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EXAONE 3.5 2.4B Instruct
可用数据有限 — 部分规格可能不完整或为估算值。
0K tokens上下文Unknown许可证4 入门质量
EXAONE 3.5 2.4B Instruct (2.4000000953674316B parameters) requires approximately 3.5 GB of VRAM with Q4_K_M quantization. For the best balance of quality and speed, we recommend hardware with at least 5 GB of VRAM.
Quick specs
Parameters2.4B
Architecturedense
Context0K tokens
Modalitytext
Min RAM0.9 GB
Rec. RAM1.5 GB (Q4_K_M)
LicenseUnknown
FamilyUnknown
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最佳硬件
EXAONE 3.5 2.4B Instruct 的最佳选择
运行此模型
量化选项
各量化级别的 VRAM 估算
No hardware detected — fit column shows raw VRAM estimates
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 0.9 GB | Low | — |
Q3_K_S | 3 | 1.2 GB | Low | — |
NVFP4 | 4 | 1.3 GB | Medium | — |
Q4_K_M | 4 | 1.5 GB | Medium | — |
Q5_K_M | 5 | 1.7 GB | High | — |
Q6_K | 6 | 2.0 GB | High | — |
Q8_0 | 8 | 2.6 GB | Very High | — |
F16 | 16 | 4.9 GB | Maximum | — |
硬件兼容性
全部硬件的适配估算
Computing compatibility...
内存详细分析
Reference: RTX 2060 6GB
Weights1.5 GB
KV Cache0.3 GB
Runtime1.2 GB
Headroom0.6 GB
常见问题
FAQ — EXAONE 3.5 2.4B Instruct
另请参阅