AFM 4.5B vs DeepHat V1 7B
Side-by-side comparison of VRAM requirements, quantization, context length, and hardware compatibility.
Specifications
| AFM 4.5B | DeepHat V1 7B | |
|---|---|---|
| Parameters | 4.6B | 7.6B |
| Context | 66K | 33K |
| Architecture | ArceeForCausalLM | Qwen2ForCausalLM |
| License | Apache 2.0 | Apache 2.0 |
| Downloads | 1.5K | 4.6K |
| Released | Sep 2025 | Aug 2025 |
VRAM by Quantization: AFM 4.5B vs DeepHat V1 7B
| Quantization | Bits | AFM 4.5B VRAM | DeepHat V1 7B VRAM |
|---|---|---|---|
| BF16 | 16.00 | 9.7 GB | 15.7 GB |
Verdict
AFM 4.5B needs less VRAM at BF16 (9.7 GB vs 15.7 GB), so it fits on smaller GPUs. AFM 4.5B supports a longer context window (66K tokens). DeepHat V1 7B is the more widely downloaded of the two.
Frequently Asked Questions
- Which needs less VRAM, AFM 4.5B or DeepHat V1 7B?
At BF16, AFM 4.5B needs 9.7 GB and DeepHat V1 7B needs 15.7 GB, so AFM 4.5B is the lighter option to run locally.
- Which has a longer context window, AFM 4.5B or DeepHat V1 7B?
AFM 4.5B supports 65,536 tokens and DeepHat V1 7B supports 32,768 tokens.
- What is the difference between AFM 4.5B and DeepHat V1 7B?
AFM 4.5B is a 4.6B model from Arcee AI, while DeepHat V1 7B is a 7.6B model from DeepHat. Compare their VRAM requirements above to see which fits your GPU or Mac.