42dot LLM PLM 1.3B vs DeepHat V1 7B
Side-by-side comparison of VRAM requirements, quantization, context length, and hardware compatibility.
Specifications
| 42dot LLM PLM 1.3B | DeepHat V1 7B | |
|---|---|---|
| Parameters | 1.4B | 7.6B |
| Context | 4K | 33K |
| Architecture | LlamaForCausalLM | Qwen2ForCausalLM |
| License | CC BY-NC 4.0 | Apache 2.0 |
| Downloads | 1.1K | 4.6K |
| Released | Feb 2024 | Aug 2025 |
VRAM by Quantization: 42dot LLM PLM 1.3B vs DeepHat V1 7B
| Quantization | Bits | 42dot LLM PLM 1.3B VRAM | DeepHat V1 7B VRAM |
|---|---|---|---|
| BF16 | 16.00 | 3.6 GB | 15.7 GB |
Verdict
42dot LLM PLM 1.3B needs less VRAM at BF16 (3.6 GB vs 15.7 GB), so it fits on smaller GPUs. DeepHat V1 7B supports a longer context window (33K tokens). DeepHat V1 7B is the more widely downloaded of the two.
Frequently Asked Questions
- Which needs less VRAM, 42dot LLM PLM 1.3B or DeepHat V1 7B?
At BF16, 42dot LLM PLM 1.3B needs 3.6 GB and DeepHat V1 7B needs 15.7 GB, so 42dot LLM PLM 1.3B is the lighter option to run locally.
- Which has a longer context window, 42dot LLM PLM 1.3B or DeepHat V1 7B?
42dot LLM PLM 1.3B supports 4,096 tokens and DeepHat V1 7B supports 32,768 tokens.
- What is the difference between 42dot LLM PLM 1.3B and DeepHat V1 7B?
42dot LLM PLM 1.3B is a 1.4B model from 42dot, while DeepHat V1 7B is a 7.6B model from DeepHat. Compare their VRAM requirements above to see which fits your GPU or Mac.