NVIDIA RTX 4050 6GB

generation:

25-35 tokens/s

quant:

Q5_K_M (GGUF)

Reported by the source; GPU count, offloading and concurrent requests can change these figures. Prompt-processing speed is shown only when the source reports it; generation speed cannot tell us time to first token. Check the full setup before comparing.

User reports Qwen3.6-35B-A3B at 25-35 tok/s on an RTX 4050 Laptop 6GB with 64GB DDR5 RAM and an i5-13420H. Setup is LM Studio with Q5_K_M and RAM offload, running 34-36k context windows. User notes a 2-minute time to first token and says the speed is outstanding for the hardware. They ask whether the model and quant are a good fit for a 3D model parameter data structuring workflow, and mention they do not need uncensored or abliterated variants.

generation:

14.0 tokens/s

quant:

Q4_K_S (GGUF)

Reported by the source; GPU count, offloading and concurrent requests can change these figures. Prompt-processing speed is shown only when the source reports it; generation speed cannot tell us time to first token. Check the full setup before comparing.

User compares DanilAI and LM Studio running Qwen3-30B-A3B-Instruct-2507 on an RTX 4050 Laptop (6 GB VRAM) with a Ryzen 7 7435HS and 24 GB RAM. LM Studio with Q4_K_S quantization reached 14.03 tokens/sec; DanilAI with hybrid FP16/8-bit/4-bit precision plus DanilDrive compression reached 25.0 tokens/sec. A separate test ran Qwen3-0.6B in FP16 with DanilDrive, reporting approximately 45% lossless compression. OBS Studio was recording throughout and may have affected performance.

generation:

76.2 tokens/s

Reported by the source; GPU count, offloading and concurrent requests can change these figures. Prompt-processing speed is shown only when the source reports it; generation speed cannot tell us time to first token. Check the full setup before comparing.

User reports Qwen3-0.6B at 76.2 t/s on an RTX 4050 Laptop 6GB, a 4.19x speedup over uncompressed bf16 (18.2 t/s). Setup is a custom engine (DanilDrive-W) with lossless dictionary-compressed bf16 weights, decompressed inline in the CUDA kernel; file size drops from 1433.7 MB to 765.5 MB (-46.6%). User also tested Qwen3-Coder-30B-A3B against Ollama and LM Studio on the same Q4_K_M GGUF, getting 16-18 t/s versus their 24-26 t/s, and notes greedy decoding can diverge after ~200 characters due to float summation order.

generation:

129.0 tokens/s

prompt processing (prefill):

8500.0 tokens/s

Reported by the source; GPU count, offloading and concurrent requests can change these figures. Prompt-processing speed is input throughput, not time to first token. Check the full setup before comparing.

User benchmarks 20 small models on an RTX 4050 6GB. Models tested include Granite 4.1 3B, Gemma-4-agentic-e2b, Nemotron-3-Nano-4B and LFM2.5-8B-A1B. The user selects LFM2.5-1.2B-Instruct as a cheap always-on model.