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qwen3.6-35b-a3b-nvfp4-vllm-cpp
Qwen3.6-35B-A3B in NVFP4, served by vllm.cpp. A 35B mixture-of-experts model with roughly 3B parameters active per token, so it reads like a much larger model while costing about as much per token as a small one. This is the engine's gated MoE checkpoint: token-for-token identical to vLLM over the 315-prompt battery on both the synchronous and asynchronous paths, at 0.92x to 0.97x vLLM's throughput from concurrency 1 to 32. The architecture is a gated-delta-net hybrid, so automatic prefix caching is off by default here where it would be on for a dense model. That is the engine's own default and this entry does not override it. Needs a Blackwell-class NVIDIA GPU and roughly 23 GB of weights plus KV cache.

Repository: localaiLicense: apache-2.0

qwen3.6-35b-a3b-nvfp4-mtp-vllm-cpp
Qwen3.6-35B-A3B NVFP4 on vllm.cpp with MTP speculative decoding enabled. The draft head ships inside the checkpoint's own mtp.* tensors, so there is no second model to download. On this model the speculative path is token-exact against speculation-off on both the synchronous and asynchronous schedulers. Same weights as qwen3.6-35b-a3b-nvfp4-vllm-cpp; install that entry instead if you would rather not spend the extra memory on speculative state. MTP is depth 1 by construction on this engine.

Repository: localaiLicense: apache-2.0

nousresearch_hermes-4-14b
Hermes 4 14B is a frontier, hybrid-mode reasoning model based on Qwen 3 14B by Nous Research that is aligned to you. Read the Hermes 4 technical report here: Hermes 4 Technical Report Chat with Hermes in Nous Chat: https://chat.nousresearch.com Training highlights include a newly synthesized post-training corpus emphasizing verified reasoning traces, massive improvements in math, code, STEM, logic, creativity, and format-faithful outputs, while preserving general assistant quality and broadly neutral alignment. What’s new vs Hermes 3 Post-training corpus: Massively increased dataset size from 1M samples and 1.2B tokens to ~5M samples / ~60B tokens blended across reasoning and non-reasoning data. Hybrid reasoning mode with explicit … segments when the model decides to deliberate, and options to make your responses faster when you want. Reasoning that is top quality, expressive, improves math, code, STEM, logic, and even creative writing and subjective responses. Schema adherence & structured outputs: trained to produce valid JSON for given schemas and to repair malformed objects. Much easier to steer and align: extreme improvements on steerability, especially on reduced refusal rates.

Repository: localaiLicense: apache-2.0

primeintellect_intellect-2
INTELLECT-2 is a 32 billion parameter language model trained through a reinforcement learning run leveraging globally distributed, permissionless GPU resources contributed by the community. The model was trained using prime-rl, a framework designed for distributed asynchronous RL, using GRPO over verifiable rewards along with modifications for improved training stability. For detailed information on our infrastructure and training recipe, see our technical report.

Repository: localaiLicense: apache-2.0

nousresearch_deephermes-3-llama-3-3b-preview
DeepHermes 3 Preview is the latest version of our flagship Hermes series of LLMs by Nous Research, and one of the first models in the world to unify Reasoning (long chains of thought that improve answer accuracy) and normal LLM response modes into one model. We have also improved LLM annotation, judgement, and function calling. DeepHermes 3 Preview is a hybrid reasoning model, and one of the first LLM models to unify both "intuitive", traditional mode responses and long chain of thought reasoning responses into a single model, toggled by a system prompt. Hermes 3, the predecessor of DeepHermes 3, is a generalist language model with many improvements over Hermes 2, including advanced agentic capabilities, much better roleplaying, reasoning, multi-turn conversation, long context coherence, and improvements across the board. The ethos of the Hermes series of models is focused on aligning LLMs to the user, with powerful steering capabilities and control given to the end user. This is a preview Hermes with early reasoning capabilities, distilled from R1 across a variety of tasks that benefit from reasoning and objectivity. Some quirks may be discovered! Please let us know any interesting findings or issues you discover!

Repository: localaiLicense: llama3

nousresearch_deephermes-3-llama-3-8b-preview
DeepHermes 3 Preview is the latest version of our flagship Hermes series of LLMs by Nous Research, and one of the first models in the world to unify Reasoning (long chains of thought that improve answer accuracy) and normal LLM response modes into one model. We have also improved LLM annotation, judgement, and function calling. DeepHermes 3 Preview is one of the first LLM models to unify both "intuitive", traditional mode responses and long chain of thought reasoning responses into a single model, toggled by a system prompt. Hermes 3, the predecessor of DeepHermes 3, is a generalist language model with many improvements over Hermes 2, including advanced agentic capabilities, much better roleplaying, reasoning, multi-turn conversation, long context coherence, and improvements across the board. The ethos of the Hermes series of models is focused on aligning LLMs to the user, with powerful steering capabilities and control given to the end user. This is a preview Hermes with early reasoning capabilities, distilled from R1 across a variety of tasks that benefit from reasoning and objectivity. Some quirks may be discovered! Please let us know any interesting findings or issues you discover!

Repository: localaiLicense: llama3

nousresearch_hermes-4-70b
Hermes 4 70B is a frontier, hybrid-mode reasoning model based on Llama-3.1-70B by Nous Research that is aligned to you. Read the Hermes 4 technical report here: Hermes 4 Technical Report Chat with Hermes in Nous Chat: https://chat.nousresearch.com Training highlights include a newly synthesized post-training corpus emphasizing verified reasoning traces, massive improvements in math, code, STEM, logic, creativity, and format-faithful outputs, while preserving general assistant quality and broadly neutral alignment. What’s new vs Hermes 3 Post-training corpus: Massively increased dataset size from 1M samples and 1.2B tokens to ~5M samples / ~60B tokens blended across reasoning and non-reasoning data. Hybrid reasoning mode with explicit … segments when the model decides to deliberate, and options to make your responses faster when you want. Reasoning that is top quality, expressive, improves math, code, STEM, logic, and even creative writing and subjective responses. Schema adherence & structured outputs: trained to produce valid JSON for given schemas and to repair malformed objects. Much easier to steer and align: extreme improvements on steerability, especially on reduced refusal rates.

Repository: localaiLicense: llama3

nousresearch_deephermes-3-mistral-24b-preview
DeepHermes 3 Preview is the latest version of our flagship Hermes series of LLMs by Nous Research, and one of the first models in the world to unify Reasoning (long chains of thought that improve answer accuracy) and normal LLM response modes into one model. We have also improved LLM annotation, judgement, and function calling. DeepHermes 3 Preview is a hybrid reasoning model, and one of the first LLM models to unify both "intuitive", traditional mode responses and long chain of thought reasoning responses into a single model, toggled by a system prompt. Hermes 3, the predecessor of DeepHermes 3, is a generalist language model with many improvements over Hermes 2, including advanced agentic capabilities, much better roleplaying, reasoning, multi-turn conversation, long context coherence, and improvements across the board. The ethos of the Hermes series of models is focused on aligning LLMs to the user, with powerful steering capabilities and control given to the end user. This is a preview Hermes with early reasoning capabilities, distilled from R1 across a variety of tasks that benefit from reasoning and objectivity. Some quirks may be discovered! Please let us know any interesting findings or issues you discover!

Repository: localaiLicense: apache-2.0