per 1M tokens
Llama 4 Maverick Instruct
novita/meta-llama/llama-4-maverick-17b-128e-instruct-fp8
Llama 4 Maverick 17B Instruct (128E) is a high-capacity multimodal language model from Meta, built on a mixture-of-experts (MoE) architecture with 128 experts and 17 billion active parameters per forward pass (400B total). It supports multilingual text and image input, and produces multilingual text and code output across 12 supported languages. Optimized for vision-language tasks, Maverick is instruction-tuned for assistant-like behavior, image reasoning, and general-purpose multimodal interaction. Maverick features early fusion for native multimodality and a 1 million token context window. It was trained on a curated mixture of public, licensed, and Meta-platform data, covering ~22 trillion tokens, with a knowledge cutoff in August 2024. Released on April 5, 2025 under the Llama 4 Community License, Maverick is suited for research and commercial applications requiring advanced multimodal understanding and high model throughput.
Price
per 1M tokens
Providers
Each row is one seller. Prices are the published rate from that source. A dash means that source did not publish the amount. Sorted by a 3:1 blend of input and output.
| Provider | Tag | Quant | Input | Output | Context | Uptime | Status | Source |
|---|---|---|---|---|---|---|---|---|
| Novita | — | — | $0.27/1M | $0.85/1M | 1.0M | — | Listed | novita |
Monthly bill
Token models use the token counts. Image, video, and audio models use units times the flat rate.
$1.12 at list price for this workload
Every rate
| Unit | Input | Output | Flat | Confidence |
|---|---|---|---|---|
| token | $0.27/1M | $0.85/1M | Not published— | official |
Price history
input or flat output
Daily snapshots
| UTC date | Unit | Input | Output | Flat |
|---|---|---|---|---|
| 2026-10-08 | token | $0.27 | $0.85 | Not published— |
| 2026-10-09 | token | $0.27 | $0.85 | Not published— |
| 2026-10-10 | token | $0.27 | $0.85 | Not published— |
| 2026-10-11 | token | $0.27 | $0.85 | Not published— |
| 2026-10-12 | token | $0.27 | $0.85 | Not published— |
| 2026-10-13 | token | $0.27 | $0.85 | Not published— |
| 2026-10-14 | token | $0.27 | $0.85 | Not published— |
| 2026-10-15 | token | $0.27 | $0.85 | Not published— |
| 2026-10-16 | token | $0.27 | $0.85 | Not published— |
| 2026-10-17 | token | $0.27 | $0.85 | Not published— |
| 2026-10-18 | token | $0.27 | $0.85 | Not published— |
| 2026-10-19 | token | $0.27 | $0.85 | Not published— |
| 2026-10-20 | token | $0.27 | $0.85 | Not published— |
| 2026-10-21 | token | $0.27 | $0.85 | Not published— |
| 2026-10-22 | token | $0.27 | $0.85 | Not published— |
| 2026-10-23 | token | $0.27 | $0.85 | Not published— |
| 2026-10-24 | token | $0.27 | $0.85 | Not published— |
| 2026-10-25 | token | $0.27 | $0.85 | Not published— |
| 2026-10-26 | token | $0.27 | $0.85 | Not published— |
| 2026-10-27 | token | $0.27 | $0.85 | Not published— |
| 2026-10-28 | token | $0.27 | $0.85 | Not published— |
| 2026-10-29 | token | $0.27 | $0.85 | Not published— |
| 2026-10-30 | token | $0.27 | $0.85 | Not published— |
Alternatives
- @cf/meta/llama-4-scout-17b-16e-instruct$0.27/1M · Compare
- DeepSeek: DeepSeek V3.1 Terminus$0.27/1M · Compare
- DeepSeek: DeepSeek V3.2 Exp$0.27/1M · Compare
- google/gemma-4-31B-it-Ultra$0.27/1M · Compare
- minimax-m25$0.27/1M · Compare
- Qwen3.5 27B$0.27/1M · Compare
Call this model
OpenRouter id novita/meta-llama/llama-4-maverick-17b-128e-instruct-fp8. InferenceList does not send the request.
curl
curl https://openrouter.ai/api/v1/chat/completions \
-H "Authorization: Bearer $OPENROUTER_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"novita/meta-llama/llama-4-maverick-17b-128e-instruct-fp8","messages":[{"role":"user","content":"Hello"}]}'
JavaScript
await fetch("https://openrouter.ai/api/v1/chat/completions", {
method: "POST",
headers: {
Authorization: "Bearer " + process.env.OPENROUTER_API_KEY,
"Content-Type": "application/json",
},
body: JSON.stringify({
model: "novita/meta-llama/llama-4-maverick-17b-128e-instruct-fp8",
messages: [{ role: "user", content: "Hello" }],
}),
});
Python
import os, json, urllib.request
req = urllib.request.Request(
"https://openrouter.ai/api/v1/chat/completions",
data=json.dumps({"model": "novita/meta-llama/llama-4-maverick-17b-128e-instruct-fp8", "messages": [{"role": "user", "content": "Hello"}]}).encode(),
headers={"Authorization": "Bearer " + os.environ["OPENROUTER_API_KEY"], "Content-Type": "application/json"},
)
print(urllib.request.urlopen(req).read().decode())