AgentFounder-30B
AgentFounder-30B is an open-weights language model from Qwen, released September 16, 2025. It has 30B parameters (dense).
Large language models (LLMs) have evolved into agentic systems capable of autonomous tool use and multi-step reasoning for complex problem-solving. However, post-training approaches building upon general-purpose foundation models consistently underperform in agentic tasks, particularly in open-source implementations.
Check it against your own PC →
Can you run AgentFounder-30B locally?
The smallest common GPU it runs on is 12 GB of VRAM (with 32 GB of RAM): IQ3_XXS, split GPU / CPU, roughly 6 tokens per second. Estimates assume 32 GB of DDR5 RAM, a 16K context and llama.cpp-style GGUF quantization. Enter your exact hardware in the live app.
| GPU memory | Verdict | Best quant | VRAM | RAM | tok/s |
|---|---|---|---|---|---|
| 6 GB VRAM | Very slow | IQ3_XXS (noticeable loss) | 5.2 GB | 10.2 GB | ~3 |
| 8 GB VRAM | Very slow | IQ3_XXS (noticeable loss) | 7.2 GB | 8.2 GB | ~3 |
| 12 GB VRAM | Runs, slowly | IQ3_XXS (noticeable loss) | 11.2 GB | 4.2 GB | ~6 |
| 16 GB VRAM | Runs, slowly | IQ4_XS (good) | 15.2 GB | 4.6 GB | ~5 |
| 24 GB VRAM | Runs on GPU | Q4_K_M (very good) | 22.2 GB | – | ~30 |
| 32 GB VRAM | Runs on GPU | Q6_K (≈ lossless) | 28.5 GB | – | ~42 |
Benchmark results
Epoch AI has not published results for AgentFounder-30B yet. New models are usually evaluated within days to weeks.
Links
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