per 1M tokens
Llama 4 Scout Instruct
novita/meta-llama/llama-4-scout-17b-16e-instruct
Llama 4 Scout 17B Instruct (16E) is a mixture-of-experts (MoE) language model developed by Meta, activating 17 billion parameters out of a total of 109B. It supports native multimodal input (text and image) and multilingual output (text and code) across 12 supported languages. Designed for assistant-style interaction and visual reasoning, Scout uses 16 experts per forward pass and features a context length of 10 million tokens, with a training corpus of ~40 trillion tokens. Built for high efficiency and local or commercial deployment, Llama 4 Scout incorporates early fusion for seamless modality integration. It is instruction-tuned for use in multilingual chat, captioning, and image understanding tasks. Released under the Llama 4 Community License, it was last trained on data up to August 2024 and launched publicly on April 5, 2025.
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 | — | — | $0.18/1M | $0.59/1M | 131K | — | Listed | novita |
Monthly bill
Token models use the token counts. Image, video, and audio models use units times the flat rate.
$0.77 at list price for this workload
Every rate
| Unit | Input | Output | Flat | Confidence |
|---|---|---|---|---|
| token | $0.18/1M | $0.59/1M | Not published— | official |
Price history
input or flat output
Daily snapshots
| UTC date | Unit | Input | Output | Flat |
|---|---|---|---|---|
| 2026-10-08 | token | $0.18 | $0.59 | Not published— |
| 2026-10-09 | token | $0.18 | $0.59 | Not published— |
| 2026-10-10 | token | $0.18 | $0.59 | Not published— |
| 2026-10-11 | token | $0.18 | $0.59 | Not published— |
| 2026-10-12 | token | $0.18 | $0.59 | Not published— |
| 2026-10-13 | token | $0.18 | $0.59 | Not published— |
| 2026-10-14 | token | $0.18 | $0.59 | Not published— |
| 2026-10-15 | token | $0.18 | $0.59 | Not published— |
| 2026-10-16 | token | $0.18 | $0.59 | Not published— |
| 2026-10-17 | token | $0.18 | $0.59 | Not published— |
| 2026-10-18 | token | $0.18 | $0.59 | Not published— |
| 2026-10-19 | token | $0.18 | $0.59 | Not published— |
| 2026-10-20 | token | $0.18 | $0.59 | Not published— |
| 2026-10-21 | token | $0.18 | $0.59 | Not published— |
| 2026-10-22 | token | $0.18 | $0.59 | Not published— |
| 2026-10-23 | token | $0.18 | $0.59 | Not published— |
| 2026-10-24 | token | $0.18 | $0.59 | Not published— |
| 2026-10-25 | token | $0.18 | $0.59 | Not published— |
| 2026-10-26 | token | $0.18 | $0.59 | Not published— |
| 2026-10-27 | token | $0.18 | $0.59 | Not published— |
| 2026-10-28 | token | $0.18 | $0.59 | Not published— |
| 2026-10-29 | token | $0.18 | $0.59 | Not published— |
| 2026-10-30 | token | $0.18 | $0.59 | Not published— |
Alternatives
- DeepSeek R1 Distill Qwen 1.5B$0.18/1M · Compare
- Llama 4 Scout Instruct (17Bx16E)$0.18/1M · Compare
- Meta Llama 3.1 8B Instruct Turbo$0.18/1M · Compare
- meta-llama/Llama-Guard-4-12B$0.18/1M · Compare
- Meta: Llama Guard 4 12B$0.18/1M · Compare
- Qwen3-VL-8B-Instruct$0.18/1M · Compare
Call this model
OpenRouter id novita/meta-llama/llama-4-scout-17b-16e-instruct. 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-scout-17b-16e-instruct","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-scout-17b-16e-instruct",
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-scout-17b-16e-instruct", "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())