AstaBrief 8B — Hardware Requirements & GPU Compatibility
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AstaBrief 8B is a 8B-parameter open language model from Allen AI. It supports a context window of up to 40,960 tokens. At Q4_K_M it needs about 5.40 GB of VRAM — see which GPUs and Macs can run it below.
1.6K downloads
63 likesSpecifications
- Publisher
- Allen AI
- Parameters
- 8B
- Architecture
- Qwen3ForCausalLM
- Context Length
- 40,960 tokens
- Vocabulary Size
- 151,936
- Release Date
- 2026-02-09
- License
- Apache 2.0
Get Started
HuggingFace
Run in cloud
Fits on RTX 3060 12GB (6 GB headroom) · Q4_K_M
- Generation speed
- ~43 tok/s
- generation speed
- Cost per 1M output tokens
- $0.39
- per 1M output tokens
How Much VRAM Does AstaBrief 8B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_Kest. | 3.40 | 4 GB | 9.7 GB | 3.40 GB | 2-bit quantization with K-quant improvements |
| Q3_K_Mest. | 3.90 | 4.5 GB | 10.2 GB | 3.90 GB | 3-bit medium quantization |
| Q4_K_Mest. | 4.80 | 5.4 GB | 11.1 GB | 4.80 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_Mest. | 5.70 | 6.3 GB | 12.0 GB | 5.70 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_Kest. | 6.60 | 7.2 GB | 12.9 GB | 6.60 GB | 6-bit quantization, very good quality |
| Q8_0est. | 8.00 | 8.6 GB | 14.3 GB | 8.00 GB | 8-bit quantization, near-lossless |
| BF16est. | 16.00 | 16.6 GB | 22.3 GB | 16.00 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 AstaBrief 8B?
Q4_K_M · 5.4 GBAstaBrief 8B (Q4_K_M) requires 5.4 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 8+ GB is recommended. Using the full 41K context window can add up to 5.7 GB, bringing total usage to 11.1 GB. 52 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti, NVIDIA GeForce RTX 3070 Ti.
Runs great
— Plenty of headroom
Decent
— Enough VRAM, may be tightWhich Devices Can Run AstaBrief 8B?
Q4_K_M · 5.4 GB53 devices with unified memory can run AstaBrief 8B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, NVIDIA Jetson Orin Nano 8GB (Super).
Runs great
— Plenty of headroomDecent
— Enough memory, may be tightRelated Models
Frequently Asked Questions
- How much VRAM does AstaBrief 8B need?
AstaBrief 8B requires 5.4 GB of VRAM at Q4_K_M, or 16.6 GB at BF16. Full 41K context adds up to 5.7 GB (11.1 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 8B × 4.8 bits ÷ 8 = 4.8 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.
KV Cache + Overhead ≈ 6.3 GB (at full 41K context)
VRAM usage by quantization
Q4_K_M5.4 GBQ4_K_M + full context11.1 GB- What's the best quantization for AstaBrief 8B?
For AstaBrief 8B, Q4_K_M (5.4 GB) offers the best balance of quality and VRAM usage. Q5_K_M (6.3 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 4 GB.
VRAM requirement by quantization
Q2_K4.0 GBQ4_K_M ★5.4 GBQ5_K_M6.3 GBQ6_K7.2 GBQ8_08.6 GBBF1616.6 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run AstaBrief 8B on a Mac?
Yes, but only at lower quantizations. The smallest Mac that can run AstaBrief 8B is MacBook Air 13" M3 (8 GB) at Q2_K; 39 of the 39 Macs we list can run it at some quantization. For Q4_K_M (5.4 GB) you need a Mac with more unified memory.
- Can I run AstaBrief 8B locally?
Yes — AstaBrief 8B can run locally on consumer hardware. At Q4_K_M quantization it needs 5.4 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is AstaBrief 8B?
At Q4_K_M, AstaBrief 8B can reach ~889 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~121 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 ÷ 5.4 × 0.65 = ~963 tok/s
Estimated speed at Q4_K_M (5.4 GB)
~963 tok/s~121 tok/s~963 tok/s~889 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of AstaBrief 8B?
At Q4_K_M, the download is about 4.80 GB. The full-precision BF16 version is 16.00 GB. The smallest option (Q2_K) is 3.40 GB.
- Which GPUs can run AstaBrief 8B?
52 consumer GPUs can run AstaBrief 8B at Q4_K_M (5.4 GB). Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT, AMD Radeon RX 7600. 40 GPUs have plenty of headroom for comfortable inference.
- Which devices can run AstaBrief 8B?
53 devices with unified memory can run AstaBrief 8B at Q4_K_M (5.4 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.