Distil Qwen3 0.6B Text2sql vs DeepSeek R1 Distill Qwen 14B Abliterated v2
Side-by-side comparison of VRAM requirements, quantization, context length, and hardware compatibility.
Specifications
| Distil Qwen3 0.6B Text2sql | DeepSeek R1 Distill Qwen 14B Abliterated v2 | |
|---|---|---|
| Parameters | 596M | 14.8B |
| Context | 41K | 131K |
| Architecture | Qwen3ForCausalLM | Qwen2ForCausalLM |
| License | Apache 2.0 | — |
| Downloads | 173 | 361 |
| Released | Jan 2026 | Jul 2025 |
VRAM by Quantization: Distil Qwen3 0.6B Text2sql vs DeepSeek R1 Distill Qwen 14B Abliterated v2
| Quantization | Bits | Distil Qwen3 0.6B Text2sql VRAM | DeepSeek R1 Distill Qwen 14B Abliterated v2 VRAM |
|---|---|---|---|
| Q2_K | 3.40 | 0.7 GB | 7.0 GB |
| Q3_K_M | 3.90 | 0.7 GB | 7.9 GB |
| Q3_K_S | 3.50 | 0.7 GB | 7.2 GB |
| Q4_0 | 4.00 | 0.7 GB | 8.1 GB |
| Q4_K_M | 4.80 | 0.8 GB | 9.6 GB |
| Q5_K_M | 5.70 | 0.8 GB | 11.2 GB |
| Q6_K | 6.60 | 0.9 GB | 12.9 GB |
| Q8_0 | 8.00 | 1.0 GB | 15.5 GB |
Verdict
Distil Qwen3 0.6B Text2sql needs less VRAM at Q4_K_M (0.8 GB vs 9.6 GB), so it fits on smaller GPUs. DeepSeek R1 Distill Qwen 14B Abliterated v2 supports a longer context window (131K tokens). DeepSeek R1 Distill Qwen 14B Abliterated v2 is the more widely downloaded of the two.
Frequently Asked Questions
- Which needs less VRAM, Distil Qwen3 0.6B Text2sql or DeepSeek R1 Distill Qwen 14B Abliterated v2?
At Q4_K_M, Distil Qwen3 0.6B Text2sql needs 0.8 GB and DeepSeek R1 Distill Qwen 14B Abliterated v2 needs 9.6 GB, so Distil Qwen3 0.6B Text2sql is the lighter option to run locally.
- Which has a longer context window, Distil Qwen3 0.6B Text2sql or DeepSeek R1 Distill Qwen 14B Abliterated v2?
Distil Qwen3 0.6B Text2sql supports 40,960 tokens and DeepSeek R1 Distill Qwen 14B Abliterated v2 supports 131,072 tokens.
- What is the difference between Distil Qwen3 0.6B Text2sql and DeepSeek R1 Distill Qwen 14B Abliterated v2?
Distil Qwen3 0.6B Text2sql is a 596M model from distil-labs (Qwen family), while DeepSeek R1 Distill Qwen 14B Abliterated v2 is a 14.8B model from huihui-ai (Qwen family). Compare their VRAM requirements above to see which fits your GPU or Mac.