NVIDIA Llama 3.1 Nemotron 70B vs Llama 3.1 70B: Benchmark Comparison
Detailed comparison of NVIDIA Llama 3.1 Nemotron 70B and Llama 3.1 70B covering benchmarks, pricing, context window, and compliance.
Key Specifications
| Specification | NVIDIA Llama 3.1 Nemotron 70B | Llama 3.1 70B |
|---|---|---|
| Vendor | other | meta |
| Version | nvidia-llama-3-1-nemotron-70b | 3.1-70b |
| Release Date | 2024-10-17 | 2024-07-23 |
| Context Window | 131072 tokens | 128000 tokens |
| Input Modalities | text | text |
| Output Modalities | text | text |
| License | Llama 3.1 Community License | Llama 3 Community License |
| SOC2 | ✗ | ✗ |
| HIPAA | ✗ | ✗ |
| GDPR | ✗ | ✗ |
| ISO 27001 | ✗ | ✗ |
Benchmark Results
| Benchmark | NVIDIA Llama 3.1 Nemotron 70B | Llama 3.1 70B | Winner |
|---|---|---|---|
| ARC | 93.2 | 92.3 | NVIDIA Llama 3.1 Nemotron 70B |
| BBH | 76.6 | 70.2 | NVIDIA Llama 3.1 Nemotron 70B |
| GPQA | 37.6 | 40 | Llama 3.1 70B |
| GSM8K | 77.8 | 78.8 | Llama 3.1 70B |
| HUMANEVAL | 66.4 | 79.7 | Llama 3.1 70B |
| IFEVAL | 69.6 | 73.7 | Llama 3.1 70B |
| MATH | 40.3 | 38.5 | NVIDIA Llama 3.1 Nemotron 70B |
| MMLU | 80.4 | 75.6 | NVIDIA Llama 3.1 Nemotron 70B |
| MUSR | 47.7 | 48.1 | Llama 3.1 70B |
| WINOGRANDE | 84.7 | 81 | NVIDIA Llama 3.1 Nemotron 70B |
Pricing Comparison
| Tier (per Mtok) | NVIDIA Llama 3.1 Nemotron 70B | Llama 3.1 70B |
|---|---|---|
| Input | $0.9 | $0.9 |
| Output | $0.9 | $0.9 |
| Cache Read | $0 | $0 |
| Cache Write | $0 | $0 |
NVIDIA Llama 3.1 Nemotron 70B gegen Llama 3.1 70B
Modellübersicht
NVIDIA Llama 3.1 Nemotron 70B and Llama 3.1 70B are both notable options in the AI model market. This page compares their benchmarks, pricing, and compliance.
Hauptspezifikationen
| Anbieter | Veröffentlichungsdatum | Kontextfenster | Lizenz |
|---|---|---|---|
| Other / Meta | 2024-10-17 / 2024-07-23 | 131K / 128K | Llama 3.1 Community License / Llama 3 Community License |
Benchmark-Leistung
| Benchmark | NVIDIA Llama 3.1 Nemotron 70B | Llama 3.1 70B | Gewinner |
|---|---|---|---|
| ARC | 93.2 | 92.3 | A |
| BBH (BIG-Bench Hard) | 76.6 | 70.2 | A |
| GPQA | 37.6 | 40.0 | B |
| GSM8K (Grade School Math 8K) | 77.8 | 78.8 | B |
| HumanEval | 66.4 | 79.7 | B |
| IFEval | 69.6 | 73.7 | B |
| MATH | 40.3 | 38.5 | A |
| MMLU (Massive Multitask Language Understanding) | 80.4 | 75.6 | A |
| MUSR | 47.7 | 48.1 | Tie |
| WinoGrande | 84.7 | 81.0 | A |
Preisvergleich
| Eingabe | Ausgabe | Cache-Lesen | Cache-Schreiben |
|---|---|---|---|
| — / — | — / — | — / — | — / — |
pro Million Token — A / B
Stärken & Schwächen
NVIDIA Llama 3.1 Nemotron 70B
- ✅ MMLU score 80.4, strong knowledge reasoning.
- ⚠️ 闭源专有模型，不支持自托管。
Llama 3.1 70B
- ✅ 可靠的通用模型。
- ⚠️ 闭源专有模型，不支持自托管。
Redaktionsmeinung
NVIDIA Llama 3.1 Nemotron 70B and Llama 3.1 70B each have their strengths. Choose based on workload (code, long context, vision), referencing the tables above.
FAQ
Which model is better for coding tasks?
Refer to the HumanEval benchmark table; the model with a higher score is better suited for coding tasks.
Which model is cheaper?
Refer to the pricing comparison table above; the model with lower input/output prices is more cost-effective.
Which has a longer context window?
Refer to the key specifications table; the model with a larger context window is better for long documents.
Referenzen
Editor's Take
See Editor's Take section.