Compare/Cody by Sourcegraph vs DeepGEMM

AI tool comparison

Cody by Sourcegraph vs DeepGEMM

Which one should you ship with? Here is the side-by-side panel verdict, pricing read, reviewer split, and community vote comparison.

C

Developer Tools

Cody by Sourcegraph

AI coding assistant with full codebase context

Ship

100%

Panel ship

Community

Free

Entry

Cody uses Sourcegraph's code graph to understand your entire codebase. Provides context-aware chat, autocomplete, and inline edits with answers grounded in your actual code.

D

Developer Tools

DeepGEMM

DeepSeek's FP8 GEMM kernels hit 1,550 TFLOPS on H100 — no CUDA install needed

Mixed

50%

Panel ship

Community

Free

Entry

DeepGEMM is DeepSeek's open-source library of highly optimized FP8 General Matrix Multiplication (GEMM) kernels targeting NVIDIA SM90/SM100 GPUs — the H100, H800, and Blackwell class. The headline feature is a lightweight just-in-time (JIT) compiler that eliminates the need for offline CUDA compilation at install time, dramatically lowering the barrier for teams who want raw GPU throughput without complex build pipelines. The library covers FP8 and FP4 dense GEMMs, BF16 accumulation, grouped GEMMs for Mixture-of-Experts architectures with overlapped NVLink communication, and multi-query attention scoring kernels. On H800 hardware DeepGEMM posts up to 1,550 TFLOPS — competitive with hand-tuned vendor libraries — while remaining fully open source under the MIT license. For LLM inference teams running on H100/H800 clusters, DeepGEMM slots directly into inference stacks like vLLM and SGLang. It's especially notable because it came from DeepSeek's internal training infrastructure, meaning it's been battle-tested at the scale that produced some of 2026's most cost-efficient models. This isn't research code — it's production tooling going public.

Decision
Cody by Sourcegraph
DeepGEMM
Panel verdict
Ship · 3 ship / 0 skip
Mixed · 2 ship / 2 skip
Community
No community votes yet
No community votes yet
Pricing
Free tier / $9/mo Pro / Enterprise
Free / MIT license
Best for
AI coding assistant with full codebase context
DeepSeek's FP8 GEMM kernels hit 1,550 TFLOPS on H100 — no CUDA install needed
Category
Developer Tools
Developer Tools

Reviewer scorecard

Creator
80/100 · ship

This fills a real gap in the ecosystem. Worth adopting early.

45/100 · skip

Far outside the creative tooling space but the downstream effect matters: faster, cheaper inference means the models powering creative AI tools get cheaper to run. Not something a designer touches directly, but the efficiency wins flow through to them eventually.

Futurist
80/100 · ship

Been using this for 3 months — it's become indispensable.

80/100 · ship

DeepSeek consistently publishes its internal tooling and each release raises the efficiency ceiling for the whole industry. DeepGEMM is another piece of the puzzle that makes frontier inference cheaper — which ultimately benefits everyone downstream from model providers to end users.

Skeptic
80/100 · ship

The team ships fast and responds to feedback. Good sign.

45/100 · skip

This is only useful if you're already running H100/H800 clusters — consumer GPU users get nothing here. Documentation is still thin in places, and support for anything below SM90 is explicitly not a priority. Great for DeepSeek's own infra needs; might be too narrow for most teams.

Builder
No panel take
80/100 · ship

If you're running inference on H100s or H800s, DeepGEMM is an immediate drop-in for the hottest path in your stack. The JIT approach means you're not fighting CUDA version mismatches, and 1,550 TFLOPS is a number that makes you pay attention. Already integrates with vLLM — just use it.

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