Technology Innovation Institute's 180-billion parameter dense open-weights model trained on extensive multilingual web and technical tokens.
Technical Specifications
- Provider
- TII
- Category
- open-source
- Release Date
- 2024-12
- Batch API Discount
- Standard rate
- Consumer Subscription
- Free / Self-Hosted
- Reasoning Effort Control
- Fixed
- Structured Outputs
- Yes
- Output Modalities
- text
- Official Documentation
- Visit Official Docs ↗
Data Privacy, Licensing & Deployment Governance
Official Provider Release Intelligence, API Quotas & Agentic Specs
- Official API Model ID (SDK String)
- falcon-3-180b
- Supported SDK & API Protocol
- OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
- Lifecycle & Deprecation Status
- Legacy Stable (Upgrade path available in TII lineup)
- Production Rate Limits (RPM & TPM)
- Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud
- Long-Context Pricing Tier (>128K / >200K)
- Free across full context window (only KV-cache VRAM scales)
- Prompt Cache Write & TTL Policy
- Automatic prefix KV-caching in vLLM / SGLang (0 cost)
- Computer Use & Browser GUI Agent
- API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)
- MCP & Parallel Tool Calling
- Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
- Web Search Grounding & Code Sandbox
- Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools
- Fine-Tuning & Distillation Support
- Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)
- Multimodal Tokenization Billing
- Text BPE (~4 chars/token)
- Weights Precision & Quantization
- BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0)
- Minimum GPU VRAM Requirement
- 112 GB VRAM (4-bit Quantized) · 387 GB VRAM (Native BF16)
- Supported Inference Engines
- vLLM, SGLang, Ollama, llama.cpp, TensorRT-LLM, HuggingFace TGI
- System Card & Safety Framework
- Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)
- Enterprise Compliance (SOC2 / HIPAA / ZDR)
- 100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control
Falcon 3 180B Cost, Context, Hardware & API Integration
Open-weights or free-tier model: $0 API license cost when self-hosted.
Same Monthly Workload Cost Across Popular Reference Models
Live Prompt Paste Tokenizer & Cost Counter
Paste real system instructions, JSON schemas, or code to measure BPE token counts across tokenizers.
Hybrid Prompt Routing Cascade Simulator
Route routine queries to a fast lightweight model ($0.15/1M) and escalate only complex reasoning turns to Falcon 3 180B:
Benchmark Scores & 6-Axis Capability Radar
- GPQA Diamond
- 54%
- MMLU-Pro
- 76%
- HumanEval
- 82%
- Chatbot Arena Elo
- 1280pts
Strengths
- Dense 180B architecture with deep factual retention and multilingual breadth
- Open weights with royalty-free commercial licensing
- Proven baseline for sovereign research and customized government models
Limitations & Trade-offs
- 32K context window is restrictive compared to modern 256K+ models
- Dense architecture demands substantial memory footprint compared to sparse MoEs
Editorial Assessment
TII's flagship dense open model representing Middle Eastern AI research leadership.
Best for: Sovereign national AI initiatives, academic foundational research, and private cluster deployments
Compare Falcon 3 180B
Frequently Asked Questions about Falcon 3 180B
How much does the Falcon 3 180B API cost per 1M tokens?+
Falcon 3 180B by TII is priced at $0 per 1M input tokens and $0 per 1M output tokens. With prompt caching enabled, cached input tokens cost $0 per 1M tokens, and asynchronous Batch API requests receive a 0% discount.
Should I use a $20/month subscription or the Falcon 3 180B pay-as-you-go API?+
A flat $20/month consumer subscription is predictable for daily interactive chat and manual coding. However, if you are building software, running automated workflows, or sending low-to-moderate volume with prompt caching enabled, the pay-as-you-go API is typically far more cost-effective and offers higher rate limits without manual UI caps.
How many words and pages fit in Falcon 3 180B's context window?+
Falcon 3 180B features a 33K tokens context window, which equals approximately 24,576 English words or ~66 standard single-spaced pages in a single prompt. Its maximum output generation per turn is 4,096 tokens.
Can I run Falcon 3 180B locally on my own GPU (Open Weights)?+
Yes, Falcon 3 180B (180B) releases open weights that can be self-hosted locally or on private cloud GPUs using vLLM, Ollama, SGLang, or llama.cpp.
Does TII train on data sent to the Falcon 3 180B API, and is commercial use allowed?+
100% Isolated when self-hosted on private GPUs or VPC. License tier: Open-Weights Research & Commercial License. Full commercial ownership of generated outputs. Supported deployment channels include: Self-Hosted GPU (vLLM / Ollama), Private VPC, or Managed Serverless API.
How does Falcon 3 180B perform on coding and reasoning benchmarks?+
Falcon 3 180B achieves a composite Intelligence Index of 78/100, scoring N/A% on SWE-bench Verified, 54% on GPQA Diamond, 76% on MMLU-Pro, and 1280 pts on Chatbot Arena Elo.
What is Falcon 3 180B best used for?+
Falcon 3 180B is best suited for: Sovereign national AI initiatives, academic foundational research, and private cluster deployments. Assessment: TII's flagship dense open model representing Middle Eastern AI research leadership.
AI Glossary & Architecture Concepts
View full glossary →Key machine learning concepts and benchmarks relevant to Falcon 3 180B:
The basic unit of text that a language model processes, typically representing about 3 to 4 English characters or roughly 0.75 words. For example, the sentence "Artificial intelligence is fast" breaks down into about 5 tokens.
A standardized evaluation suite used to objectively measure and rank an AI model's capabilities across specific tasks — such as SWE-bench Verified for software engineering, AIME for competitive math, or MMLU for general knowledge.
The maximum number of tokens a model can consider at once — both the input it reads and the output it writes. A 1,000,000-token context window can hold roughly 750,000 English words in a single request.
The ability of a language model to recognize when an external capability is needed and output structured JSON arguments to invoke external APIs, databases, or terminal commands. The runtime executes the tool and passes results back to the model.
An open standard created by Anthropic that allows AI applications and agents to connect seamlessly to local filesystems, development environments, and third-party APIs via standardized server interfaces.
The neural network architecture introduced in 2017 that powers modern LLMs, using self-attention mechanisms to process all tokens in a sequence concurrently rather than sequentially.
Benchmark scores, token prices, and rate limits evolve rapidly as AI labs release model updates. Always verify current specifications and pricing on the official provider documentation.
Sources: Technology Innovation Institute Falcon Documentation↗