SemiAnalysis Benchmark of Real Coding-Agent Traffic Puts Nvidia About Five Times Ahead of AMD on Cost

SemiAnalysis published AgentX, an open-source benchmark that replays recorded coding-agent sessions instead of synthetic prompts, and the result is unfavorable for AMD. At a target interactivity of 150 output tokens per second per user, the analysts report that Nvidia hardware reaches up to five times better cost efficiency than AMD when serving the GLM 5.3 model through the open-source SGLang runtime. Forbes summarized the same finding, noting cost advantages as wide as 20 times on certain open-source software stacks.

The most significant finding in the analysis is not the multiple itself. SemiAnalysis argues that at 150 tokens per second per user, the gap is large enough that cost per token would still favor Nvidia even if a competitor gave its accelerators away for free, once hosting and power costs are counted. That is a claim about software quality, not about the chips themselves. The analysts attribute Nvidia's lead to cache management, request routing, and incremental tokenization, factors that matter far more under agent traffic than under single-turn chat.

The shape of the workload explains why. AgentX uses anonymized Claude Code sessions with a median input of roughly 142,000 tokens against a median output of 444 tokens, plus long idle gaps between turns. Under that profile, any stack that recomputes context aggressively or schedules requests poorly performs worse, while stacks that reuse prefixes and chunks perform better.

Two caveats limit how broadly this number applies. The comparison sets Nvidia's current Blackwell generation against AMD's current CDNA 4 chips, while Nvidia's upcoming Rubin generation, Google's tensor processing units, and AMD's upcoming MI455X chip are not yet included. AgentX also measures one category of work, coding agents, which happens to be the workload Nvidia's serving software has been tuned hardest against. A second AI Post summary of the report repeated the five-times figure without those qualifications, which shows how a benchmark result can turn into an unqualified market narrative.