GPUs are built for training, not inference. General Compute is an inference cloud running on ASICs — purpose-built alternatives to Nvidia silicon designed specifically for inference. We deliver 5x faster responses and higher per-user throughput for latency-sensitive workloads like coding and voice agents. Our OpenAI-compatible API means you swap your base URL, keep your existing workflows, and run real-time AI on infrastructure built for the job.
Hey Product Hunt, I'm Jason, Co-founder & CTO of General Compute!
The Problem
Agents are the most exciting thing happening in AI right now but the infra they run on was designed for chatbots, not autonomous workflows. When an agent has to make 20, 50, sometimes hundreds of sequential LLM calls to complete a task, latency compounds into a ceiling on what's actually possible.
Most inference providers today hit you with one of two tradeoffs:
❌ GPU-based stacks – Great for training, but memory-bandwidth bottlenecks mean your agent runs slowly (~120 tokens/second)
❌ "Fast" inference with catches – Some providers deliver speed but lock you into small models, limited context windows, or pricing that breaks at agent-scale token volume. Speed without intelligence isn’t worth the trade off.
After years building voice agents and real-time AI products ourselves, we got tired of waiting. So we built General Compute.
How General Compute is Different 🚀
GC is an ASIC-first inference cloud built on multiple chips, including SambaNova. SN uses a 3 tier memory architecture and dataflow, which is a fancy way of saying “It’s really fast cause we don’t have the same bottlenecks”.
🔹 Agent first (OpenClaw) – Agents can sign up on their own and manage their own API keys. OpenClaw can move its inference just by pointing it at our website.
🔹 Built for agent workloads – Tuned for both coding agents and voice AI (TTFT), the things that matter when you're chaining dozens of calls. Your agent finishes in seconds, not minutes.
🔹 Speed without the tradeoffs – Frontier open models, full context windows, and pricing that actually works at production scale.
Who is this for?
If you're building AI agents, voice AI ,or even just using OpenClaw or OpenCode and want faster inference, then GC is built for you. Faster inference isn't just a nice-to-have; it unlocks use cases that weren't viable before.
🔗 Get started today
Sign up at https://generalcompute.com and start running your workloads on ASICs today. We are offering $200 in free credit to anyone that signs up through the Product Hunt launch (up from the normal $5 in credit)
The ASIC angle is interesting, how does the model selection compare to GPU clouds? Are you running your own fine-tuned models or is it more about offering the same models (Llama, etc.) just with faster inference?
You’re pushing an ASIC-first stack (including SambaNova) while also offering “bring your own model”: what constraints does the hardware impose on model choice and deployment (architectures, context length, quantization, speculative decoding), and how do you decide what to optimize first for real-world agent traffic?
Big congrats on the launch!
How about the time to set up? Is it able to run on CPU?
Love that this is an OpenAI-compatible API. Being able to just swap the base URL and get ASIC-level inference speeds without rewriting workflows is huge. Great work!
The ASIC-for-inference approach is clever. GPU memory bandwidth just isn't optimized for inference memory access patterns. At RetainSure we've been routing latency-sensitive AI calls for customer success workflows, and 200ms vs 800ms response time matters a lot at scale. How do your ASICs handle KV cache eviction for long-context requests?
OpenClaw can sign itself up? That's wild. Finally someone building for a world where agents run themselves. 👏
Congrats on the launch. Your onboarding workflow is great. I missed clear models and pricing information upfront, and when I got onboarded I saw that you offer three models at somewhat premium pricing.
This leads me to my question: what is your value prop beyond latency? Because if you're competing on price, OpenRouter is still going to get you.
Model
Context
Input / 1M
Output / 1M
DeepSeek V3.2
Reasoning
deepseek-v3.2
32k
$3.00
$4.50
DeepSeek V3.1
Reasoning
deepseek-v3.1
128k
$3.00
$4.50
MiniMax M2.7
minimax-m2.7
160k
$0.40
$2.34
this is a very real agent infra problem. Chatbot latency is annoying, but agent latency compounds into a hard ceiling when workflows need dozens of sequential LLM calls. how General Compute balances raw speed with reasoning quality on longer agent workflows, especially when there is large context, tool use, retries, and coding tasks. Is the biggest gain in TTFT/throughput, or do you also see better end-to-end task completion?
About General Compute on Product Hunt
“AI models that run on an inference cloud optimized for speed”
General Compute launched on Product Hunt on May 22nd, 2026 and earned 242 upvotes and 29 comments, earning #3 Product of the Day. GPUs are built for training, not inference. General Compute is an inference cloud running on ASICs — purpose-built alternatives to Nvidia silicon designed specifically for inference. We deliver 5x faster responses and higher per-user throughput for latency-sensitive workloads like coding and voice agents. Our OpenAI-compatible API means you swap your base URL, keep your existing workflows, and run real-time AI on infrastructure built for the job.
General Compute was featured in API (98.2k followers), Software Engineering (42.5k followers) and Alpha (10 followers) on Product Hunt. Together, these topics include over 16.7k products, making this a competitive space to launch in.
Who hunted General Compute?
General Compute was hunted by Ben Lang. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how General Compute stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Ben Lang
Hey Product Hunt, I'm Jason, Co-founder & CTO of General Compute!
The Problem
Agents are the most exciting thing happening in AI right now but the infra they run on was designed for chatbots, not autonomous workflows. When an agent has to make 20, 50, sometimes hundreds of sequential LLM calls to complete a task, latency compounds into a ceiling on what's actually possible.
Most inference providers today hit you with one of two tradeoffs:
❌ GPU-based stacks – Great for training, but memory-bandwidth bottlenecks mean your agent runs slowly (~120 tokens/second)
❌ "Fast" inference with catches – Some providers deliver speed but lock you into small models, limited context windows, or pricing that breaks at agent-scale token volume. Speed without intelligence isn’t worth the trade off.
After years building voice agents and real-time AI products ourselves, we got tired of waiting. So we built General Compute.
How General Compute is Different 🚀
GC is an ASIC-first inference cloud built on multiple chips, including SambaNova. SN uses a 3 tier memory architecture and dataflow, which is a fancy way of saying “It’s really fast cause we don’t have the same bottlenecks”.
🔹 Agent first (OpenClaw) – Agents can sign up on their own and manage their own API keys. OpenClaw can move its inference just by pointing it at our website.
🔹 Built for agent workloads – Tuned for both coding agents and voice AI (TTFT), the things that matter when you're chaining dozens of calls. Your agent finishes in seconds, not minutes.
🔹 Speed without the tradeoffs – Frontier open models, full context windows, and pricing that actually works at production scale.
Who is this for?
If you're building AI agents, voice AI ,or even just using OpenClaw or OpenCode and want faster inference, then GC is built for you. Faster inference isn't just a nice-to-have; it unlocks use cases that weren't viable before.
🔗 Get started today
Sign up at https://generalcompute.com and start running your workloads on ASICs today. We are offering $200 in free credit to anyone that signs up through the Product Hunt launch (up from the normal $5 in credit)