stosssik

stosssik

11 日前議論

[dead]

stosssik

16 日前議論

Original approach for their annual shareholder decks. I liek that.

stosssik

17 日前議論

[flagged]

stosssik

26 日前議論

Can't remember if the correct parameter for your LLM is max_tokens or max_completion_tokens ?

Say no more: we are launching modelparams . dev, the first complete model parameters database, open and collaborative.

You can browse it (UI), query it (API) or types in your app (NPM).

stosssik

3 か月前議論

A curated list of LLM APIs with permanent free tiers, no trial credits, no credit card traps.

Info included: rate limits, max context, and supported modalities.

Here's the list per provider:

Cohere (https://cohere.com/)

  • Command A (111B)
  • Command R+
  • Command R
  • + 3 more model (https://docs.cohere.com/docs/models)

Google Gemini (https://ai.google.dev/)

  • Gemini 2.5 Flash
  • Gemini 2.5 Flash-Lite

Mistral AI (https://mistral.ai/)

  • Mistral Small 4
  • Mistral Medium 3
  • Mistral Large 3
  • + 3 more model (https://docs.mistral.ai/getting-started/models/models_overview/)

Z AI (Zhipu AI) (https://z.ai/)

  • GLM-4.7-Flash
  • GLM-4.5-Flash
  • GLM-4.6V-Flash

Inference providers - Third-party platforms that host open-weight models from various sources.

Cerebras (https://cerebras.ai/)

  • llama3.1-8b
  • gpt-oss-120b
  • qwen-3-235b-a22b-instruct-2507
  • zai-glm-4.7

Cloudflare Workers AI (https://developers.cloudflare.com/workers-ai/)

  • @cf/meta/llama-3.3-70b-instruct-fp8-fast
  • @cf/meta/llama-3.1-8b-instruct-fp8-fast
  • @cf/meta/llama-3.2-11b-vision-instruct
  • + 5 more models (https://developers.cloudflare.com/workers-ai/models/)

GitHub Models (https://github.com/marketplace/models)

  • gpt-4.1
  • gpt-4.1-mini
  • gpt-4o
  • + 7 more models (https://github.com/marketplace/models)

Groq (https://groq.com/)

  • llama-3.3-70b-versatile
  • llama-3.1-8b-instant
  • llama-4-scout-17b-16e-instruct
  • + 7 more models (https://console.groq.com/docs/models)

Hugging Face (https://huggingface.co/)

  • Meta-Llama-3.1-8B-Instruct
  • Mistral-7B-Instruct-v0.3
  • Mixtral-8x7B-Instruct-v0.1
  • Phi-3.5-mini-instruct
  • Qwen2.5-7B-Instruct

Kilo Code (https://kilocode.ai/)

  • bytedance-seed/dola-seed-2.0-pro:free - Modality: Text | Rate Limit: ~200 req/hr
  • x-ai/grok-code-fast-1:optimized:free - Modality: Text (code) | Rate Limit: ~200 req/hr
  • nvidia/nemotron-3-super-120b-a12b:free
  • arcee-ai/trinity-large-thinking:free - Modality: Text (reasoning) | Rate Limit: ~200 req/hr
  • openrouter/free - Modality: Text | Rate Limit: ~200 req/hr

LLM7.io (https://llm7.io/)

  • deepseek-r1-0528 - Modality: Text (reasoning) | Rate Limit: 30 RPM (120 with token)
  • deepseek-v3-0324 - Modality: Text | Rate Limit: 30 RPM (120 with token)
  • gemini-2.5-flash-lite - Modality: Text + Vision | Rate Limit: 30 RPM (120 with token)
  • + 3 more model (https://llm7.io/)

NVIDIA NIM (https://build.nvidia.com/)

  • deepseek-ai/deepseek-r1
  • nvidia/llama-3.1-nemotron-ultra-253b-v1
  • nvidia/nemotron-3-super-120b-a12b
  • + 3 more models (https://build.nvidia.com/models)

Ollama Cloud (https://ollama.com/cloud)

  • llama3.1:cloud
  • deepseek-r1:cloud
  • qwen2.5:cloud
  • gemma2:cloud
  • mistral:cloud

OpenRouter (https://openrouter.ai/)

  • deepseek/deepseek-r1-0528:free
  • deepseek/deepseek-chat-v3-0324:free
  • qwen/qwen3.6-plus:free
  • + 9 more free models (https://openrouter.ai/models?q=free)

SiliconFlow (https://siliconflow.com/)

  • Qwen/Qwen3-8B
  • deepseek-ai/DeepSeek-R1-0528-Qwen3-8B
  • deepseek-ai/DeepSeek-R1-Distill-Qwen-7B
  • + 3 more model (https://siliconflow.com/models)

RPM = requests per minute • RPD = requests per day. TPM = Tokens per minute • TPD = Tokens per day • RPS = Requests per second • All endpoints are OpenAI SDK-compatible.

stosssik

4 か月前議論

[dead]

stosssik

4 か月前議論

I've talked to over a hundred OpenClaw users over the past two months. Cost comes up in almost every conversation. People set up their agent, use it normally, and end up with bills they didn't expect. $141 overnight from a misconfigured heartbeat. $800 in a month on a multi-agent setup. $30 burned doing barely anything.

The article digs into why this happens and what you can do about it. The core problem is that without optimization, every request hits your most expensive model, your system context loads on every call, and your conversation history grows with each exchange. It adds up fast.

The fixes range from simple config changes to architectural decisions. Routing tasks to the right model instead of sending everything to Opus. Using skills instead of spinning up multiple agents. Leveraging prompt caching on the provider side. Keeping your context lean. Running local models for lightweight tasks. And tracking costs daily instead of discovering a surprise bill at the end of the month.

Two deployments documented 77% and 80% cost reductions through these approaches. All sources and community reports are linked at the bottom. Happy to answer questions.

stosssik

4 か月前議論

I mapped the major players building the OpenClaw ecosystem, just 2 months after its release.

What's unfolding around OpenClaw is unlike anything I've witnessed in open-source AI.

In 60 days: - 230K+ GitHub stars - 116K+ Discord members - ClawCon touring globally (SF, Berlin, Tokyo...) - A dedicated startup validation platform (TrustMRR) - And an entire ecosystem of companies, tools and integrations forming around a single open-source project.

Managed hosting, LLM routing, security layers, agent social networks, skill marketplaces.

New categories are taking shape in real time.

Some of these players are only weeks old. And established companies like OpenRouter, LiteLLM or VirusTotal are shipping native integrations.

Whether you're a VC exploring AI infra, an operator running agents, or a founder building in this space, this is the landscape right now.

Some of these startups are already pulling real revenue. Alternatives are stacking thousands of GitHub stars on their own. OpenRouter recently raised funding. The money and the users are already here. Most of what's on this map didn't exist 60 days ago.

This is what happens when an open-source project launches with the right building blocks at the right moment.

stosssik

5 か月前議論

This resonates a lot. And we’re working on something in the same space: a way to build MCP aps for non technical people. If there are builders here who like experimenting, we’re looking for beta testers: -> https://manifest.build

stosssik

6 か月前議論

Totally agree. Vibe coding will generate lots of internal AI apps, but turning them into reliable, secure, governed services still requires real engineering, which is exactly why we’re building https://manifest.build. It lets non-technical teams build Agentic apps fast through an AI powered workflow builder while giving engineering and IT a single platform to add governance, security, data access, and keep everything production-ready at scale.

stosssik

6 か月前議論

Thanks for the perspective. Could you be more concrete about what specifically doesn’t change with vibe-coded apps? Have you recurring friction points in mind that force a handoff to professional engineers once these apps need to scale ?

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How Much Do GPU Clusters Cost?

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Free models you can use with your OpenClaw (no credit card needed)

Query and manage Marketplace databases from the dashboard

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A curated list of open-source projects and resources for the OpenClaw ecosystem

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Learn Fundamentals, Not Frameworks

Show HN: The OpenClaw Market Map, Q1 2026

How to stop burning money on OpenClaw

Manifest (Skydeck Batch21) – open-source alternative to OpenRouter

Open source router for personal AI agents

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