InternScience
Agents-A1 4B
前沿65.2K下载量64点赞Jul 2026发布日期262K tokens上下文Apache 2.0许可证62 良好质量
Agents-A1 4B (4.5B parameters) requires approximately 4.7 GB of VRAM with Q4_K_M quantization. For the best balance of quality and speed, we recommend hardware with at least 6 GB of VRAM.
快速开始
— 复制粘贴即可本地运行Copy-paste commands to run Agents-A1 4B on your machine.
Run
docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \
--hf-repo "InternScience/Agents-A1-4B" \
--hf-file "Agents-A1-4B-Q4_K_M.gguf" \
-c 4096 -ngl 99Quick specs
Parameters4.5B
Architecturedense
Context262K tokens
Modalitytext+vision
Min RAM1.8 GB
Rec. RAM2.7 GB (Q4_K_M)
LicenseApache 2.0
FamilyAgents-A1
✓ Reasoning
About this model
- •4.5B dense and vision-capable — fits in ~3GB at Q4.
- •262K context, unusually long for a 4B-class model.
- •Hybrid linear + full attention (1-in-4 layers) keeps long-context KV cache small.
- •Shares the Agents-A1 long-horizon agentic training recipe.
相关模型
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最佳硬件
Agents-A1 4B 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 |
|---|---|---|---|---|
Q1_0_G128 | 1.125 | 0.6 GB | Very Low | — |
Q2_0_G128 | 1.71 | 1.2 GB | Low | — |
Q2_K | 2 | 1.8 GB | Low | — |
Q3_K_S | 3 | 2.2 GB | Low | — |
NVFP4 | 4 | 2.5 GB | Medium | — |
Q4_K_M | 4 | 2.7 GB | Medium | — |
Q5_K_M | 5 | 3.2 GB | High | — |
Q6_K | 6 | 3.7 GB | High | — |
Q8_0 | 8 | 4.8 GB | Very High | — |
F16 | 16 | 9.2 GB | Maximum | — |
Quality benchmarks
Agents-A1 4B benchmark scores
Coding
SWE-bench Verified—
HumanEval+—
Aider Polyglot—
LiveCodeBench59.6%
General
Chatbot Arena—
IFEval94.8%
Source: official · 2026-07-13
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
Weights2.7 GB
KV Cache0.5 GB
Runtime0.9 GB
Headroom0.6 GB
常见问题
FAQ — Agents-A1 4B
另请参阅