Falcon 7B Instruct — Hardware Requirements & GPU Compatibility
Chat
Falcon 7B Instruct is the instruction-tuned version of TII's Falcon 7B, fine-tuned on a mix of chat and instruction datasets to follow user prompts more reliably. It was among the early open models to show that a well-tuned 7B model could handle conversational tasks, summarization, and basic reasoning without requiring massive hardware. While newer models have since raised the bar, Falcon 7B Instruct remains a lightweight option for users who want a responsive local assistant with modest resource requirements.
Runs great on a 24 GB GPU
Runs from 8 GB (Q4_K_M · 16K)Best on 24 GB (Q4_K_M · ~138 tok/s · 32K)Macs from 16 GB (Q4_K_M · ~29 tok/s)
Apache 2.0
Reference GPU · RTX 4090 24 GB
Estimates, ±20% · how we estimate
Run Falcon 7B Instruct
One recommended way. Every other method, OS and quant is in the step-by-step guide.Each way opens a step-by-step guide for your OS and quant.
Recommended
vllm serve tiiuae/falcon-7b-instruct --max-model-len 16384vLLM repo with its own quantisation
Download: Weights on Hugging Face
Ways to runOther ways
each opens step-by-stepRun in cloud
Runs on RTX 3080 Ti (12 GB) (4 GB headroom) · Q4_K_M
- Generation speed
- ~125 tok/s
- generation speed
- Cost per 1M output tokens
- $0.27
- per 1M output tokens
How Much VRAM Does Falcon 7B Instruct Need?
Select a quantization level; the listed hardware adheres to it.
| Quantization | VRAM | +32K | On RTX 4090 (reference) | |
|---|---|---|---|---|
| 3.4 GB | 8.7 GB | 2-bit · K-quant — 2-bit quantization with K-quant improvements | Fits: 32K context · ~194 tok/s | |
| 3.9 GB | 9.2 GB | 3-bit medium — 3-bit medium quantization | Fits: 32K context · ~169 tok/s | |
| 4.8 GB | 10.1 GB | 4-bit medium — 4-bit medium quantization — most popular sweet spot | Fits: 32K context · ~138 tok/s | |
| 5.7 GB | 11 GB | 5-bit medium — 5-bit medium quantization — good quality/size tradeoff | Fits: 32K context · ~116 tok/s | |
| 6.5 GB | 11.9 GB | 6-bit, very good — 6-bit quantization, very good quality | Fits: 32K context · ~100 tok/s | |
| 7.9 GB | 13.3 GB | 8-bit, near-lossless — 8-bit quantization, near-lossless | Fits: 32K context · ~83 tok/s | |
| 15.9 GB | 21.2 GB | 16-bit · bfloat — Brain floating point 16 — preferred for training | Fits: 32K context · ~41 tok/s |
Selected Q4_K_M
4-bit medium quantization7.3GBat 16K context
- Weights
- 4.1 GB
- KV cache
- 2.9 GB
- Overhead
- 0.3 GB
Fits RTX 4090 (reference) · 16.8 GB free · ~138 tok/s
≥50 tok/s needs ≥366 GB/s · RTX 5090 ~245, RTX 3090 Ti ~138
Which Hardware Can Run Falcon 7B Instruct?
Q4_K_M · 4.8 GBFalcon 7B Instruct (Q4_K_M) requires 4.8 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 7+ GB is recommended. 52 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti. 151 devices with unified memory can run Falcon 7B Instruct, including Mac Studio (M3 Ultra, 256GB), Mac Studio (M3 Ultra, 512GB).
≤ 11 GB
≤ 11 GB tier →fits · 0.8 GB free · up to 16K ctx
16 GPUs · 2 device families
RTX 3080~104Simulate output on RTX 3080RTX 2080 Ti~84Simulate output on RTX 2080 TiRTX 3070 Ti~83Simulate output on RTX 3070 TiOrin Nano~14Simulate output on NVIDIA Jetson Orin Nano 8GB (Super)iPhone~10Simulate output on iPhone 1720 GB
fits · 12.8 GB free · up to 32K ctx
1 GPU
RX 7900 XT~101Simulate output on RX 7900 XT32–40 GB
fits · 24.8 GB free · up to 32K ctx
1 GPU · 3 Mac classes · 4 device families
RTX 5090~245Simulate output on RTX 5090M5 Max36 GB~68Simulate output on Mac Studio M5 Max (36 GB)M532 GB~23Simulate output on MacBook Air 13" M5 (32 GB)Orin~28Simulate output on NVIDIA Jetson AGX Orin 32GBSnapdragon X Elite (X1E-80-100)~18Simulate output on Snapdragon X Elite Copilot+ PC
By VRAM tier · typical GPUs and Macs at Q4_K_M
Alternatives to Falcon 7B Instruct
Falcon family · 13 models →Similar models
6| Model | Score | VRAM | tok/s | Why it is similar |
|---|---|---|---|---|
| Qwen2.5 7B InstructAlibaba | 65.1 | 5.8 GB | ~131 | same size |
| Olmo 3 7B InstructAllen AI | — | 8.4 GB | ~114 | same size |
| Phi Mini MoE InstructMicrosoft | — | 5.4 GB | ~239 | same size |
| DeepSeek R1 Distill Qwen 7BDeepSeek | — | 5.8 GB | ~131 | same size |
| Eurus 2 7B PRIMEPRIME-RL | — | 5.1 GB | ~131 | same size |
| Mathstral 7B v0.1Mistral AI | — | 6.8 GB | ~133 | same size |
Specifications
- Publisher
- TII UAE
- Family
- Falcon
- Parameters
- 7.2B
- Architecture
- FalconForCausalLM
- Vocabulary Size
- 65,024
- Release Date
- 2023-04-25
- License
- Apache 2.0
Frequently Asked Questions
How much VRAM does Falcon 7B Instruct need?
Falcon 7B Instruct requires 4.8 GB of VRAM at Q4_K_M, or 15.9 GB at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 7.2B × 4.8 bits ÷ 8 = 4.3 GB
KV Cache + Overhead ≈ 0.5 GB (at 2K context + ~0.3 GB framework)
Fit ratings and hardware model lists check this model with room for a 16K-token context, which needs a little more memory.
VRAM usage by quantization
What's the best quantization for Falcon 7B Instruct?
For Falcon 7B Instruct, Q4_K_M (4.8 GB) offers the best balance of quality and VRAM usage. Q5_K_M (5.7 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 3.4 GB.
VRAM requirement by quantization
★ Recommended — best balance of quality and VRAM usage.
Can I run Falcon 7B Instruct on a Mac?
Yes — Mac Mini M2 Pro (16 GB) and 133 other Macs can run Falcon 7B Instruct. Apple Silicon uses unified memory, so the model shares RAM with the system. At Q4_K_M you need at least 4.8 GB of usable unified memory (RAM minus macOS overhead).
Can I run Falcon 7B Instruct locally?
Yes — Falcon 7B Instruct can run locally on consumer hardware. Popular tools include Ollama, LM Studio, and llama.cpp.
How fast is Falcon 7B Instruct?
At Q4_K_M, Falcon 7B Instruct can reach ~1008 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~138 tok/s. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: NVIDIA B200 → 8000 ÷ 4.76 × 0.65 = ~1092 tok/s
Estimated speed at Q4_K_M (4.8 GB)
Real-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
What's the download size of Falcon 7B Instruct?
At Q4_K_M, the download is about 4.33 GB. The full-precision BF16 version is 14.43 GB. The smallest option (Q2_K) is 3.07 GB.
Which GPUs can run Falcon 7B Instruct?
52 consumer GPUs can run Falcon 7B Instruct at Q4_K_M. Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT. 52 GPUs have plenty of headroom for comfortable inference.
Which devices can run Falcon 7B Instruct?
151 devices with unified memory can run Falcon 7B Instruct at Q4_K_M (4.8 GB), including AMD Ryzen AI 9 HX 370 (Strix Point) Laptop, ASUS Ascent GX10, Beelink GTR9 Pro (Ryzen AI Max+ 395, 128 GB), Framework Desktop (Ryzen AI Max+ 395, 128 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.