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Meta · Open weights

Llama 3.1 70B Celeste v0.1

Added Jan 1, 2024Open weights

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Use in the app

Creative model based on Llama 3.1 70B

Input
Text
Output
Text
Discovery tier
Open weights

Pricing

USD per 1M tokens
Input
$0.49
Output
$0.49

Reference prices as published by the model provider. API example

Specifications

Context window
32.8K
Max output
—

Side by side

Llama 3.1 70B Celeste v0.1 compared

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

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Llama 3.1 70B Celeste v0.1MetaThis modelMuse Spark 1.2MetaRemove
ProviderMetaMeta
Discovery tierOpen weightsFrontier
AddedJan 1, 2024Aug 5, 2026
Limits
Context window32.77K1MBest
Max output—65.54K
Average output—172 tokens
Pricing, USD per 1M tokens
Input$0.49Best$1.25
Output$0.49Best$4.25
Cache read—$0.15
Benchmark indexes
Intelligence Index—39.6
Coding Index—72.2
Capabilities
ReasoningNoYes
ToolsNoYes
VisionNoYes
Structured outputNoYes
PDF inputNoYes
Audio inputNoYes
Video inputNoYes
Parallel toolsNoYes
Reasoning effort—minimal, low, medium, high, xhigh

Public evaluations

Benchmarks

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

  • Llama 3.1 70B Celeste v0.1
  • Muse Spark 1.2

Intelligence Index

  • Llama 3.1 70B Celeste v0.1—
  • Muse Spark 1.239.6
3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • Llama 3.1 70B Celeste v0.1: —
    • Muse Spark 1.2: 72.2

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • Llama 3.1 70B Celeste v0.1: —
    • Muse Spark 1.2: 40.6%

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • Llama 3.1 70B Celeste v0.1: —
    • Muse Spark 1.2: 15.7%

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • Llama 3.1 70B Celeste v0.1: —
    • Muse Spark 1.2: 1,327 Elo

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • Llama 3.1 70B Celeste v0.1: —
    • Muse Spark 1.2: 1,475 Elo

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • Llama 3.1 70B Celeste v0.1: —
    • Muse Spark 1.2: 17.4%

  • AA-LCRv1.1

    Reasoning across long documents

    • Llama 3.1 70B Celeste v0.1: —
    • Muse Spark 1.2: 79.0%

  • MLCR-AA

    Long-context reasoning over medical records

    • Llama 3.1 70B Celeste v0.1: —
    • Muse Spark 1.2: 7.2%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Llama 3.1 70B Celeste v0.1: —
    • Muse Spark 1.2: 45.5%

  • GPQA Diamond

    Graduate-level science questions

    • Llama 3.1 70B Celeste v0.1: —
    • Muse Spark 1.2: 90.4%

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • Llama 3.1 70B Celeste v0.1: —
    • Muse Spark 1.2: 7.1%

  • SciCode

    Scientific computing in Python

    • Llama 3.1 70B Celeste v0.1: —
    • Muse Spark 1.2: 57.4%

Legacy evaluations

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Llama 3.1 70B Celeste v0.1: —
    • Muse Spark 1.2: 79.0%

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

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": "nothingiisreal/L3.1-70B-Celeste-V0.1-BF16",
    "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="nothingiisreal/L3.1-70B-Celeste-V0.1-BF16",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Meta

Other Meta models, starting with the same family.