Claim Extractor 4B Q 2605 — Hardware Requirements & GPU Compatibility
ChatClaim Extractor 4B Q 2605 is a 4.7B-parameter open language model from principled-intelligence. It supports a context window of up to 262,144 tokens. At BF16 it needs about 9.79 GB of VRAM — see which GPUs and Macs can run it below.
Specifications
- Publisher
- principled-intelligence
- Parameters
- 4.7B
- Architecture
- Qwen3_5ForConditionalGeneration
- Context Length
- 262,144 tokens
- Vocabulary Size
- 248,320
- Release Date
- 2026-05-14
- License
- Apache 2.0
Get Started
How Much VRAM Does Claim Extractor 4B Q 2605 Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| BF16est. | 16.00 | 9.8 GB | 31.1 GB | 9.32 GB | Brain floating point 16 — preferred for training |
est.= calculated VRAM estimate; no published GGUF file found for that quantization yet. Other rows are verified against real community uploads.
Which GPUs Can Run Claim Extractor 4B Q 2605?
BF16 · 9.8 GBClaim Extractor 4B Q 2605 (BF16) requires 9.8 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 13+ GB is recommended. Using the full 262K context window can add up to 21.3 GB, bringing total usage to 31.1 GB. 39 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti, NVIDIA GeForce RTX 3080 Ti.
Runs great
— Plenty of headroomDecent
— Enough VRAM, may be tightWhich Devices Can Run Claim Extractor 4B Q 2605?
BF16 · 9.8 GB49 devices with unified memory can run Claim Extractor 4B Q 2605, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, iPad Pro M5 13" (16 GB).
Runs great
— Plenty of headroomDecent
— Enough memory, may be tightRelated Models
Frequently Asked Questions
- How much VRAM does Claim Extractor 4B Q 2605 need?
Claim Extractor 4B Q 2605 requires 9.8 GB of VRAM at BF16. Full 262K context adds up to 21.3 GB (31.1 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 4.7B × 16 bits ÷ 8 = 9.3 GB
KV Cache + Overhead ≈ 0.5 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 21.8 GB (at full 262K context)
VRAM usage by quantization
BF169.8 GBBF16 + full context31.1 GB- Can I run Claim Extractor 4B Q 2605 on a Mac?
Claim Extractor 4B Q 2605 requires at least 9.8 GB at BF16, which exceeds the unified memory of most consumer Macs. You would need a Mac Studio or Mac Pro with a high-memory configuration.
- Can I run Claim Extractor 4B Q 2605 locally?
Yes — Claim Extractor 4B Q 2605 can run locally on consumer hardware. At BF16 quantization it needs 9.8 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Claim Extractor 4B Q 2605?
At BF16, Claim Extractor 4B Q 2605 can reach ~449 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~67 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 ÷ 9.8 × 0.65 = ~531 tok/s
Estimated speed at BF16 (9.8 GB)
~531 tok/s~67 tok/s~531 tok/s~449 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Claim Extractor 4B Q 2605?
At BF16, the download is about 9.32 GB.
- Which GPUs can run Claim Extractor 4B Q 2605?
39 consumer GPUs can run Claim Extractor 4B Q 2605 at BF16 (9.8 GB). Top options include AMD Radeon RX 6800, AMD Radeon RX 6800 XT, AMD Radeon RX 6900 XT, AMD Radeon RX 6700 XT. 26 GPUs have plenty of headroom for comfortable inference.
- Which devices can run Claim Extractor 4B Q 2605?
52 devices with unified memory can run Claim Extractor 4B Q 2605 at BF16 (9.8 GB), including AMD Ryzen AI 9 HX 370 (Strix Point) Laptop, ASUS Ascent GX10, Apple iPhone 17 Pro, Asus ROG Flow Z13 (2025, 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.