Meta · Open weights
Llama 3.1 70B Celeste v0.1
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.
| Llama 3.1 70B Celeste v0.1MetaThis model | Muse Glimmer 30BMetaRemove | |
|---|---|---|
| Provider | Meta | Meta |
| Discovery tier | Open weights | Open weights |
| Added | Jan 1, 2024 | Aug 11, 2026 |
| Limits | ||
| Context window | 32.77K | 131.07KBest |
| Average output | — | 682 tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.49 | $0.35Best |
| Output | $0.49Best | $1.50 |
| Cache read | — | $0.04 |
| Performance | ||
| Throughput | — | 70.8 tok/s |
| Time to first token | — | 1.1 s |
| Request success (24h) | — | 100.0% |
| Benchmark indexes | ||
| Intelligence Index | — | 17.5 |
| Coding Index | — | 49.0 |
| Capabilities | ||
| Reasoning | No | Yes |
| Tools | No | Yes |
| Vision | No | Yes |
| Structured output | No | Yes |
| 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 Glimmer 30B
Intelligence Index
- Llama 3.1 70B Celeste v0.1—
- Muse Glimmer 30B17.5
Indexes
Coding Index
Composite of the coding evaluations
- Llama 3.1 70B Celeste v0.1: —
- Muse Glimmer 30B: 49.0
Agentic work
AutomationBench-AA
Workflow automation, penalized for guardrail violations
- Llama 3.1 70B Celeste v0.1: —
- Muse Glimmer 30B: 6.8%
AutomationBench-AA tasks completed
Workflows finished end to end without a guardrail violation
- Llama 3.1 70B Celeste v0.1: —
- Muse Glimmer 30B: 0.8%
AA-Briefcasev1.1
Agentic knowledge work, rated head to head
- Llama 3.1 70B Celeste v0.1: —
- Muse Glimmer 30B: 477 Elo
GDPval-AAv2.1
Economically valuable occupational tasks, rated head to head
- Llama 3.1 70B Celeste v0.1: —
- Muse Glimmer 30B: 783 Elo
Document reasoning
GDP.pdf
Professional reasoning over PDF documents, all-pass rate
- Llama 3.1 70B Celeste v0.1: —
- Muse Glimmer 30B: 10.0%
AA-LCRv1.1
Reasoning across long documents
- Llama 3.1 70B Celeste v0.1: —
- Muse Glimmer 30B: 83.3%
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- Llama 3.1 70B Celeste v0.1: —
- Muse Glimmer 30B: 22.0%
GPQA Diamond
Graduate-level science questions
- Llama 3.1 70B Celeste v0.1: —
- Muse Glimmer 30B: 83.5%
Coding
Terminal-Benchv4.0
Practical software engineering in a terminal
- Llama 3.1 70B Celeste v0.1: —
- Muse Glimmer 30B: 0.5%
SciCode
Scientific computing in Python
- Llama 3.1 70B Celeste v0.1: —
- Muse Glimmer 30B: 44.9%
Legacy evaluations
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- Llama 3.1 70B Celeste v0.1: —
- Muse Glimmer 30B: 83.3%
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.
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
Related models
Other Meta models, starting with the same family.