Meta · Open weights

Anubis 70B v1

Added Jan 1, 2024Open weights

Use in the app

L3.3 finetune for roleplaying.

Input: Text
Output: Text
Discovery tier: Open weights

Pricing

USD per 1M tokens

Input: $0.31
Output: $0.31

Reference prices as published by the model provider. API example

Specifications

Context window: 65.5K
Max output: 16.4K
Average output (7 days): 423 tokens; Longer than 43% of 465 models

Side by side

Anubis 70B v1 compared

Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.

Limits
	Anubis 70B v1MetaThis model	Anubis 70B v1.1MetaRemove
Provider	Meta	Meta
Discovery tier	Open weights	Open weights
Added	Jan 1, 2024	Jan 1, 2024
Context window	65.54KBest	32K
Max output	16.38K	16.38K
Average output	423 tokens	225 tokens
Pricing, USD per 1M tokens
Input	$0.31	$0.31
Output	$0.31	$0.31
Performance
Throughput	—	48.3 tok/s
Time to first token	—	2.4 s
Request success (24h)	21.4%	33.0%Best
Capabilities
Reasoning effort	—	—

Public evaluations

Benchmarks

There are no public benchmark results for these models yet.

Live routing data

Performance and reliability

Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.

Prompt cache hits: 0.0%
Request success (24h): 21.4%

Cache hits are the share of input tokens recently served from a prompt cache across all requests. They are not a forecast of your own hit rate.

Developers

Use it through the API

Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.

Read the quickstart

curl https://www.noumen.xyz/api/v1/chat/completions \
  -H "Authorization: Bearer $NOUMEN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "TheDrummer/Anubis-70B-v1",
    "messages": [{ "role": "user", "content": "Explain this stack trace." }]
  }'

import os
from openai import OpenAI

client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
    model="TheDrummer/Anubis-70B-v1",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)