Meta model product
1 70B Instruct is a large language model optimized for multilingual dialogue use cases.
Updated Aug 17, 2026. Default version: Llama 3.1 70B Instruct
This profile uses the model's current scored version. Arena ratings and prices are shown separately.
Benchmark scores for Llama 3.1 70B Instruct.
Benchmark | Score | Rank | Participants | Percentile | Evidence | Evaluated |
|---|
| BenchmarkGSM-8K (CoT) | Score95.1% | Rank01 | Participants2 | Percentile100.0% | EvidenceC | Evaluated |
| BenchmarkMATH (CoT) | Score68.0% | Rank01 | Participants6 | Percentile100.0% | EvidenceC | Evaluated |
| BenchmarkMBPP ++ base version | Score86.0% | Rank01 | Participants1 | Percentile100.0% | EvidenceC | Evaluated |
| BenchmarkAPI-Bank | Score90.0% | Rank02 | Participants3 | Percentile50.0% | EvidenceC | Evaluated |
| BenchmarkBFCL | Score84.8% | Rank02 | Participants11 | Percentile90.0% | EvidenceC | Evaluated |
| BenchmarkGorilla Benchmark API Bench | Score29.7% | Rank02 | Participants3 | Percentile50.0% | EvidenceC | Evaluated |
| BenchmarkMMLU (CoT) | Score86.0% | Rank02 | Participants3 | Percentile50.0% | EvidenceC | Evaluated |
| BenchmarkMultilingual MGSM (CoT) | Score86.9% | Rank02 | Participants3 | Percentile50.0% | EvidenceC | Evaluated |
| BenchmarkMultipl-E HumanEval | Score65.5% | Rank02 | Participants3 | Percentile50.0% | EvidenceC | Evaluated |
| BenchmarkMultipl-E MBPP | Score62.0% | Rank02 | Participants3 | Percentile50.0% | EvidenceC | Evaluated |
| BenchmarkNexus | Score56.7% | Rank02 | Participants4 | Percentile66.7% | EvidenceC | Evaluated |
| BenchmarkARC-C | Score94.8% | Rank04 | Participants34 | Percentile90.9% | EvidenceC | Evaluated |
| BenchmarkDROP | Score79.6% | Rank14 | Participants30 | Percentile55.2% | EvidenceC | Evaluated |
| BenchmarkIFEval | Score87.5% | Rank32 | Participants67 | Percentile53.0% | EvidenceC | Evaluated |
| BenchmarkHumanEval | Score80.5% | Rank45 | Participants66 | Percentile32.3% | EvidenceC | Evaluated |
| BenchmarkMMLU | Score83.6% | Rank47 | Participants101 | Percentile54.0% | EvidenceC | Evaluated |
| BenchmarkMMLU-Pro | Score66.4% | Rank102 | Participants134 | Percentile24.1% | EvidenceC | Evaluated |
| BenchmarkGPQA | Score41.7% | Rank206 | Participants239 | Percentile13.9% | EvidenceC | Evaluated |
Preference and agent-evaluation results for the default version.
Arena | Category | Rank | Rating / score | Votes | Observations | Result date |
|---|
| Arenatext | Categoryoverall | Rank263 | Rating / score1261.0 | Votes55,240 | ObservationsN/A | Result date |
| Arenatext style control | Categoryoverall | Rank264 | Rating / score1293.3 | Votes55,240 | ObservationsN/A | Result date |
Official vendor API pricing appears first, followed by individual provider offers.
Provider | Provider model ID | Region | Input / 1M | Output / 1M | Context | Updated |
|---|
| ProviderNvidia | Provider model IDmeta/llama-3.1-70b-instruct | Regionglobal | Input / 1MN/A | Output / 1MN/A | Context128K | Updated |
| ProviderOpenRouter | Provider model IDmeta-llama/llama-3.1-70b-instruct | Regionglobal | Input / 1M$0.40 | Output / 1M$0.40 | Context131.1K | Updated |
| ProviderAmazon Bedrock | Provider model IDmeta.llama3-1-70b-instruct-v1:0 | Regionglobal | Input / 1M$0.72 | Output / 1M$0.72 | Context128K | Updated |
| ProviderVercel AI Gateway | Provider model IDmeta/llama-3.1-70b | Regionglobal | Input / 1M$0.72 | Output / 1M$0.72 | Context128K | Updated |
| ProviderLLM Gateway | Provider model IDllama-3.1-70b-instruct | Regionglobal | Input / 1M$0.72 | Output / 1M$0.72 | Context128K | Updated |
Official prices use only the vendor's configured official Provider and positive standard USD PAYG rates. Third-party offers remain explicitly labeled.
Provider-specific output speed and catalog latency for Llama 3.1 70B Instruct. Runtime does not affect the capability score.
Provider | Output Speed | Catalog Latency | Max Input | Max Output | Updated |
|---|
| ProviderCerebras | Output Speed1,204 tok/s | Catalog Latency0.2 s | Max Input128K | Max Output128K | Updated |
| ProviderGroq | Output Speed250 tok/s | Catalog Latency0.5 s | Max Input128K | Max Output128K | Updated |
| ProviderHyperbolic | Output Speed100 tok/s | Catalog Latency0.5 s | Max Input128K | Max Output128K | Updated |
| ProviderBedrock | Output Speed100 tok/s | Catalog Latency0.5 s | Max Input128K | Max Output128K | Updated |
| ProviderTogether | Output Speed94 tok/s | Catalog Latency0.5 s | Max Input128K | Max Output128K | Updated |
| ProviderSambanova | Output Speed74 tok/s | Catalog Latency0.5 s | Max Input128K | Max Output128K | Updated |
| ProviderLambda | Output Speed42 tok/s | Catalog Latency0.5 s | Max Input128K | Max Output128K | Updated |
| ProviderFireworks | Output Speed32 tok/s | Catalog Latency0.5 s | Max Input128K | Max Output128K | Updated |
| ProviderDeepInfra | Output Speed25 tok/s | Catalog Latency0.5 s | Max Input128K | Max Output128K | Updated |
Output Speed is generated output tokens received per second. Catalog latency is reported separately from observed provider TTFT.
Technical details for the model's default version.
Available versions of this model. The score column identifies the version used in the overall ranking.
Version | Released | LLMBoard | Parameters | Context | Max output | Open weights | License |
|---|
| VersionLlama 3.1 70B Instruct | Released | LLMBoard12.6 | Parameters70B | Context128K | Max output128K | Open weightsNo | LicenseLlama 3.1 Community License |
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 LLMBoard score.
Key information about Llama 3.1 70B and its available data.
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.
Data as of 2026-08-17.
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 was created by Meta.
The default version has a 128K token context window.
No. The default version is not marked as having publicly available weights.
5 provider offerings are linked to the default version.
Nearby ranked alternatives include Llama 4 Scout, Phi 4 Mini Reasoning, Nova Lite.