Rishiraj Dutta Gupta and Wafer Team
Wafer integration with TrueFoundry AI Gateway
How Wafer's fast, OpenAI-compatible serverless inference integrates with TrueFoundry AI Gateway for unified routing, observability, and zero data retention.
Ian YePerformance per dollar is getting faster and cheaper
How we served GLM5.2 on AMD MI355X at 2626 tok/s/node and 213 tok/s single stream at over 2x lower cost than Blackwell.
Balaji Varadarajan and Wafer TeamThe Inference Alpha: Maximizing Frontier Models on AMD
How DigitalOcean and Wafer unlock order-of-magnitude inference speedups on AMD GPUs for Kimi 2.5, DeepSeek V3.2, and GLM-5 through deep kernel and systems engineering.
Ian YeAchieving Heterogeneous Compute One Kernel at a Time
How custom kernels pushed our AMD MI355X deployment from a tuned baseline to leading Qwen3.5 397B throughput.
John HahnQuantizing Kimi K2.6 to NVFP4 for Blackwell Inference
Wafer and Parasail released wafer-ai/Kimi-K2.6-NVFP4: Blackwell NVFP4 weights for production Kimi K2.6 inference.
Danny Willow LiuQwen3.6-35B-A3B on AMD MI355X: Being The Fastest With ATOM on AMD
ATOM on 8×MI355X leads public Qwen3.6-35B-A3B on Artificial Analysis decode and sustains ~15k tok/s per node at production latency.
Emilio AndereAnnouncing our Seed Round
Wafer has raised $4 million in seed funding led by Fifty Years to build AI that optimizes AI infrastructure.
Steven ArellanoWhere Did My Microseconds Go?
In our NVFP4 KernelArena suite, cpp_extension.load() hid a blind spot: JIT and CPU migration inflated kernel launch times.
Emilio AndereA Field Guide to Reward Hacking in AI Kernel Generation
Ten ways LLMs game GPU kernel benchmarks: timer tricks, garbage reads, caching, and the checks that catch them.
Steven ArellanoIntroducing KernelArena
Benchmark AI-generated GPU kernels, with first results on WaferBench NVFP4 (B200) and KernelBench HIP (MI300X).
Wafer TeamTrace Compare: Compare vLLM traces across platforms
1:1 kernel mappings across providers. Diff huge vLLM traces fast with clean prefill vs decode.
Wafer TeamWorkspaces: GPU Compute for Your Coding Agent
Give your AI coding assistant direct GPUs, with no manual SSH, Docker, or infra babysitting.
Wafer TeamCloud Compiler Analyzer (PTX/SASS) Inside Your IDE
Cloud CUDA builds with PTX/SASS, PyTorch headers, and VS Code integration. No local CUDA install.
Wafer TeamNordlys Labs: 8x Faster Routing with Wafer-Guided Kernel Optimization
A non-kernel expert hit 8× on latency-critical CUDA clustering with Wafer profile-guided optimization.
Wafer TeamProfile-Guided GPU Kernel Optimization
Profiling in our CLI broke a theory-only plateau: 11.65× on the Kimi Delta Attention kernel.
Wafer TeamThe Year of the LLM GPU Kernel Engineer
Our agent optimized AMD's topk_sigmoid kernel: 9× over PyTorch, step by step.
Wafer TeamCase Study: A 104x (?) Speedup on KernelBench
A fused kernel claimed 104× speedup while reading garbage, and passed checks until we added a determinism guard.
Wafer TeamWhich models are the most HIP?
Frontier models wrote HIP kernels for KernelBench on MI300X. We measured which ones were correct and how fast.
Wafer Teamwafer-ai CLI: GPU Superpowers for Your Coding Agent
GPU docs, trace analysis, and remote kernel eval for your coding agent via the wafer-ai CLI.
Wafer TeamGPU Docs: Now Available on the Web
The GPU docs tool from our IDE extension, now a standalone web app.
Wafer TeamIntroducing ROCprofiler Compute: AMD GPU Profiling in Your IDE
AMD profiling in VS Code and Cursor: metrics, roofline, and kernel stats without leaving the editor.
Wafer TeamIntroducing Wafer's Built-in Perfetto Trace Viewer
Open Chrome trace JSON in your IDE with Perfetto: timeline, flamegraphs, SQL, metrics.
Wafer TeamIntroducing the Wafer Extension for VS Code and Cursor
Profiling (NCU), compiler explorer, and GPU docs: your GPU stack inside the editor.
Wafer TeamIntroducing Chip Benchmark: Hardware-Centric Performance Insights for AI Workloads
Chip Benchmark is our open suite for open-weight LLMs across accelerators, so you can pick hardware with real numbers.
Wafer TeamUnlocking AMD MI300X for High-Throughput, Low-Cost LLM Inference
MI300X packs 192GB HBM3 and 5.3 TB/s bandwidth, often skipped for LLM inference. We show quantization and tuning.