TokenSpeed, an open‑source LLM inference engine designed for agent workloads, delivers TensorRT‑LLM‑level performance and vLLM‑level ease of use, outperforms TensorRT‑LLM by up to 11% throughput and halves latency on speculative decoding, and has earned Nvidia’s public recommendation.
The author benchmarks Gemma 4 locally on a 24 GB M4 Pro MacBook Pro (llama.cpp) and on a Dell GB10 with an NVIDIA Blackwell GPU (Ollama), comparing token speed, tool‑call reliability, and task completion against cloud GPT‑5.4, showing the Mac runs faster per token but the Blackwell system achieves higher first‑pass success with fewer retries, and that the jump from Gemma 3 to Gemma 4 dramatically improves agentic coding viability.
This article examines Nvidia's massive GB202 Blackwell GPU—its 750 mm² die, 922 billion transistors, 192 SMs, and extensive memory subsystem—while comparing its compute units, instruction caches, atomics, and bandwidth against AMD's RDNA4‑based RX 9070, highlighting architectural trade‑offs, performance metrics, and future GPU competition.
This article provides a detailed technical comparison between Nvidia's Blackwell GB202 GPU and AMD's RDNA4 RX 9070, covering CPU and GPU updates, SM front‑end design, memory hierarchies, execution units, atomics, L2 performance, power consumption, and real‑world benchmark results such as FluidX3D.
