Llama 3 70B Instruct
Llama 3 70B Instruct is worth evaluating for coding, classification, and json / tool use when its provider route and context window match the workload.
Use it for
- Teams evaluating coding, classification, and json / tool use
- Workloads that can use a 8k context window
- Buyers comparing 4 tracked provider routes
Do not use it for
- Vision or document-understanding workloads
- 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
Large-scale open-source AI for social technologies.
Cheapest of 18 routes · Hyperbolic AI Inference
About
The Llama 3 70B Instruct model is a large language model with 70 billion parameters, released by Meta on April 18, 2024. It's an instruction-tuned variant optimized for conversational applications, utilizing an advanced auto-regressive transformer architecture. The model excels in following instructions and engaging in dialogue, having been trained on over 15 trillion tokens with a December 2023 knowledge cutoff. It demonstrates superior performance on industry benchmarks, scoring 82.0 on the MMLU (5-shot) test. The model incorporates extensive safety measures and optimizations, including RLHF, to enhance helpfulness and reduce harmful content generation. For more details, visit the model's Hugging Face page [1].
Llama 3 70B Instruct is an open-weight model in the Llama 3 family. The structured metadata tracks a 8k-token context window and structured outputs. This page tracks provider routes through GCP Vertex AI, AWS Bedrock, Microsoft Foundry, and 15 more, with the cheapest tracked route listed at $0.4 input and $0.4 output per 1M tokens. Headline tracked benchmarks include HumanEval 72.6, Massive Multitask Language Understanding 82.0, and Instruction-Following Evaluation 77.8.
Top use-case fit: coding, agents, and build tasks
Coding
Q/$ B1 relevant benchmark in the decision map.
Classification
Q/$ C2 relevant benchmarks in the decision map.
JSON / Tool use
Included by capability and metadata signals in the decision map.
Provider price ladder
Compare all 18Compare API pricing across 4 providers for input and output tokens, batch, and cached reads when available.
| Provider | Input / 1M | Output / 1M | Route |
|---|---|---|---|
| Hyperbolic AI Inference | $0.400 | $0.400 | Serverless |
| DeepInfra | $0.450 | $0.650 | Serverless |
| Novita AI | $0.510 | $0.740 | Serverless |
| OpenRouter | $0.510 | $0.740 | Serverless |
Available via routers & gateways(16)
LiteLLM
GatewayOpen-source Python SDK and proxy server that unifies 100+ LLM APIs behind a single OpenAI-compatible interface, with load balancing, cost tracking, and configurable failover.
OpenRouter
HybridUnified hybrid gateway to 400+ models from 60+ providers via a single OpenAI-compatible API, with optional auto-routing that selects the best model per prompt.
Portkey
GatewayProduction AI gateway routing to 1,600+ LLMs with failover, load balancing, semantic caching, and guardrails; Apache 2.0 core is fully self-hostable with the complete feature set.
AIRouter
RouterCommercial LLM router that analyzes incoming requests and routes to the optimal model for cost/quality/latency via a drop-in OpenAI-compatible API, with a privacy-preserving embedding mode that avoids sending prompt content.
Amazon Bedrock Intelligent Prompt Routing
RouterAWS Bedrock's native intelligent prompt router that routes prompts between Anthropic Claude model tiers (Haiku/Sonnet) based on predicted task complexity, with no extra per-routing charge.
Azure AI Foundry Model Router
RouterMicrosoft Azure AI Foundry's native model router that uses a trained ML model to route each prompt in real time to the optimal Azure-hosted model, with Balanced/Cost/Quality mode selection and automatic failover.
Capabilities
Benchmark peer barsfor Coding
Benchmark scores(4)
| Benchmark | Score | Version | Source |
|---|---|---|---|
| HumanEval | 72.6 | pass@1 | https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard |
| Massive Multitask Language Understanding | 82.0 | 5-shot | https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard |
| Instruction-Following Evaluation | 77.8 | v2 | https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard |
| MMLU PRO | 57.4 | — | https://huggingface.co/spaces/TIGER-Lab/MMLU-Pro |
Migration checks
No linked migration route is available for this model yet.
Compare Llama 3 70B Instruct with other models
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Comparison and alternatives
Browse all comparisons →Show all 41 popular comparisonssorted by 7-day search impressions
Frequently asked questions
What is the context window of Llama 3 70B Instruct?
Llama 3 70B Instruct has a context window of 8k tokens.
How much does Llama 3 70B Instruct cost?
Llama 3 70B Instruct pricing ranges from $0.40/1M to $3.78/1M input tokens depending on the provider.
When was Llama 3 70B Instruct released?
Llama 3 70B Instruct was released on 2024-04-18.
Which providers offer Llama 3 70B Instruct?
Llama 3 70B Instruct is available from 18 providers: GCP Vertex AI, AWS Bedrock, Microsoft Foundry, NVIDIA NIM, DeepInfra, OctoAI API (Deprecated), Databricks Foundation Model Serving, Fireworks AI, Baseten API, Lepton AI API, OCI Generative AI, Together AI, IBM watsonx, Scale AI GenAI Platform, Hyperbolic AI Inference, OpenRouter, Replicate API, Novita AI.
What benchmarks has Llama 3 70B Instruct been tested on?
Llama 3 70B Instruct has been evaluated on 4 benchmarks, including HumanEval, Massive Multitask Language Understanding, Instruction-Following Evaluation, MMLU PRO.
Large-scale open-source AI for social technologies.
Cheapest of 18 routes · Hyperbolic AI Inference