·3 min read
DeepSeek V4 Pro on AgentX: B200 vs B300 and the KV Cache Working Set
50% more HBM squeezes out extra throughput, and the per-point telemetry shows exactly where it comes from
agentxagenticbenchmarkinferencedeepseekb200b300h200nvidia
Articles
Articles on agentic inference, AgentX results, chip performance, and ML infrastructure.
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Allagenticagentsagentxamdannouncementasicb200b300benchmarkcanndeepseekdisaggdynamofp4fp8gb200gb300glm5gpuh100h200huaweiinferencekimilatencymi355xminimaxnvfp4nvidianvl72openaiqwenrocmrubinsglangthroughputtilerttrtllmvllmwide-ep
·2 min read
DeepSeek V4 Pro on AgentX: GB200 vs GB300 Rack-Scale Disaggregation
Both lean on PD disagg, GB300 adds DEP32 wide-EP decode, and the gap shows up in first-token latency rather than token rate
agentxagenticbenchmarkinferencedeepseekgb200gb300nvl72disaggwide-epnvidia
·3 min read
DeepSeek V4 Pro on AgentX: MI355X vs B200, and the August 21 Flip
AMD matched B200 vLLM on performance per dollar for end-to-end latency, then upstream vLLM work moved the line
agentxagenticbenchmarkinferencedeepseekmi355xb200amdnvidia
·2 min read
GLM 5.3 on AgentX: MI355X ATOM Beats GB300 NVL72 on Part of the Curve
Where AMD’s vendor engine wins on performance per dollar, and what E2E Normalized Interactivity actually measures
agentxagenticbenchmarkinferenceglm5mi355xgb300nvl72trtllmsglangamdnvidia
·2 min read
GLM 5.3 on AgentX: NVIDIA Is Up to 5x Cheaper per Token at 150 tok/s/user
At this operating point, free AMD silicon would still not close the gap
agentxagenticbenchmarkinferenceglm5b200b300mi355xsglangnvidiaamd
·2 min read
Kimi K3 on AgentX: MI355X ATOM Beats GB300 NVL72 on Part of the Curve
AMD’s vendor engine wins a real slice of the performance per dollar frontier, while Hopper struggles to serve K3 at all
agentxagenticbenchmarkinferencekimimi355xgb300nvl72h200amdnvidia
·3 min read
MiniMax M3 on AgentX: Why B200 and B300 Beat Their Rack-Scale GB200 NVL72 & GB300 NVL72 Counterparts
The Dynamo router becomes the bottleneck, no submission runs context parallelism, and AMD leaves KV offload on the table
agentxagenticbenchmarkinferenceminimaxb200b300gb200gb300nvl72dynamoamdrocm
·2 min read
MiniMax M3 on AgentX: B300 TRT-LLM TP2 Owns the Crown
NVIDIA sweeps the 432B model, and the missing DP-attention points explain why cache locality became a routing constraint
agentxagenticbenchmarkinferenceminimaxb300b200gb200trtllmvllmnvidia
·2 min read
Qwen3.5 397B on AgentX: B300 FP4 Delivers 12x the Performance per Dollar of H100
What four years of hardware and a 4-bit format buy on a long-context agentic workload
agentxagenticbenchmarkinferenceqwenb300h100h200fp4fp8sglangnvidia
·2 min read
MI355X versus GB300 NVL72 Inference Performance: 20x Gap on Qwen3.5 SGLang
GatedDeltaNet, a 262k native context, and no AMD competition at all on the same engine
agentxagenticbenchmarkinferenceqwensglangtrtllmnvidiaamd
·64 min read
AgentX - InferenceXv3: Does the CUDA Moat Hold Up in Agentic Inferencing?
$3 Million USD dataset open sourced, 1 Mil+ Context Length, Multiturn, Sub Agents 95%+ KVCache HitRate, GB300 NVL72, MI355X, B200
agentxagenticbenchmarkinferencegpunvidiaamdannouncement
·6 min read
A Brief Overview of Agentic Workloads
Multi-turn sessions, long contexts, and near-total prefix reuse make agentic inference a systems problem, and change what a benchmark has to measure
agenticagentsagentxbenchmarkinference
·17 min read
Ultra-High Interactivity on NVIDIA GPUs? TileRT on InferenceX
Can TileRT software on NVIDIA GPUs compete with Cerebras, Groq LPU, and SambaNova? Batch size 1, disaggregated engine, high-throughput prefill engine, high-interactivity decode engine
benchmarkgpuinferencenvidiab200gb300tilertvllmglm5agentxagentic