Meta model product
Llama 3.1 70B Instruct is a large language model optimized for multilingual dialogue use cases. It outperforms many available open source and closed chat models on common industry benchmarks.
Updated Aug 10, 2026. Default version: Llama 3.1 70B Instruct
Structured fields from the published default version.
This profile uses the latest version under this unique model that has a calculated LLMBoard score. Arena and price are excluded.
Published benchmark records for the scored version Llama 3.1 70B Instruct.
| GSM-8K (CoT) | 1.0 | 1 | 2 | 100.0% | C | |
| MATH (CoT) | 0.7 | 1 | 6 | 100.0% | C | |
| MBPP ++ base version | 0.9 | 1 | 1 | 100.0% | C | |
| API-Bank | 0.9 | 2 | 3 | 50.0% | C | |
| BFCL | 0.8 | 2 | 11 | 90.0% | C | |
| Gorilla Benchmark API Bench | 0.3 | 2 | 3 | 50.0% | C | |
| MMLU (CoT) | 0.9 | 2 | 3 | 50.0% | C | |
| Multilingual MGSM (CoT) | 0.9 | 2 | 3 | 50.0% | C | |
| Multipl-E HumanEval | 0.7 | 2 | 3 | 50.0% | C | |
| Multipl-E MBPP | 0.6 | 2 | 3 | 50.0% | C | |
| Nexus | 0.6 | 2 | 4 | 66.7% | C | |
| ARC-C | 0.9 | 4 | 34 | 90.9% | C | |
| DROP | 0.8 | 14 | 30 | 55.2% | C | |
| IFEval | 0.9 | 32 | 65 | 51.6% | C | |
| MMLU | 0.8 | 47 | 100 | 53.5% | C | |
| HumanEval | 0.8 | 50 | 76 | 34.7% | C | |
| MMLU-Pro | 0.7 | 98 | 129 | 24.2% | C | |
| GPQA | 0.4 | 200 | 233 | 14.2% | C |
Preference and agent-evaluation signals from published Arena datasets.
| text | french | 209 | 1259.9 | 501 | N/A | |
| text | japanese | 210 | 1132.8 | 1,428 | N/A | |
| text | spanish | 211 | 1252.3 | 606 | N/A | |
| text style control | french | 212 | 1299.7 | 501 | N/A | |
| text style control | japanese | 214 | 1175.4 | 1,428 | N/A | |
| text style control | spanish | 218 | 1285.3 | 606 | N/A | |
| text | korean | 222 | 1140.6 | 873 | N/A | |
| text | german | 223 | 1221.5 | 1,353 | N/A | |
| text style control | korean | 228 | 1187.2 | 873 | N/A | |
| text style control | german | 229 | 1255.8 | 1,353 | N/A | |
| text | industry legal and government | 232 | 1283.6 | 3,177 | N/A | |
| text style control | industry legal and government | 234 | 1328.3 | 3,177 | N/A | |
| text | industry medicine and healthcare | 239 | 1256.4 | 2,821 | N/A | |
| text | english | 243 | 1293.8 | 29,694 | N/A | |
| text | industry life and physical and social science | 243 | 1276.4 | 9,381 | N/A | |
| text | math | 247 | 1251.7 | 7,677 | N/A | |
| text style control | industry medicine and healthcare | 248 | 1311.7 | 2,821 | N/A | |
| text | industry mathematical | 249 | 1253.5 | 6,524 | N/A | |
| text | industry business and management and financial operations | 250 | 1234.8 | 6,381 | N/A | |
| text style control | industry mathematical | 251 | 1275.2 | 6,524 | N/A | |
| text | expert | 252 | 1207.9 | 2,924 | N/A | |
| text style control | expert | 252 | 1272.8 | 2,924 | N/A | |
| text style control | industry entertainment and sports and media | 252 | 1263.9 | 8,719 | N/A | |
| text style control | industry life and physical and social science | 252 | 1318.5 | 9,381 | N/A | |
| text | industry entertainment and sports and media | 253 | 1230.4 | 8,719 | N/A | |
| text style control | multi turn | 254 | 1288.4 | 10,405 | N/A | |
| text | multi turn | 255 | 1256.2 | 10,405 | N/A | |
| text style control | coding | 255 | 1333.1 | 9,389 | N/A | |
| text | hard prompts english | 256 | 1263.1 | 9,133 | N/A | |
| text style control | english | 256 | 1320.9 | 29,694 | N/A | |
| text style control | math | 256 | 1269.1 | 7,677 | N/A | |
| text | exclude ties | 257 | 1177.2 | 34,840 | N/A | |
| text | russian | 257 | 1232.8 | 7,285 | N/A | |
| text style control | industry business and management and financial operations | 257 | 1287.0 | 6,381 | N/A | |
| text | coding | 258 | 1260.2 | 9,389 | N/A | |
| text | overall | 259 | 1261.1 | 55,240 | N/A | |
| text style control | longer query | 259 | 1294.0 | 7,622 | N/A | |
| text style control | russian | 259 | 1269.6 | 7,285 | N/A | |
| text | creative writing | 260 | 1232.2 | 8,250 | N/A | |
| text | industry software and it services | 260 | 1260.9 | 14,811 | N/A | |
| text style control | overall | 260 | 1293.3 | 55,240 | N/A | |
| text style control | exclude ties | 260 | 1222.3 | 34,840 | N/A | |
| text | hard prompts | 261 | 1241.6 | 14,981 | N/A | |
| text | instruction following | 262 | 1231.6 | 21,910 | N/A | |
| text | longer query | 262 | 1241.2 | 7,622 | N/A | |
| text style control | creative writing | 262 | 1257.1 | 8,250 | N/A | |
| text style control | hard prompts english | 262 | 1314.7 | 9,133 | N/A | |
| text style control | instruction following | 262 | 1272.3 | 21,910 | N/A | |
| text | chinese | 264 | 1214.3 | 4,846 | N/A | |
| text | non english | 264 | 1219.0 | 25,546 | N/A | |
| text style control | hard prompts | 264 | 1298.3 | 14,981 | N/A | |
| text style control | industry software and it services | 264 | 1319.0 | 14,811 | N/A | |
| text | industry writing and literature and language | 265 | 1235.7 | 14,962 | N/A | |
| text style control | chinese | 266 | 1276.5 | 4,846 | N/A | |
| text style control | non english | 271 | 1256.9 | 25,546 | N/A | |
| text style control | industry writing and literature and language | 272 | 1263.2 | 14,962 | N/A |
Official vendor API PAYG pricing is summarized first. The table then lists individual provider offerings without treating their minimum as the official price.
| Nvidia | meta/llama-3.1-70b-instruct | global | N/A | N/A | 128K | |
| OpenRouter | meta-llama/llama-3.1-70b-instruct | global | $0.40 | $0.40 | 131.1K | |
| LLM Gateway | llama-3.1-70b-instruct | global | $0.72 | $0.72 | 128K | |
| Amazon Bedrock | meta.llama3-1-70b-instruct-v1:0 | global | $0.72 | $0.72 | 128K | |
| Vercel AI Gateway | meta/llama-3.1-70b | global | $0.72 | $0.72 | 128K |
Official prices use only the vendor's configured official Provider and positive standard USD PAYG rates. Third-party offers remain explicitly labeled.
All published versions linked to this unique model. The score columns identify the version used by the current overall ranking.
| Llama 3.1 70B Instruct | 52.4 | 70B | 128K | 128K | No | Llama 3.1 Community License |
A concise description based on the published model registry.
Llama 3.1 70B Instruct is a large language model optimized for multilingual dialogue use cases. It outperforms many available open source and closed chat models on common industry benchmarks.
Use the benchmark, Arena and pricing sections above as separate evidence. A missing field means the current data snapshot does not support that claim.
Data snapshot: 2026-08-07. Editorial model content is not available in the backend.
Open a comparison with the three ranked models immediately above and below this model.
Recommendations prioritize the same model type and family, then the closest published LLMBoard score.
Common questions about Llama 3.1 70B.
Llama 3.1 70B's default version was released on Jul 23, 2024.
No official standard PAYG price is currently available for Llama 3.1 70B. The lowest tracked third-party offer starts at $0.40 input and $0.40 output via OpenRouter.
Llama 3.1 70B is published under Meta in the model registry.
The default version has a 128K token context window.
No. The default version is not marked as having publicly available weights.
5 published provider offerings are linked to the default version.
Nearby ranked alternatives include Sarvam 105B, LongCat Flash Chat, Gemini 2.0 Flash Lite.