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Meta · Open weights

Anubis 70B v1.1

Added Jan 1, 2024Open weights

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Use in the app

L3.3 finetune for roleplaying – updated v1.1 with improved reasoning.

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
32K
Max output
16.4K
Average output (7 days)
225 tokens
Longer than 24% of 465 models

Side by side

Anubis 70B v1.1 compared

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

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Anubis 70B v1.1MetaThis modelMuse Spark OpenMetaRemove
ProviderMetaMeta
Discovery tierOpen weightsFrontier
AddedJan 1, 2024Oct 15, 2026
Limits
Context window32K1.05MBest
Max output16.38K—
Average output225 tokens1.3K tokens
Pricing, USD per 1M tokens
Input$0.31Best$1.25
Output$0.31Best$4.25
Cache read—$0.15
Performance
Throughput48.3 tok/s—
Time to first token2.4 s—
Request success (24h)33.0%—
Benchmark indexes
Intelligence Index—38.9
Capabilities
ReasoningNoYes
ToolsNoYes
VisionNoYes
Structured outputNoYes
Reasoning effort—low, medium, high, xhigh

Public evaluations

Benchmarks

Independent evaluation results, with how each score ranks among the models in the Noumen catalog.

  • Anubis 70B v1.1
  • Muse Spark Open

Intelligence Index

  • Anubis 70B v1.1—
  • Muse Spark Open38.9
3.8Catalog models by score55.1

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • Anubis 70B v1.1: —
    • Muse Spark Open: 49.7%

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • Anubis 70B v1.1: —
    • Muse Spark Open: 20.9%

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • Anubis 70B v1.1: —
    • Muse Spark Open: 1,279 Elo

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • Anubis 70B v1.1: —
    • Muse Spark Open: 1,401 Elo

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • Anubis 70B v1.1: —
    • Muse Spark Open: 18.6%

  • AA-LCRv1.1

    Reasoning across long documents

    • Anubis 70B v1.1: —
    • Muse Spark Open: 78.3%

  • MLCR-AA

    Long-context reasoning over medical records

    • Anubis 70B v1.1: —
    • Muse Spark Open: 7.8%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Anubis 70B v1.1: —
    • Muse Spark Open: 43.9%

  • GPQA Diamond

    Graduate-level science questions

    • Anubis 70B v1.1: —
    • Muse Spark Open: 89.0%

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • Anubis 70B v1.1: —
    • Muse Spark Open: 8.1%

  • SciCode

    Scientific computing in Python

    • Anubis 70B v1.1: —
    • Muse Spark Open: 58.4%

Legacy evaluations

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Anubis 70B v1.1: —
    • Muse Spark Open: 78.3%

Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis

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.

Throughput
48.3 tok/s
Faster than 35% of 247 models
Time to first token
2.4 s
Quicker than 67% of 247 models
Prompt cache hits
0.0%
Request success (24h)
33.0%

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-v1.1",
    "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-v1.1",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Meta

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