Models · 46Qwen3.6-27B-Fable-Agentic
Qwen3.6-27B-Fable-Agentic
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- Base model
- Jackrong/Qwopus3.6-27B-v2
- Updated
- 1mo ago
Qwen3.6-27B-Fable-Agentic
Agentic - Reasoning - Tool-Calling - Top-Tier Knowledge
Qwen3.6-27B-Fable-Agentic is a powerful 27B agentic model that reasons step-by-step and operates tools across multi-turn sessions, while delivering top-tier general knowledge. Fine-tuned from Jackrong/Qwopus3.6-27B-v2.
Benchmarks
Evaluated head-to-head against the base model on identical questions, with an 8192-token budget so step-by-step reasoning is never truncated.
| Benchmark | Base | This model |
|---|---|---|
| MMLU-Pro (350 Q) | 86.86% | 88.29% |
| GSM8K (300 Q) | 98.00% | 97.33% |
| GPQA-Diamond (198 Q) | 57.58% | 57.07% |
Knowledge improved, hard reasoning preserved: +1.43 over base on MMLU-Pro, matching it on GSM8K math and on GPQA-Diamond (graduate-level science, ~frontier-class for a 27B) - with agentic tool-calling added on top.
MMLU-Pro by category
| Category | Base | This model |
|---|---|---|
| Biology | 96.0% | 94.0% |
| Business | 78.0% | 88.0% |
| Chemistry | 84.0% | 80.0% |
| Computer Science | 84.0% | 84.0% |
| Health | 82.0% | 86.0% |
| Math | 94.0% | 94.0% |
| Physics | 90.0% | 92.0% |
| Overall | 86.86% | 88.29% |
Highlights
- Top-tier knowledge - 88.29% MMLU-Pro, above the base model
- Strong math - 97.33% GSM8K
- Agentic tool-calling across multi-turn sessions
- Step-by-step reasoning built in
Capabilities
- Agentic, multi-turn tool-calling
- Chain-of-thought reasoning
- Top-tier general knowledge and math
- Multimodal (vision + text) architecture
Usage (vLLM)
vllm serve lemuralabs/Qwen3.6-27B-Fable-Agentic --trust-remote-code --reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser qwen3_coder --max-model-len 16384
Tip: this model reasons before answering - give it a generous max_tokens so it can finish its chain of thought.
License
Apache 2.0