1× RTX 5090
252tok/sEveryday
1 request, prose prompt, no speculative decoding Source
Intelligence18with thinkingno thinking 15
Local AI · Recipe · 1× RTX 3090
Qwen3.6 27B Q4_K_M with llama.cpp on 1× RTX 3090 (alesha-pro)
Qwen3.6 27B Q4_K_M with llama.cpp on 1× RTX 3090 (alesha-pro): 63.9 tok/s according to github.com (dataset as of Nov 3, 2026).
by alesha-pro
Intelligence (original model) · Artificial Analysisno independent value
Engine
- Engine
- llama.cpp mainline build 10013 (a4ce2595c)
- Quantization
- GGUF Q4_K_M (17.1 GB) + q4_0 KV
- Model family
- Qwen3.6
- Context
- 200,000
- Parameters
- 27B dense (64 Layer, 16 full attention, 48 Gated DeltaNet)
- Creator
- alesha-pro
- GitHub stars
- 0
- Repo updated
- Aug 4, 2026
Measurements
Every sourced value of this recipe, each with its condition and source. Bars relative to the largest value in the group.
Decode · 1 request
Prefill by context
What you need
- Hardware
- 1 × NVIDIA RTX 3090
- Weights
- Main weightsunsloth/Qwen3.6-27B-MTP-GGUF Apache-2.0
- Engine
- llama.cpp mainline build 10013 (a4ce2595c)
- Context
- 200,000 tokens
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