Llama 3.3 70B
Meta's Llama 3.3 70B is an open-weights, instruction-tuned language model optimized for multilingual dialogue, offering strong performance with enterprise-friendly licensing.
Overview
What is Llama 3.3 70B
Llama 3.3 70B is Meta's open-weights, instruction-tuned language model released in December 2024. It delivers enhanced performance over prior Llama versions and competes with larger models, optimized for multilingual dialogue and enterprise use cases with strong safety alignment.
Running it privately on Venice
Running on Venice, Llama 3.3 70B benefits from zero retention—your prompts are never stored, profiled, or used for training. This ensures private, sovereign AI interactions while maintaining full access to the model’s open, uncensored capabilities and tool use. You retain control without Big Tech surveillance.
Assessment
Strengths and limitations
- Open weights allow for self-hosting, fine-tuning, and deployment without licensing risk.
- Strong multilingual support in English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai.
- Optimized for dialogue and instruction-following with supervised fine-tuning and RLHF.
- Supports function calling and web search for dynamic, real-time applications.
- Trained on 15T+ tokens with a 128K context window, enabling long-form reasoning and document processing.
- Knowledge cutoff is December 2023, so it lacks awareness of events afterward.
- Not fully uncensored—aligned for safety, which may lead to refusals on edge-case topics.
- Less efficient than smaller models for lightweight or edge deployments.
Capabilities
What it supports
- Tool use / function calling
- Vision (image input)
- Reasoning
- Web search
- Code-optimized
- Structured output (JSON schema)
- Audio input
- Video input
- Multiple image inputs
- Log probabilities
Specifications
Datasheet
- Maker
- Meta
- Released
- December 6, 2024
- Architecture
- Optimized transformer with Grouped-Query Attention (GQA)
- Parameters
- 70B
- Open/closed
- Open weights
- Context window
- 128K tokens
- Max output
- 4.096K tokens
- Capabilities
- Function calling, Web search
- Privacy on Venice
- Private — zero retention
- Available on Venice since
- Apr 2025
- License
- Llama 3.3 Community License Agreement
API
Call it from your code
Venice exposes an OpenAI-compatible API. Point your base URL at Venice and pass the model id.
curl https://api.venice.ai/api/v1/chat/completions \
-H "Authorization: Bearer $VENICE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "llama-3.3-70b",
"messages": [{ "role": "user", "content": "Explain quantum tunneling simply." }]
}'Pricing
What it costs on Venice
Billed per token on Venice: $0.70 per 1M input tokens and $2.80 per 1M output tokens.
New Venice accounts include a free daily allowance and 500 welcome credits — no credit card required.
Alternatives
How it compares
| Model | Max context | Open weights | Price (in/out per 1M) | Strongest at |
|---|---|---|---|---|
| Llama 3.3 70B | 128K tokens | Yes | $0.70 in · $2.80 out / 1M | Multilingual dialogue, open deployment |
| Claude Opus 5 | 1M tokens | No | $6 in · $30 out / 1M | Complex reasoning, long-context tasks |
| DeepSeek V4 Flash 0731 | 1M tokens | Yes | $0.17 in · $0.35 out / 1M | Cost-efficient throughput |
| Google Gemma 4 31B Instruct | 256K tokens | Yes | $0.12 in · $0.36 out / 1M | Efficiency and low-cost scaling |
Balances open licensing with strong performance and privacy on Venice.
Use cases
What it is good for
- 01Enterprise chatbots requiring multilingual support and data sovereignty.
- 02Private research assistants using web search and tool use without data retention.
- 03Custom fine-tuned agents for customer support, compliance, or internal knowledge workflows.
- 04Open-source AI deployments where transparency and license permissiveness are critical.
- 05Applications needing function calling and structured output without vendor lock-in.
Prompting
Getting better results
Use clear system messages to guide tone and role, as the model is instruction-tuned.
Leverage the 128K context for long documents—summarize, extract, or reason over full texts.
Format function calls precisely as shown in Meta’s documentation for reliable tool use.
FAQ
Frequently asked questions
Llama 3.3 70B is Meta's open-weights, instruction-tuned language model released in December 2024. It offers enhanced performance for multilingual dialogue and enterprise applications, with 70 billion parameters and a 128K context window.
Llama 3.3 70B is not open source but has open weights under the Llama 3.3 Community License Agreement. You can download, use, and modify it for commercial purposes, but it is not fully open-source like Apache or MIT-licensed models.
On Venice, Llama 3.3 70B costs $0.70 per 1M input tokens and $2.80 per 1M output tokens. There is no upfront fee—billing is per token, making it cost-effective for variable usage.
Yes, Llama 3.3 70B supports function calling and tool use. It can execute zero-shot function calls in the same format as Llama 3.2, enabling integration with external tools and APIs.
Llama 3.3 70B has a context window of 128,000 tokens, allowing it to process long documents, extended conversations, and complex reasoning tasks in a single session.
Llama 3.3 70B is open and more private, ideal for sovereign deployments. Claude Opus 5 has a larger 1M context and stronger reasoning on long-form tasks but is closed and significantly more expensive. Choose Llama for openness and cost control, Opus for maximum reasoning depth.
No, Llama 3.3 70B is not uncensored. It uses supervised fine-tuning and RLHF to align with safety and helpfulness, which may result in refusals on sensitive topics. However, running it on Venice ensures your prompts are not stored or monitored.
Llama 3.3 70B supports multiple languages including English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai, making it suitable for global enterprise applications.
Run Llama 3.3 70B privately
No prompt logging. No data used for training.