Llama 3.3 70B Instruct
Meta's open-weights 70B flagship matching Llama 3.1 405B capabilities on industry benchmarks at 1/5th the compute.
128k
Tokens
8.192k
Output limit
Dense Transformer
Model family
70B
Total / Active
$0.12
Per 1M tokens
$0.30
Per 1M tokens
Model Overview
Llama 3.3 70B Instruct delivers industry-leading open-weights performance comparable to 405B parameter models. Features 128k context window, robust tool calling, structured JSON output, and broad local deployment compatibility with vLLM, Ollama, and llama.cpp.
Developer Implementation Notes
Can be run locally in 4-bit quantization (Q4_K_M) on a single 48GB GPU (or dual 24GB RTX 3090/4090s) and 64GB Mac Studio.
Key Strengths
- Open-weights with permissive commercial license (under 700M MAU)
- Matches previous 405B capabilities on coding and reasoning
- Fits comfortably on dual 24GB GPUs or single 48GB A40/A6000
- Extensive ecosystem tooling support
Limitations & Boundaries
- Text only (no native image or audio support)
- Higher memory footprint than 32B models
Capabilities & Modalities
Best Production Use Cases
- On-premise enterprise deployment and data privacy compliance
- Custom fine-tuning for proprietary company data
- Cost-effective agent and copilot backends
Verified Benchmark Results
Standardized evaluations with methodology notes and authoritative citation links.
Pricing & Inference Cost Calculator
Token Cost Estimator – Llama 3.3 70B Instruct
Calculate projected inference spend with prompt caching
Quick Workload Presets
$0.2400
2.00M input tokens
$0.1500
0.50M output tokens
$0.39
Avg: $0.00039 / req
Deployment & Integration Options
Compare with Similar Models
DeepSeek-R1
Open-weights frontier reasoning model trained via large-scale reinforcement learning without supervised cold start.
Codestral 2501
Mistral AI's dedicated code generation model with 256k context window and fill-in-the-middle (FIM) capabilities.
DeepSeek-V3
Frontier open-weights 671B MoE base and chat model with multi-head latent attention (MLA) and dual-pipe training.
Data Accuracy & Verification Notice
AI model specifications, pricing records, and benchmark metrics published on this platform are compiled directly from authoritative sources (official provider documentation, research papers, and verified evaluation harnesses). Benchmark results reflect specific test harnesses and prompting methodologies; scores are not directly comparable across differing evaluation setups.