·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
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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
·20 min read
Vera Rubin NVL72 vs GB200 NVL72? Inference TCO & Architecture Analysis
Rubin LUT Based Tensor Core, Feynman, Rack Scale, Perf Per MegaWatt, Perf Per Dollar, Software Improvements, Public Rubin Software, PyTorch, vLLM, OpenAI Triton
benchmarkgpuinferencenvidiarubingb200gb300deepseektrtllmdynamo
·29 min read
DeepSeekV4 1.6T Day 0 to Day 43 Performance Over Time — Huawei, GB300 NVL72, MI355X, B200
Day 0 Inference Performance, InferenceX, 100x performance improvement in 26 Days, Cost per Million Tokens, Huawei 950DT Inference Trace Analysis
benchmarkgpuinferencedeepseeknvidiaamdhuaweigb300b300b200mi355xh200sglangvllmtrtllmcann
·10 min read
GB300 NVL72 vs GB200 NVL72 Inference Performance & Perf per Dollar - on DeepSeek-V4-Pro 1.6T: Up to 2.83x Throughput
DSv4-Pro FP4 8K/1K, Dynamo+vLLM, disaggregated on both racks. GB300's 50% extra HBM (288 vs 192 GB/GPU) unlocks a wider prefill+decode recipe GB200 can't fit — lifting middle-of-curve perf/$ by 2.31x despite a 20% per-GPU TCO premium.
benchmarkgpuinferencedeepseeknvidiagb300gb200nvl72vllmdynamowide-epdisagg
·13 min read
MI355X DeepSeek-V4-Pro on SGLang: 110.5x Throughput per GPU in 26 Days
The amd/deepseek_v4 side branch shipped TileLang attention indexer, Triton sparse MLA, fused RoPE/Hadamard, FlyDSL MoE, and FP4 weights across 31 performance optimizations PRs — lifting first-light 20 tok/s/GPU at 2.4 tok/s/user into 2,256 tok/s/GPU at 9.4 tok/s/user on 8K/1K, with both throughput and interactivity climbing together
benchmarkgpuinferencedeepseekamdmi355xsglangrocmfp4
·8 min read
GB200 NVL72 vs B200 on DeepSeek R1 670B: Up to 4.4x Throughput per GPU at 125 tok/s/user
DeepSeek R1 FP4 1k/1k. NVL72's 72-GPU NVLink scale-up fabric lets decode run wide EP up to EP=32, where B200's 8-GPU NVLink island caps out at EP=8 over RoCEv2
benchmarkgpuinferencedeepseeknvidiagb200b200nvl72trtllmdynamowide-epdisagg
·5 min read
SGLang 0.5.6 on B200 DeepSeek R1 FP4: Up to 1.8x at Low Concurrency
Piecewise CUDA graphs for DeepSeek V3, a unified event loop, and JIT kernels push 8k/1k throughput from 508 to 907 tok/s/GPU on the same 16 GPU B200 pool
benchmarkinferencegpunvidiab200deepseeksglangfp4