Groq
80 pts
0 wins
VS
NVIDIA Build (NIM API)
80 pts
1 wins
🤝 It's a tie — both have their strengths
📊 Side-by-Side
Category
Groq
NVIDIA Build (NIM API)
Free Tier
✅ 6000 tokens/min (Llama 3.3 70B)
✅ Unlimited (40 RPM rate limit)
Free API
✅ Free tier（永久免费）
✅ 无限制（已取消额度限制）
Rate Limit
30 RPM / 6000 TPM
40 RPM（可申请提升到 200 RPM）
Open Source
❌ No
❌ No
Free Models
6
10
GitHub Stars
-
-
🧠 Model Details
Groq 6 models Llama 3.3 70B Versatile
World's fastest inference, 6000 tokens/min free, LPU chip accelerated
Llama 4 Scout 17B
Meta Llama 4 Scout, MoE architecture, free to use
Llama 4 Maverick 17B
Meta Llama 4 Maverick, MoE architecture, free to use
Mixtral 8x7B
MoE architecture, cost-effective
Gemma 2 9B
Google Gemma 2, ultra-fast small model
DeepSeek R1 Distill Llama 70B
DeepSeek R1 distilled, strong reasoning
NVIDIA Build (NIM API) 10 models MiniMax M2.7
230B params, coding/reasoning/office all-rounder
Kimi K2.5
Moonshot native multimodal agentic model, 15T tokens training, 1M context, top Chinese ability
GLM-5.1
Zhipu's latest flagship, GLM-5 upgrade, optimized for agentic coding/long-horizon reasoning. GLM-5 deprecated 2026-04-20
DeepSeek V3.2
671B MoE, coding champion
DeepSeek R1
671B MoE, reasoning champion
Gemma 4 31B-IT
Google's latest open source, strong agentic capability, runs on consumer hardware
Nemotron-3-Super-120B
NVIDIA's own flagship, hybrid Mamba-Transformer MoE, 1M context, 7.5x throughput vs Qwen3.5-122B
Llama 4 Maverick
Meta's latest open source LLM
Qwen 3.5
Alibaba Qwen, native multimodal, 397B params with only 17B active, extremely efficient
Step 3.5 Flash
StepFun, extremely fast