Alibaba
Qwen3 1.7B
reasoning
2B
Parameters
1,2 Go
Q4_K_M file
≥ 2,7 Go
Recommended VRAM
40 960
Max context
Speed by graphics card
Simulate in the “Configurator” →Standard llama-bench run (prompt 512 / generation 128 tokens), model fully in VRAM. Click a card for details. Electricity cost at the default price (0,25 €/kWh).
| Card · Q4_K_M | VRAM | Generation | Prompt | VRAM used | Power | € elec. / M tok | Price |
|---|---|---|---|---|---|---|---|
| RTX 5070 Ti | 16 Go | 456 tok/s | 22 669 | 2,9 Go | 84 W | 0,01 €/M tok | — |
Not measured on these cards yet — click for an estimate:
Technical sheet
- Published
- 2025-04-27
- Architecture
- 28 layers · 8 KV heads · dimension 128
- Attention
- Standard: every layer keeps the whole context in memory.
- Context cache (f16)
- ≈ 109 MB per 1,000 tokens · 3,5 Go for 32,768 tokens
- GGUF file
- bartowski/Qwen_Qwen3-1.7B-GGUF · Qwen_Qwen3-1.7B-Q4_K_M.gguf Download (1,2 Go)
- Official repo
- Qwen/Qwen3-1.7B
Public Hugging Face data (official config.json, GGUF repo). The context cache only counts full-attention layers.