LLM Reference

Llama 3 70B

Released
2024-04-18
Last refreshed
2026-07-09
Status
Researched 253d ago
Open weightsCommercial use: conditionalCodingClassification

Llama 3 70B is worth evaluating for coding and classification when its provider route and context window match the workload.

Use it for

  • Teams evaluating coding and classification
  • Workloads that can use a 8k context window
  • Buyers comparing 1 tracked provider route

Do not use it for

  • Vision or document-understanding workloads
  • Strict JSON or tool-calling flows
Specifications
Family
Llama 3
Released
2024-04-18
Context
8k
Parameters
70B
Architecture
Decoder Only
Knowledge cutoff
2023-12
Specialization
general
Openness
Open weights
License
Llama 3 CommunityCommercial use: conditional
Weights
Available
Code
Unknown
Training
Fine-tuned
Created by

Large-scale open-source AI for social technologies.

Menlo Park, California, United States
Founded 2013
Website
Pricing
Output / 1M
$2.75
Input / 1M
$0.650

Cheapest of 1 route · Replicate API

About

The Llama 3 70B model is a state-of-the-art large language model with 70 billion parameters, released by Meta on April 18, 2024. It's based on an auto-regressive transformer architecture and has been optimized for dialogue applications using supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF). The model supports an 8,000-token context length and has been trained on over 15 trillion tokens from public online sources. It excels in tasks such as conversational AI, text generation, and natural language understanding, outperforming many existing open-source chat models on industry benchmarks.

Top use-case fit: coding, agents, and build tasks

Coding

Q/$ C

1 relevant benchmark in the decision map.

Classification

Q/$ D

2 relevant benchmarks in the decision map.

Provider price ladder

Compare API pricing across 1 providers for input and output tokens, batch, and cached reads when available.

ProviderInput / 1MOutput / 1MRoute
Replicate API$0.650$2.75
Serverless

Capabilities

No model capability flags are currently sourced.

Benchmark peer barsfor Coding

Benchmark scores(7)

Scores are benchmark-specific and are direction-aware: the same numeric gap can mean very different outcomes across suites. Use the leaderboard context and this model's provider route to decide whether the winning margin is meaningful for your workload.
BenchmarkScoreVersionEvaluationSource
Google-Proof Q&A44.1diamondObserved 2026-03-06research
HellaSwag92.410-shotObserved 2026-03-06research
HumanEval72.6pass@1Observed 2026-03-06research
Massive Multitask Language Understanding80.55-shotObserved 2026-03-06research
Grade School Math 8K93.0Observed 2026-05-28Source
BIG-Bench Hard83.2Observed 2026-05-28Source
AI2 Reasoning Challenge94.8Observed 2026-05-28Source

Migration checks

No linked migration route is available for this model yet.

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