Benchmark result
peculiar-ragdoll/Cyber-Tiel-Coder-35B-A3B-GGUF:Q4_K_XL on NVIDIA GeForce RTX 2060 — 25.9 tok/s
Measured with llama.cpp manual on September 22, 2026.
What the model built
Open full screen →The coding scenario asks for a playable game in a single HTML file. This is exactly what the model returned, unedited; the frame only adds a line that tells this page how tall it is.
How this run compares
1st fastest of 2 runs of this model on NVIDIA GeForce RTX 2060 · median 19.6 tok/s.
sort
- 125.9tok/s83.0llama.cpp · Q4_Kthis run
- 213.2tok/s59.4OpenAI-compatible · Q4_K
Reproduce this run
toolllama.cpp manual
modelpeculiar-ragdoll/Cyber-Tiel-Coder-35B-A3B-GGUF:Q4_K_XL (Q4_K)
context131,072
clientv0.4.80+98
Set those in llama.cpp, then:
llm-benchmark benchmark --model "peculiar-ragdoll/Cyber-Tiel-Coder-35B-A3B-GGUF:Q4_K_XL" --tool "llama.cpp"The client prompts for context length and thinking mode, and for the KV cache dtype on Unsloth Studio. Sampling is left at the model default — the values above are what the tool reported using, not overrides the client sent.