Falcon 11B — Hardware Requirements & GPU Compatibility
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Falcon2-11B is TII's base pretrained causal decoder model, not instruction-tuned, with 11 billion parameters trained on over 5,000 billion tokens of the RefinedWeb dataset plus curated corpora spanning English and nine other European languages. Training proceeded in stages that grew the context window from 2,048 to 8,192 tokens before a final high-quality data stage. TII recommends further fine-tuning before production use. At 11 billion parameters it runs on a single consumer GPU, especially once quantized. Context length is 8,192 tokens. It is released under the TII Falcon License 2.0, a custom Apache 2.0-based license that adds an acceptable-use policy for responsible use of the model. It was published in May 2024, and has since been superseded by the Falcon3 series.
Runs great on a 24 GB GPU
Runs from 8 GB (Q4_K_M · 4K)Best on 24 GB (Q4_K_M · ~89 tok/s · 8K)Macs from 16 GB (Q4_K_M · ~19 tok/s)
unknown
Reference GPU · RTX 4090 24 GB
Estimates, ±20% · how we estimate
Run Falcon 11B
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
ollama run hf.co/mradermacher/falcon-11B-i1-GGUF:Q4_K_MQ4_K_M fits fully on the RTX 4090 · 15.5 GB free · 8K context
Download: falcon-11B.i1-Q4_K_M.gguf6.85 GBmradermacher
Ways to runOther ways
each opens step-by-stepRun in cloud
Runs on RTX 3080 Ti (12 GB) (3 GB headroom) · Q4_K_M
- Generation speed
- ~81 tok/s
- generation speed
- Cost per 1M output tokens
- $0.42
- per 1M output tokens
How Much VRAM Does Falcon 11B Need?
Select a quantization level; the listed hardware adheres to it.
| Quantization | VRAM | +32K | On RTX 4090 (reference) | |
|---|---|---|---|---|
| 5.2 GB | — | 2-bit · K-quant — 2-bit quantization with K-quant improvements | Fits: 8K context · ~126 tok/s | |
| 5.3 GB | — | 3-bit small — 3-bit small quantization | Fits: 8K context · ~123 tok/s | |
| 6.0 GB | — | 3-bit medium — 3-bit medium quantization | Fits: 8K context · ~110 tok/s | |
| 6.1 GB | — | 4-bit · legacy — 4-bit legacy quantization | Fits: 8K context · ~107 tok/s | |
| 7.3 GB | — | 4-bit medium — 4-bit medium quantization — most popular sweet spot | Fits: 8K context · ~89 tok/s | |
| 8.7 GB | — | 5-bit medium — 5-bit medium quantization — good quality/size tradeoff | Fits: 8K context · ~75 tok/s | |
| 10.1 GB | — | 6-bit, very good — 6-bit quantization, very good quality | Fits: 8K context · ~65 tok/s | |
| 12.2 GB | — | 8-bit, near-lossless — 8-bit quantization, near-lossless | Fits: 8K context · ~54 tok/s |
Selected Q4_K_M
4-bit medium quantization8.5GBat 8K context
- Weights
- 6.6 GB
- KV cache
- 1.6 GB
- Overhead
- 0.3 GB
Fits RTX 4090 (reference) · 15.5 GB free · ~89 tok/s
≥50 tok/s needs ≥563 GB/s · RTX 5090 ~159, RTX 3090 Ti ~89
Which Hardware Can Run Falcon 11B?
Q4_K_M · 7.3 GBFalcon 11B (Q4_K_M) requires 7.3 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 10+ GB is recommended. 52 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti, NVIDIA GeForce RTX 3080. 151 devices with unified memory can run Falcon 11B, including Mac Studio (M3 Ultra, 256GB), Mac Studio (M3 Ultra, 512GB), NVIDIA Jetson Orin Nano 8GB (Super).
12 GB
12 GB tier →fits · 3.5 GB free · up to 8K ctx
10 GPUs
RTX 3080 Ti~81Simulate output on RTX 3080 TiRTX 5070~60Simulate output on RTX 5070RTX 4070~45Simulate output on RTX 407020 GB
fits · 11.5 GB free · up to 8K ctx
1 GPU
RX 7900 XT~66Simulate output on RX 7900 XT32–40 GB
fits · 23.5 GB free · up to 8K ctx
1 GPU · 3 Mac classes · 4 device families
RTX 5090~159Simulate output on RTX 5090M5 Max36 GB~44Simulate output on Mac Studio M5 Max (36 GB)M532 GB~15Simulate output on MacBook Air 13" M5 (32 GB)Orin~18Simulate output on NVIDIA Jetson AGX Orin 32GBSnapdragon X Elite (X1E-80-100)~12Simulate output on Snapdragon X Elite Copilot+ PC
By VRAM tier · typical GPUs and Macs at Q4_K_M
How good is Falcon 11B?
llmrun Score blends public benchmark boards into one number; 100 = the average open model.
Not enough data yet for an llmrun Score.
A Score needs results on enough independent boards. How the Composite Score is built
Benchmarks
Here are all 4 boards that have results for this model, sorted by their weight in the llmrun Score; badges show who ran the test.
- MMLU
Epoch AI · May 2024Lab-reported
Lab-reported58.4%
#51/85 open
- GSM8K
Epoch AI · May 2024Lab-reported
Lab-reported53.8%
#30/62 open
- HellaSwag
Epoch AI · May 2024Lab-reported
Lab-reported82.9%
#11/47 open
- WinoGrande
Epoch AI · May 2024Lab-reported
Lab-reported78.3%
#13/51 open
Alternatives to Falcon 11B
Falcon family · 13 models →Similar models
6| Model | Score | VRAM | tok/s | Why it is similar |
|---|---|---|---|---|
| Gemma 4 12BGoogle | — | 9 GB | ~80 | same size |
| GLM 4.1V 9B ThinkingZ.ai | — | 7.2 GB | ~100 | same size |
| Qwen2.5 Omni 7BAlibaba | — | 9.9 GB | ~93 | same size |
| Llama 3.2 11B Vision InstructMeta | — | 9.8 GB | ~93 | same size |
| Bielik 11B V3.0 Instructspeakleash | — | 27.4 GB | —needs > 24 GB | same size |
| Midm 2.0 Base InstructK-intelligence | — | 10.5 GB | ~86 | same size |
Specifications
- Publisher
- TII UAE
- Family
- Falcon
- Parameters
- 11.1B
- Architecture
- FalconForCausalLM
- Context Length
- 8,192 tokens
- Vocabulary Size
- 65,024
- Release Date
- 2024-05-09
- License
- unknown
Frequently Asked Questions
How much VRAM does Falcon 11B need?
Falcon 11B requires 7.3 GB of VRAM at Q4_K_M, or 24.4 GB at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 11.1B × 4.8 bits ÷ 8 = 6.7 GB
KV Cache + Overhead ≈ 0.6 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
Can NVIDIA GeForce RTX 4090 run Falcon 11B?
Yes, at Q8_0 (12.2 GB) or lower. Higher quantizations like BF16 (24.4 GB) exceed the NVIDIA GeForce RTX 4090's 24 GB.
What's the best quantization for Falcon 11B?
For Falcon 11B, Q4_K_M (7.3 GB) offers the best balance of quality and VRAM usage. Q5_K_S (8.4 GB) provides better quality if you have the VRAM. The smallest option is IQ2_XXS at 3.4 GB.
VRAM requirement by quantization
★ Recommended — best balance of quality and VRAM usage.
Can I run Falcon 11B on a Mac?
Yes — Mac Mini M2 Pro (16 GB) and 133 other Macs can run Falcon 11B. Apple Silicon uses unified memory, so the model shares RAM with the system. At Q4_K_M you need at least 7.3 GB of usable unified memory (RAM minus macOS overhead).
Can I run Falcon 11B locally?
Yes — Falcon 11B can run locally on consumer hardware. Popular tools include Ollama, LM Studio, and llama.cpp.
How fast is Falcon 11B?
At Q4_K_M, Falcon 11B can reach ~655 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~89 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 ÷ 7.33 × 0.65 = ~709 tok/s
Estimated speed at Q4_K_M (7.3 GB)
Real-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
What's the download size of Falcon 11B?
At Q4_K_M, the download is about 6.66 GB. The full-precision BF16 version is 22.21 GB. The smallest option (IQ2_XXS) is 3.05 GB.
Which GPUs can run Falcon 11B?
52 consumer GPUs can run Falcon 11B at Q4_K_M. Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT, AMD Radeon RX 7600. 38 GPUs have plenty of headroom for comfortable inference.
Which devices can run Falcon 11B?
151 devices with unified memory can run Falcon 11B at Q4_K_M (7.3 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.