I tested 4 free 70B-class LLM endpoints for real production work — here's what each is actually good at

The question

Most "production-grade" AI tools ship on paid endpoints — OpenAI, Anthropic, Gemini Pro. That's the safe choice. It's also the expensive one.

I wanted to know: in mid-2026, can free 70B-class open-source endpoints actually carry a real product workload? Not a toy chatbot — a tool that generates working HTML/CSS/JS for arbitrary user prompts.

So I built one. The result is Sitecraft (wiz-craft.vercel.app) — a free, open-source AI website builder. It runs across four different free endpoints and lets users switch between them mid-conversation.

This post is what I learned about each one. Not a benchmark — a working engineer's notes.

The 4 endpoints I shipped

Provider	Model	Why it's on the list
Cerebras	Qwen 3 235B	Reasoning depth — strongest at "think before generating"
Groq	Llama 4 Scout	Throughput king — fastest token rate I've measured
OpenRouter	Ling-2.6 Flash	Generalist; best fallback when the others rate-limit
Cloudflare	GPT-OSS 120B	Edge inference; lowest latency from a Workers backend

All four have free tiers that are actually usable for shipping (not just "free for 100 tokens then $50/M"). Different free-tier shapes, but real free.

What each one is actually good at

Cerebras · Qwen 3 235B — the reasoner

When the prompt requires planning (e.g. "build a 3-page site with consistent design language across all pages, plus a working contact form"), Qwen on Cerebras consistently produces the most coherent output. It thinks about the whole problem before emitting code.

Trade-off: it's slower per token than Groq, and the free tier rate-limits aggressively when you go beyond a few requests per minute.

Use it when: The prompt is open-ended and the model needs to invent structure.

Groq · Llama 4 Scout — the speed demon

Groq's LPUs are the fastest inference I've ever benchmarked. Llama 4 Scout hits ~500+ tokens/second sustained, which means a full single-page site (~3000-5000 tokens) lands in under 10 seconds — feels instant in the UI.

Trade-off: Llama 4 Scout is smaller and less "thoughtful" than Qwen 3 235B. For complex prompts it sometimes generates plausible but incorrect code (wrong CSS selectors, hallucinated APIs).

Use it when: Iteration speed matters more than first-shot correctness.

OpenRouter · Ling-2.6 Flash — the generalist fallback

OpenRouter's free Ling-2.6 Flash isn't the best at any single thing, but it's consistently okay across prompt types and almost never rate-limits. That makes it the perfect fallback target when one of the other three is throttled.

Trade-off: code output quality is noticeably lower than Qwen — more boilerplate, less elegant HTML structure.

Use it when: You need a fallback that won't fail. Paired with quality-checks downstream, it's the safety net.

Cloudflare · GPT-OSS 120B — the edge play

If your backend already runs on Cloudflare Workers, calling Cloudflare AI from the same edge node is hands-down the lowest-latency setup. No cross-region hop, no cold-start penalty.

Trade-off: GPT-OSS 120B is older architecture than the others. Output quality sits between Llama 4 Scout and Ling — fine for short outputs, weaker for long-form generation.

Use it when: Your stack is already on Cloudflare and you want to keep the inference call inside the edge.

The orchestration strategy

You don't pick one. You orchestrate.

For Sitecraft I shipped a simple router:

1. Default: Groq Llama 4 (fastest perceived response)
2. If user explicitly toggles "high-quality": Cerebras Qwen 3 235B
3. If primary is rate-limited (429): fall back to OpenRouter Ling
4. Cloudflare GPT-OSS: offered as a manual switch for users on slow connections (edge-routed)

The user can also switch mid-conversation — useful when, say, Qwen produced a great structural draft but you want Groq to iterate fast on the styling.

The whole router is ~80 lines of plain JS. No LangChain, no framework. Just an if/else over which endpoint to hit, plus a small wrapper that normalises response formats (each provider returns slightly different envelope JSON).

The honest trade-offs

If you're considering this approach, here's what I wish someone had told me upfront:

• Response format quirks. Every provider returns slightly different JSON. Cerebras gives choices[0].message.content, Cloudflare gives result.response, OpenRouter mostly mirrors OpenAI but with quirks on streaming. Build a normaliser early or you'll regret it.

• Free tiers are real but bounded. "Free" usually means rate-limited per minute and per day. For a side project with low traffic, you'll never notice. For a viral hit, you'll need a paid tier or a queue.

• Quality variance is real. Even within the same prompt, Qwen and Llama 4 will produce noticeably different code. If your UX expects consistency, normalise via post-processing or pick one provider per request type.

• No streaming compatibility guarantees. SSE format varies subtly. If you stream tokens to a UI, expect to write provider-specific stream parsers.

• Latency varies wildly by region. Groq is fast from US-East. From APAC, the round-trip dominates. Cloudflare's edge play wins here.

When this approach is right (and when it isn't)

Use free open-source endpoints if:

• You're shipping a side project / proof-of-concept and don't want a credit-card dependency
• Your users are okay with "good enough" code (and you can iterate)
• You want flexibility to swap models without lock-in
• You're learning about LLM orchestration and want hands-on experience with the trade-offs

Stick with paid (Claude / GPT-5 / Gemini Pro) if:

• You need single-shot correctness (no iteration loop)
• You're building agentic workflows with deep reasoning (multi-tool, long context)
• You have a real budget and uptime SLA matters
• Your prompts genuinely need 200K+ context

For Sitecraft, the 4-endpoint orchestration was the right call — generating a website is iterative anyway, the user is in the loop, and "free forever" is part of the product pitch.

For my other side project, App Architect (a 5-phase design workflow that turns app ideas into TDD prompts), I went the opposite direction and built it on Claude Artifacts — because that tool needs deep reasoning over a long structured conversation, and the paid frontier model is worth it.

Right tool for the right job.

Try it

→ wiz-craft.vercel.app — switch between the 4 endpoints mid-conversation and feel the difference for yourself.

Source: github.com/pcpranav/sitecraft

If you've shipped on free open-source endpoints, I'd love to hear which providers you settled on and why. Drop a comment.