Groq vs OpenRouter
A side-by-side look at scores, pricing and features — with RECATOOLS' ASEAN-aware verdict for each.
Groq
Ultra-fast open-weight model inference on custom LPU silicon
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| RECATOOLS Score | 7.6 / 10 | 8.6 / 10 |
| Capability | ||
| Value for money | ||
| Ease of use | ||
| ASEAN readiness | ||
| API quality | ||
| Pricing | Freemium | Freemium |
| Free tier | Forever free: 14,400 requests/day, 30 RPM, 6,000 TPM, no credit card. Open-weight model access (Llama, Gemma, Mixtral, Qwen, DeepSeek Distill, Whisper). Limits apply at the org level. | — |
| Paid from | Llama 3.1 8B $0.05/$0.08; Llama 3.3 70B $0.59/$0.79 per 1M in/out tokens | — |
| Has API | ✓ | ✓ |
| Open source | ✗ | ✗ |
| Free to use | ✓ | ✗ |
| Users | ~3M developers/teams on GroqCloud (mid-2026); ~75% of Fortune 100 hold accounts | — |
| Founded | 2016 | — |
| Maker | Groq, Inc. (independent; Nvidia acquired most chip assets/IP/leadership in a ~$20B Dec 2025 deal, but GroqCloud was excluded and stays with independent Groq) | — |
| Verdict | Groq is among the fastest options for open-weight model inference — if raw tokens-per-second throughput is your primary requirement, few providers beat it at this price point (independent benchmarks put Llama 3.3 70B at... |
OpenRouter solved a real headache: instead of holding a dozen provider keys and reconciling a dozen invoices, you point one OpenAI-compatible endpoint at 300-plus models and get automatic fallback when a provider chokes.... |
| Full review → | Full review → |
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Comparisons cover up to 4 tools. Scores are RECATOOLS editorial assessments; verify current pricing on each vendor's site.