Llama 3.3 70B Instruct

Llama 3.3 70B Instruct by Meta excels in the Coding category, where it ranks #180 with a composite score of 67/100. The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). The Llama 3.3 instruction tuned text only model... It is particularly strong in areas highlighted by its top benchmark performance and adoption metrics, making it suitable for both individual developers and enterprise teams looking for a reliable coding solution.

Llama 3.3 70B Instruct is priced at $0.10 per million input tokens and $0.32 per million output tokens (USD). Contact the provider for volume discounts and enterprise pricing. Pricing is competitive within the coding category and reflects the model's quality-to-cost ratio.

In the Coding category, Llama 3.3 70B Instruct holds rank #180 out of 378 models tracked. Its quality rank is #180 and adoption rank is #180. You can use our comparison tool at /compare to see detailed side-by-side metrics with specific alternatives. Key differentiators include its composite scoring across benchmarks, community sentiment, and real-world adoption rates.

Llama 3.3 70B Instruct has been evaluated across 6 different signals. Its strongest areas include Capabilities (50/100), Benchmarks (71/100), Pricing (100/100). These scores are derived from industry-standard benchmarks, community ratings, and real-world performance metrics. The composite score of 67/100 reflects a weighted combination of all tracked signals.

Llama 3.3 70B Instruct is a paid model, though some providers may offer trial credits or limited free tiers for evaluation. Check Meta's website for current free tier availability and promotional offers.

Llama 3.3 70B Instruct supports a 131K token context window (131,072 tokens total). That translates to roughly 98,304 words in a single prompt. This is large enough to process entire codebases, research papers, or long conversation histories in one shot.

Llama 3.3 70B Instruct can generate up to 16K output tokens (16,384 tokens) per response. That is roughly 12,288 words. This is enough for generating complete code files, detailed reports, or long-form content in a single response.

Llama 3.3 70B Instruct supports function/tool calling, structured JSON output, streaming responses. Function calling lets you integrate it with external APIs and tools programmatically. These capabilities determine which workflows and integrations the model can handle natively.

Yes, Llama 3.3 70B Instruct is an open-source model. You can download the weights, run it locally, fine-tune it for your use case, or deploy it on your own infrastructure. Many cloud providers also offer hosted versions if you prefer not to manage the infrastructure yourself. Self-hosting gives you full control over data privacy and eliminates per-token API costs.

Llama 3.3 70B Instruct was developed by Meta. It was released on December 6, 2024. You can access it through Meta's API or download the model weights directly. Check our provider page for all models from Meta and how they compare against each other.

Pick Llama 3.3 70B Instruct when you need a solid balance of cost and capability for everyday development tasks, content generation, and standard API integrations. If your task is straightforward text completion or classification, a cheaper model might give you 90% of the quality at a fraction of the price. Run a quick benchmark on your actual use case before committing.

You can access Llama 3.3 70B Instruct through Meta's API using standard HTTP requests or their official SDK. Most providers support OpenAI-compatible endpoints, so switching between models often requires changing just the model name in your API call. Streaming is supported for real-time token-by-token output. For production use, implement proper error handling, rate limiting, and cost monitoring.