0
pipeline
16 98304 160 3 $2.45 Launch
rtx5090-2.16.64.160
1,048,576.0
tensor
16 65536 160 2 $2.93 Launch
rtx3090-4.16.64.160
1,048,576.0
tensor
16 65536 160 4 $3.10 Launch
rtx4090-3.16.96.160
1,048,576.0
pipeline
16 98304 160 3 $3.23 Launch
teslah100-1.16.64.160
1,048,576.0
16 65536 160 1 $3.83 Launch
rtx4090-4.16.64.160
1,048,576.0
tensor
16 65536 160 4 $4.14 Launch
h200-1.16.128.160
1,048,576.0
16 131072 160 1 $4.74 Launch

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