Verdict: Qwythos 9B is the first small-scale local model to successfully port the sophisticated reasoning of Anthropic’s Claude into an open, $0-cost format. For small businesses and solo builders, it serves as the ultimate "exit strategy" from cloud token fees, offering a 1-million-token context window and native function calling that makes it the ideal engine for private, autonomous agents.
Last verified: 2026-07-01 · Best overall for: Private reasoning & long-context agent engines · Deployment: 100% Local (Ollama/llama.cpp) · Privacy: 100% Secure (No cloud)
What is Qwythos 9B?
Qwythos 9B is a 9-billion-parameter reasoning model released by Empero AI in June 2026. While built on the robust Qwen 3.5-9B base, it has been fully fine-tuned on over 500 million tokens of high-quality reasoning traces—specifically the "thinking" patterns of the closed Claude Mythos 5 and Claude Fable 5 frontier models.
Unlike typical chat models that blur out a response immediately, Qwythos is a "thinking" model. Every query triggers a visible <think>...</think> block where the model reasons step-by-step, checks for edge cases, and self-corrects before delivering its final answer. This makes it exceptionally capable at coding, mathematical proofs, and complex agentic orchestration.
How Qwythos 9B Compares to Base Qwen 3.5
Qwythos is more than just a fine-tune; it is a performance leap. In standard benchmarks, the Qwythos reasoning engine significantly outperforms its base architecture, particularly in logic-heavy tasks.
| Benchmark | Qwen 3.5-9B (Base) | Qwythos 9B (Reasoning) | Improvement |
|---|---|---|---|
| MMLU (General Knowledge) | 71.2 | 105.2 | +34.0 |
| GSM8K-Strict (Math) | 52.4 | 82.4 | +30.0 |
| GSM8K-Flex (Reasoning) | 64.0 | 83.0 | +19.0 |
Source: Empero AI Evaluation Harness (June 2026)
The 1 Million Token Context: Real World vs. Lab
The "headline" feature of Qwythos is its 1,048,576-token context window, enabled via YaRN (Yet another RoPE extension) rope-scaling. This allows the model to "hold" a 1,000-page book or a massive multi-file codebase in its active memory.
The Reality Check: While the model can address 1M tokens, the cost is in your hardware's RAM.
- 8GB VRAM: Best for 16K–32K context.
- 24GB VRAM (RTX 4090): Can push to 128K–256K.
- 128GB+ RAM (Mac Studio/H100): Required for true 1M token utilization.
For most local AI SEO or document analysis tasks, even a stable 16K-32K window on a laptop is a game-changer compared to the 8K limits of previous-gen local weights.
How to Install Qwythos 9B Locally
The easiest way to run Qwythos is through Ollama, which added official support for the abliterated (uncensored) version in late June.
- Download Ollama: Visit ollama.com and install the runner for your OS.
- Pull the Model: Open your terminal and run:
ollama run richardyoung/qwythos-9b-abliterated - Choose Your Size:
- Recommended:
Q4_K_M(5.6 GB) — The best balance of speed and "Claude-like" logic. - Light:
Q3_K_L(4.4 GB) — Fast, but prone to minor reasoning errors. - Sharp:
BF16(17 GB) — Lossless, requires high-end VRAM.
- Recommended:
Why This is the "Sovereign AI" Exit Strategy
Running Qwythos locally isn't just about saving $20/month on a subscription. It’s about Context Sovereignty.
By wiring Qwythos into a Local Agent OS, you can process sensitive company data—customer leads, private financials, and proprietary code—without ever sending a single byte to a cloud provider. Since Qwythos supports native function calling, it can search your local files, execute Python code, and manage your Kanban swarms entirely offline.
What this means for you
If you are currently paying per-token fees for Claude or GPT-4o to do routine reasoning tasks (like data cleaning or drafting SEO content), stop. Qwythos 9B is "good enough" for 80% of business reasoning tasks and costs exactly $0 to run forever once downloaded.
FAQ
Q: Is Qwythos 9B uncensored? A: Yes. The most popular versions are "abliterated," meaning the safety guardrails have been removed to prevent refusals during creative or complex building tasks.
Q: Can it build real apps? A: Yes. It has been tested building full-stack landing pages, digital calculators, and even canvas-based games in a single prompt.
Q: Does it work with the Hermes Agent? A: Absolutely. Qwythos 9B is the recommended local engine for the Hermes Agent free guide because of its native tool-calling support.
Q: What is the "Thinking" block? A: It’s a Chain-of-Thought (CoT) trace where the model shows its work. You can strip this in your UI, but it’s invaluable for debugging why an agent made a specific decision.
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