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Meta model product

Llama 3.1 70B

1 70B is a large language model optimized for multilingual dialogue use cases.

Updated Sep 8, 2026. Default version: Llama 3.1 70B Instruct

LLMBoard Score11.5Llama 3.1 70B Instruct
Coverage20%16 benchmark families
Context window128KTokens
Official input priceN/AOfficial price unavailable

On this page

  • Capability
  • Benchmarks
  • Arena
  • Pricing
  • Runtime
  • Specification
  • Versions
  • Similar models
  • About
  • FAQ

Llama 3.1 70B Capability Profile

This profile uses the model's current scored version. Arena ratings and prices are shown separately.

Llama 3.1 70B Instruct LLMBoard score breakdown

Llama 3.1 70B Benchmark Results

Benchmark scores for Llama 3.1 70B Instruct.

20 rows
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Benchmark
Score
Rank
Participants
Percentile
Evidence
Evaluated
BenchmarkGSM-8K (CoT)Score95.10%Rank01Participants2Percentile100.00%EvidenceCEvaluatedSep 8, 2026
BenchmarkMATH (CoT)Score68.00%Rank01Participants6Percentile100.00%EvidenceCEvaluatedSep 8, 2026
BenchmarkMBPP ++ base versionScore86.00%Rank01Participants1Percentile100.00%EvidenceCEvaluatedSep 8, 2026
BenchmarkAPI-BankScore90.00%Rank02Participants3Percentile50.00%EvidenceCEvaluatedSep 8, 2026
BenchmarkBFCLScore84.80%Rank02Participants11Percentile90.00%EvidenceCEvaluatedSep 8, 2026
BenchmarkGorilla Benchmark API BenchScore29.70%Rank02Participants3Percentile50.00%EvidenceCEvaluatedSep 8, 2026
BenchmarkMMLU (CoT)Score86.00%Rank02Participants3Percentile50.00%EvidenceCEvaluatedSep 8, 2026
BenchmarkMultilingual MGSM (CoT)Score86.90%Rank02Participants3Percentile50.00%EvidenceCEvaluatedSep 8, 2026
BenchmarkMultipl-E HumanEvalScore65.50%Rank02Participants3Percentile50.00%EvidenceCEvaluatedSep 8, 2026
BenchmarkMultipl-E MBPPScore62.00%Rank02Participants3Percentile50.00%EvidenceCEvaluatedSep 8, 2026
BenchmarkNexusScore56.70%Rank02Participants4Percentile66.67%EvidenceCEvaluatedSep 8, 2026
BenchmarkARC-CScore94.80%Rank04Participants34Percentile90.91%EvidenceCEvaluatedSep 8, 2026
BenchmarkDROPScore79.60%Rank14Participants30Percentile55.17%EvidenceCEvaluatedSep 8, 2026
BenchmarkIFEvalScore87.50%Rank33Participants68Percentile52.24%EvidenceCEvaluatedSep 8, 2026
BenchmarkHumanEvalScore80.50%Rank45Participants66Percentile32.31%EvidenceCEvaluatedSep 8, 2026
BenchmarkMMLUScore83.60%Rank47Participants101Percentile54.00%EvidenceCEvaluatedSep 8, 2026
BenchmarkMMLU-ProScore66.40%Rank106Participants138Percentile23.36%EvidenceCEvaluatedSep 8, 2026
BenchmarkLM Arena TextScore1,260.68 ratingRank184Participants210Percentile12.44%EvidenceAEvaluatedSep 2, 2026
BenchmarkLM Arena Text Style ControlScore1,293.03 ratingRank185Participants210Percentile11.96%EvidenceAEvaluatedSep 2, 2026
BenchmarkGPQAScore41.70%Rank214Participants247Percentile13.41%EvidenceCEvaluatedSep 8, 2026

Llama 3.1 70B Arena Results

Preference and agent-evaluation results for the default version.

30 of 56 rows
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Arena
Category
Rank
Rating / score
Votes
Observations
Result date
ArenatextCategoryfrenchRank159Rating / score1,260.91Votes501ObservationsN/AResult dateSep 2, 2026
ArenatextCategoryjapaneseRank161Rating / score1,132.42Votes1,428ObservationsN/AResult dateSep 2, 2026
ArenatextCategoryspanishRank161Rating / score1,252.30Votes606ObservationsN/AResult dateSep 2, 2026
Arenatext style controlCategoryfrenchRank161Rating / score1,300.23Votes501ObservationsN/AResult dateSep 2, 2026
ArenatextCategorygermanRank163Rating / score1,221.42Votes1,353ObservationsN/AResult dateSep 2, 2026
ArenatextCategorykoreanRank163Rating / score1,140.12Votes873ObservationsN/AResult dateSep 2, 2026
Arenatext style controlCategoryjapaneseRank163Rating / score1,175.02Votes1,428ObservationsN/AResult dateSep 2, 2026
Arenatext style controlCategoryspanishRank163Rating / score1,287.07Votes606ObservationsN/AResult dateSep 2, 2026
Arenatext style controlCategorygermanRank166Rating / score1,255.74Votes1,353ObservationsN/AResult dateSep 2, 2026
Arenatext style controlCategorykoreanRank166Rating / score1,187.09Votes873ObservationsN/AResult dateSep 2, 2026
Arenatext style controlCategoryindustry legal and governmentRank170Rating / score1,328.56Votes3,177ObservationsN/AResult dateSep 2, 2026
ArenatextCategoryindustry legal and governmentRank171Rating / score1,283.50Votes3,177ObservationsN/AResult dateSep 2, 2026
ArenatextCategoryindustry medicine and healthcareRank174Rating / score1,256.48Votes2,821ObservationsN/AResult dateSep 2, 2026
ArenatextCategorymathRank174Rating / score1,251.65Votes7,677ObservationsN/AResult dateSep 2, 2026
ArenatextCategoryindustry life and physical and social scienceRank175Rating / score1,276.01Votes9,381ObservationsN/AResult dateSep 2, 2026
ArenatextCategoryenglishRank177Rating / score1,293.62Votes29,694ObservationsN/AResult dateSep 2, 2026
ArenatextCategoryindustry mathematicalRank177Rating / score1,253.44Votes6,524ObservationsN/AResult dateSep 2, 2026
Arenatext style controlCategoryindustry life and physical and social scienceRank178Rating / score1,318.36Votes9,381ObservationsN/AResult dateSep 2, 2026
Arenatext style controlCategorymathRank178Rating / score1,269.11Votes7,677ObservationsN/AResult dateSep 2, 2026
ArenatextCategoryindustry business and management and financial operationsRank179Rating / score1,234.65Votes6,381ObservationsN/AResult dateSep 2, 2026
Arenatext style controlCategoryindustry mathematicalRank179Rating / score1,275.20Votes6,524ObservationsN/AResult dateSep 2, 2026
Arenatext style controlCategoryindustry medicine and healthcareRank179Rating / score1,312.33Votes2,821ObservationsN/AResult dateSep 2, 2026
Arenatext style controlCategoryenglishRank180Rating / score1,320.93Votes29,694ObservationsN/AResult dateSep 2, 2026
ArenatextCategoryindustry entertainment and sports and mediaRank182Rating / score1,229.71Votes8,719ObservationsN/AResult dateSep 2, 2026
Arenatext style controlCategorycodingRank182Rating / score1,333.23Votes9,389ObservationsN/AResult dateSep 2, 2026
Arenatext style controlCategoryindustry entertainment and sports and mediaRank182Rating / score1,263.31Votes8,719ObservationsN/AResult dateSep 2, 2026
Arenatext style controlCategorymulti turnRank182Rating / score1,288.63Votes10,405ObservationsN/AResult dateSep 2, 2026
ArenatextCategoryexclude tiesRank183Rating / score1,176.39Votes34,840ObservationsN/AResult dateSep 2, 2026
Arenatext style controlCategorychineseRank183Rating / score1,277.40Votes4,846ObservationsN/AResult dateSep 2, 2026
Arenatext style controlCategorycreative writingRank183Rating / score1,256.63Votes8,250ObservationsN/AResult dateSep 2, 2026

Llama 3.1 70B Pricing

Official vendor API pricing appears first, followed by individual provider offers.

Official API
N/A
Official provider
N/A
Lowest third-party
From $0.40 input, $0.40 output per 1M via OpenRouter
Tracked offerings
5
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Provider
Provider model ID
Region
Input / 1M
Output / 1M
Context
Updated
ProviderNvidiaProvider model IDmeta/llama-3.1-70b-instructRegionglobalInput / 1MN/AOutput / 1MN/AContext128KUpdatedSep 8, 2026
ProviderOpenRouterProvider model IDmeta-llama/llama-3.1-70b-instructRegionglobalInput / 1M$0.40Output / 1M$0.40Context131.1KUpdatedSep 8, 2026
ProviderAmazon BedrockProvider model IDmeta.llama3-1-70b-instruct-v1:0RegionglobalInput / 1M$0.72Output / 1M$0.72Context128KUpdatedSep 8, 2026
ProviderVercel AI GatewayProvider model IDmeta/llama-3.1-70bRegionglobalInput / 1M$0.72Output / 1M$0.72Context128KUpdatedSep 8, 2026
ProviderDevPass (LLM Gateway)Provider model IDllama-3.1-70b-instructRegionglobalInput / 1M$0.72Output / 1M$0.72Context128KUpdatedSep 8, 2026

Official prices use only the vendor's configured official Provider and positive standard USD PAYG rates. Third-party offers remain explicitly labeled.

Llama 3.1 70B Runtime Performance

Provider-specific output speed and catalog latency for Llama 3.1 70B Instruct. Runtime does not affect the capability score.

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Provider
Output Speed
Catalog Latency
Max Input
Max Output
Updated
ProviderCerebrasOutput Speed1,204.00 tok/sCatalog Latency0.20 sMax Input128KMax Output128KUpdatedSep 8, 2026
ProviderGroqOutput Speed250.00 tok/sCatalog Latency0.50 sMax Input128KMax Output128KUpdatedSep 8, 2026
ProviderDeepInfraOutput Speed25.00 tok/sCatalog Latency0.50 sMax Input128KMax Output128KUpdatedSep 8, 2026

Output Speed is generated output tokens received per second. Catalog latency is reported separately from observed provider TTFT.

Llama 3.1 70B Specifications

Technical details for the model's default version.

Version
Llama 3.1 70B Instruct
Released
Jul 23, 2024
Knowledge cutoff
Unknown
Parameters
70B
Context window
128K
Max output
128K
Inputs
text
Outputs
text
Open weights
Yes
License
Llama 3.1 Community License

Llama 3.1 70B Versions

Available versions of this model. The score column identifies the version used in the overall ranking.

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Version
Released
LLMBoard
Parameters
Context
Max output
Open weights
License
VersionLlama 3.1 70B InstructReleasedJul 23, 2024LLMBoard11.47Parameters70BContext128KMax output128KOpen weightsYesLicenseLlama 3.1 Community License

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What is Llama 3.1 70B?

Key information about Llama 3.1 70B and its available data.

1 70B Instruct is a large language model from Meta optimized for multilingual dialogue use cases. It outperforms many available open source and closed chat models on common industry benchmarks.

Data as of 2026-09-08.

FAQ

Common questions about Llama 3.1 70B.

When was Llama 3.1 70B released?

Llama 3.1 70B's default version was released on Jul 23, 2024.

How much does Llama 3.1 70B cost?

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.

Who created Llama 3.1 70B?

Llama 3.1 70B was created by Meta.

What is the context window for Llama 3.1 70B?

The default version has a 128K token context window.

Is Llama 3.1 70B open weight?

Yes. The default version is marked as open weight under Llama 3.1 Community License.

How many API providers offer Llama 3.1 70B?

5 provider offerings are linked to the default version.