nvidia · Open weights
Nvidia Nemotron 70b
Nvidia's latest Llama fine-tune optimized for instruction following. Early results hints that it might outperform models such as GPT-4o and Claude 3.5 Sonnet.
- Input
- Text
- Output
- Text
- Discovery tier
- Open weights
Pricing
USD per 1M tokens- Input
- $0.36
- Output
- $0.41
Reference prices as published by the model provider. API example
Specifications
- Context window
- 16.4K
- Max output
- 8.2K
Side by side
Nvidia Nemotron 70b compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| Nvidia Nemotron 70bnvidiaThis model | Nvidia Nemotron 3 Ultra 550BnvidiaRemove | |
|---|---|---|
| Provider | nvidia | nvidia |
| Discovery tier | Open weights | Open weights |
| Added | Apr 15, 2025 | Jun 4, 2026 |
| Limits | ||
| Context window | 16.38K | 1MBest |
| Max output | 8.19K | 65.54KBest |
| Average output | — | 56 tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.36Best | $0.50 |
| Output | $0.41Best | $2.50 |
| Performance | ||
| Throughput | — | 107.6 tok/s |
| Time to first token | — | 1.2 s |
| Request success (24h) | 22.9% | 100.0%Best |
| Benchmark indexes | ||
| Intelligence Index | 6.9 | 22.9Best |
| Coding Index | — | 49.3 |
| Math Index | 11.0 | — |
| Capabilities | ||
| Reasoning | No | Yes |
| Tools | No | Yes |
| Parallel tools | No | Yes |
| Reasoning effort | — | — |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- Nvidia Nemotron 70b
- Nvidia Nemotron 3 Ultra 550B
Intelligence Index
- Nvidia Nemotron 70b6.9
- Nvidia Nemotron 3 Ultra 550B22.9
Nvidia Nemotron 70b: Better than 8% of 326 scored models
Indexes
Coding Index
Composite of the coding evaluations
- Nvidia Nemotron 70b: —
- Nvidia Nemotron 3 Ultra 550B: 49.3
Math Index
Composite of the math evaluations
- Nvidia Nemotron 70b: 11.0
- Nvidia Nemotron 3 Ultra 550B: —
Agentic work
AutomationBench-AA
Workflow automation, penalized for guardrail violations
- Nvidia Nemotron 70b: —
- Nvidia Nemotron 3 Ultra 550B: 3.0%
AutomationBench-AA tasks completed
Workflows finished end to end without a guardrail violation
- Nvidia Nemotron 70b: —
- Nvidia Nemotron 3 Ultra 550B: 0.3%
AA-Briefcasev1.1
Agentic knowledge work, rated head to head
- Nvidia Nemotron 70b: —
- Nvidia Nemotron 3 Ultra 550B: 876 Elo
GDPval-AAv2.1
Economically valuable occupational tasks, rated head to head
- Nvidia Nemotron 70b: —
- Nvidia Nemotron 3 Ultra 550B: 1,013 Elo
Document reasoning
GDP.pdf
Professional reasoning over PDF documents, all-pass rate
- Nvidia Nemotron 70b: —
- Nvidia Nemotron 3 Ultra 550B: 5.0%
AA-LCRv1.1
Reasoning across long documents
- Nvidia Nemotron 70b: 8.3%
- Nvidia Nemotron 3 Ultra 550B: 79.3%Top
MLCR-AA
Long-context reasoning over medical records
- Nvidia Nemotron 70b: —
- Nvidia Nemotron 3 Ultra 550B: 5.6%
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- Nvidia Nemotron 70b: 4.2%
- Nvidia Nemotron 3 Ultra 550B: 28.4%Top
GPQA Diamond
Graduate-level science questions
- Nvidia Nemotron 70b: 46.5%
- Nvidia Nemotron 3 Ultra 550B: 86.7%Top
MMLU-Pro
Multi-subject knowledge and reasoning
- Nvidia Nemotron 70b: 69.0%
- Nvidia Nemotron 3 Ultra 550B: —
IFBench
Following precise output instructions
- Nvidia Nemotron 70b: 30.7%
- Nvidia Nemotron 3 Ultra 550B: 81.4%Top
Coding
Terminal-Benchv4.0
Practical software engineering in a terminal
- Nvidia Nemotron 70b: —
- Nvidia Nemotron 3 Ultra 550B: 0.5%
SciCode
Scientific computing in Python
- Nvidia Nemotron 70b: —
- Nvidia Nemotron 3 Ultra 550B: 40.3%
LiveCodeBench
Recent competitive programming problems
- Nvidia Nemotron 70b: 16.9%
- Nvidia Nemotron 3 Ultra 550B: —
Math
AIME 2025
Competition mathematics, 2025 problems
- Nvidia Nemotron 70b: 11.0%
- Nvidia Nemotron 3 Ultra 550B: —
AIME
Competition mathematics
- Nvidia Nemotron 70b: 24.7%
- Nvidia Nemotron 3 Ultra 550B: —
MATH-500
Competition math problems
- Nvidia Nemotron 70b: 73.3%
- Nvidia Nemotron 3 Ultra 550B: —
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- Nvidia Nemotron 70b: 4.5%
- Nvidia Nemotron 3 Ultra 550B: 36.4%Top
τ²-Bench Telecom
Tool use in a customer-support simulation
- Nvidia Nemotron 70b: 23.1%
- Nvidia Nemotron 3 Ultra 550B: 83.3%Top
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- Nvidia Nemotron 70b: 8.3%
- Nvidia Nemotron 3 Ultra 550B: 79.3%Top
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.
- Request success (24h)
- 22.9%
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": "nvidia/Llama-3.1-Nemotron-70B-Instruct-HF",
"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="nvidia/Llama-3.1-Nemotron-70B-Instruct-HF",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)nvidia
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