Feature
Open-source reasoning models (thinking mode)
Reasoning models generate long internal chains-of-thought before answering. They trade latency for accuracy on math, code and multi-step problems. Includes both dedicated reasoning models and Qwen 3 variants with a toggleable thinking mode.
7 models with reasoning
Moonshot AI's 1-trillion-parameter mixture-of-experts (32B active per token). Trained on 15.5T tokens with a heavy emphasis on tool-use and agentic behaviour. Modified-MIT licence with an attribution clause for very-large deployments. Exceptional at long-horizon agent tasks; benchmarked well against Claude Sonnet on SWE-bench Verified.
- Context
- 128K
- License
- kimi
- VRAM Q4
- 600 GB
Reasoning model trained with reinforcement learning on top of DeepSeek V3-Base. MIT licence — even the weights are unrestricted, making R1 the most permissively-licensed frontier reasoning model. Generates long internal chains-of-thought before answering, trading latency for accuracy on math, code, and reasoning benchmarks. Distilled variants (e.g. R1 Distill Llama 70B) recover most of the quality at much smaller scales.
- Context
- 128K
- License
- mit
- VRAM Q4
- 402.6 GB
The flagship Qwen 3 release: a 235B-total MoE with 22B active parameters per token. Competitive with DeepSeek V3 and Llama 4 Maverick on reasoning benchmarks while being smaller total. Apache 2.0 — one of the most permissively licenced frontier-class models.
- Context
- 128K
- License
- apache-2-0
- VRAM Q4
- 141 GB
R1 reasoning capabilities distilled into a Llama 3.3 70B base. The most accessible way to run R1-class reasoning locally — fits on a single H100 in fp16 or on a 4090 at Q4. Inherits Llama 3's community licence (commercial use under 700M MAU). Great pick for production reasoning workloads where the full R1 is too expensive to host but o1/R1-style quality is required.
- Context
- 128K
- License
- llama-3
- VRAM Q4
- 42 GB
Qwen's reasoning-focused 'thinking' model. Generates long chains-of-thought before answering, similar to OpenAI's o1 and DeepSeek R1 lineage. Optimised for math and competition-style problem solving. The Preview tag means Qwen is iterating quickly; later versions may obsolete this one. Useful today for math-heavy workloads where a slow, careful answer is preferred to a fast wrong one.
- Context
- 33K
- License
- apache-2-0
- VRAM Q4
- 19.2 GB
32B sweet-spot Qwen 3, Apache 2.0. Reasoning-mode toggle inherited from smaller siblings; strong on math, code and agentic tool use. Fits on a single H100 in fp16 and on a 4090 at Q4.
- Context
- 33K
- License
- apache-2-0
- VRAM Q4
- 19.2 GB
The April 2025 refresh of Qwen at 8B. Native mixed-mode reasoning: the model can 'think' before answering when triggered, or answer directly for simple queries — configurable per request. Apache 2.0. A strong upgrade over Qwen 2.5 7B on math and code, with much better instruction following.
- Context
- 33K
- License
- apache-2-0
- VRAM Q4
- 4.8 GB