NVIDIA NIM provides optimized AI model inference APIs for LLMs, vision, and embedding models through NVIDIA cloud infrastructure.
integrate.api.nvidia.comRankings are based on community-submitted tests and periodic health probes. Advisory only, not official data.
Compare 59 model rows across audit recency, latest speed tests, throughput, latency, and per-token pricing.
| Model | Input ($/M) | Output ($/M) | Audit | Speed | Latency |
|---|---|---|---|---|---|
| - | - | 1006884100 | 81.1 t/s | 1.05 s | |
google/diffusiongemma-26b-a4b-it | - | - | — | 697.7 t/s | 0.70 s |
nvidia/nemotron-3-ultra-550b-a55b | - | - | — | 79.4 t/s | 1.70 s |
stepfun-ai/step-3.7-flash | - | - | — | 118.6 t/s | 15.57 s |
mistralai/mistral-medium-3.5-128b | - | - | — | 46.8 t/s | 10.40 s |
nvidia/nemotron-3-nano-omni-30b-a3b-reasoning | - | - | — | 274.5 t/s | 0.66 s |
google/gemma-4-31b-it | - | - | 1006886100 | 20.4 t/s | 26.82 s |
meta/llama-3.1-8b-instruct | - | - | — | 145.7 t/s | 0.21 s |
meta/llama-3.3-70b-instruct | - | - | — | 28.1 t/s | 5.27 s |
mistralai/mistral-small-4-119b-2603 | - | - | — | 120.9 t/s | 0.29 s |
nvidia/nemotron-mini-4b-instruct | - | - | — | 86.6 t/s | 0.45 s |
| - | - | 848480100 | 82.4 t/s | 9.31 s | |
nvidia/nemotron-3-nano-30b-a3b | - | - | — | 207.0 t/s | 1.13 s |
| - | - | — | 83.2 t/s | 0.39 s | |
| - | - | 727280100 | 21.4 t/s | 1.34 s | |
| - | - | 1006878100 | 22.8 t/s | 14.36 s | |
| - | - | — | 42.3 t/s | 32.01 s | |
nvidia/nemotron-3-super-120b-a12b | - | - | — | 28.5 t/s | 31.58 s |
marin/marin-8b-instruct | - | - | — | 84.2 t/s | 0.44 s |
qwen/qwen3-next-80b-a3b-thinking | - | - | — | 106.6 t/s | 9.02 s |
meta/llama-4-maverick-17b-128e-instruct | - | - | — | 92.8 t/s | 0.27 s |
institute-of-science-tokyo/llama-3.1-swallow-70b-instruct-v0.1 | - | - | — | 19.0 t/s | 0.49 s |
meta/llama-3.2-90b-vision-instruct | - | - | — | 16.9 t/s | 0.69 s |
| - | - | — | 18.5 t/s | 0.50 s | |
meta/llama-3.1-405b-instruct | - | - | — | 22.7 t/s | 5.87 s |
qwen/qwen3-coder-480b-a35b-instruct | - | - | — | 49.3 t/s | 2.07 s |
meta/llama3-70b-instruct | - | - | — | 37.5 t/s | 0.47 s |
| - | - | — | 31.3 t/s | 16.79 s | |
z-ai/glm5 | - | - | — | 24.9 t/s | 35.20 s |
stockmark/stockmark-2-100b-instruct | - | - | — | 55.3 t/s | 0.74 s |
nvidia/llama-3.1-nemotron-ultra-253b-v1 | - | - | — | 45.2 t/s | 0.21 s |
| - | - | — | 45.2 t/s | 2.90 s | |
| - | - | 848480100 | 28.0 t/s | 13.61 s | |
| - | - | — | 78.8 t/s | 3.19 s | |
| - | - | — | 81.8 t/s | 4.79 s | |
| - | - | — | 47.9 t/s | 18.53 s | |
z-ai/glm4.7 | - | - | — | 57.0 t/s | 27.72 s |
| - | - | — | 86.4 t/s | 2.88 s | |
01-ai/yi-large | - | - | — | 43.7 t/s | 0.22 s |
| - | - | — | 55.6 t/s | 0.29 s | |
| - | - | — | 41.4 t/s | 2.36 s | |
google/gemma-2-27b-it | - | - | — | 43.7 t/s | 0.23 s |
google/gemma-3-27b-it | - | - | — | 50.8 t/s | 0.47 s |
meta/llama-3.1-70b-instruct | - | - | — | 51.2 t/s | 0.23 s |
microsoft/phi-3-medium-128k-instruct | - | - | — | 18.1 t/s | 0.49 s |
microsoft/phi-4-mini-flash-reasoning | - | - | — | 74.2 t/s | 0.46 s |
mistralai/mistral-small-24b-instruct | - | - | — | 29.7 t/s | 0.49 s |
mistralai/mixtral-8x22b-instruct-v0.1 | - | - | — | 89.7 t/s | 0.22 s |
| - | - | — | 45.1 t/s | 0.58 s | |
nvidia/llama-3.1-nemotron-70b-instruct | - | - | — | 52.2 t/s | 0.23 s |
nvidia/llama-3.3-nemotron-super-49b-v1.5 | - | - | — | 57.5 t/s | 11.11 s |
| - | - | — | 17.9 t/s | 4.49 s | |
| - | - | — | 41.3 t/s | 19.45 s | |
| - | - | — | 152.8 t/s | 0.95 s | |
| - | - | 7684100100 | 162.7 t/s | 1.12 s | |
| - | - | — | 44.5 t/s | 21.25 s | |
| - | - | — | 87.6 t/s | 8.96 s | |
| - | - | — | 41.0 t/s | 0.49 s | |
| - | - | — | 34.0 t/s | 0.59 s |
Showing 59 of 59 model rows
| Time | Model | Speed | Latency |
|---|---|---|---|
| Jul 5, 05:47 AM | z-ai/glm-5.2 | 24.30 tok/s | 1.40s |
| Jul 3, 03:37 AM | z-ai/glm-5.2 | 137.86 tok/s | 0.70s |
| Jul 2, 04:51 AM | deepseek-ai/deepseek-v4-flash | 13.40 tok/s | 57.53s |
| Jul 2, 04:49 AM | qwen/qwen3.5-122b-a10b | 58.72 tok/s | 1.67s |
| Jul 2, 04:42 AM | deepseek-ai/deepseek-v4-pro | 21.19 tok/s | 1.40s |
| Jul 2, 04:41 AM | mistralai/mistral-small-4-119b-2603 | 120.92 tok/s | 0.29s |
| Jul 2, 04:37 AM | mistralai/mistral-medium-3.5-128b | 46.84 tok/s | 10.40s |
| Jul 2, 04:34 AM | nvidia/nemotron-3-ultra-550b-a55b | 36.46 tok/s | 2.98s |
| Jul 2, 04:33 AM | moonshotai/kimi-k2.6 | 68.46 tok/s | 10.97s |
| Jul 2, 04:32 AM | google/diffusiongemma-26b-a4b-it | 697.68 tok/s | 0.70s |
Compare NVIDIA NIM alternatives against 6 nearby API providers using 317 LMSpeed signals across shared model coverage, pricing, benchmark speed, uptime, and free-model availability.
| Provider | Why compare | Models | Free | Avg price | Speed | 30d uptime |
|---|---|---|---|---|---|---|
| NVIDIA NIM nvidia-nim NVIDIA NIM provides optimized AI model inference APIs for LLMs, vision, and embedding models through NVIDIA cloud infrastructure. | Current provider baseline | 51 | 0 | N/A | 66 tok/s | 66.7% |
| OpenRouter openrouter A unified API interface providing access to over 300 models from 60+ providers, including OpenAI, Anthropic, and Google. |
| 191 | 0 | N/A | 86 tok/s | 66.7% |
siliconflow Provides cost-effective generative AI cloud services based on open-source models for text, image, video, and audio generation. |
| 60 | 0 | N/A | 53 tok/s | 66.7% |
api-kriora-com Provides OpenAI-compatible APIs and managed GPU instances for deploying and scaling open-source AI models. |
| 9 | 0 | N/A | 565 tok/s | 66.7% |
router-huggingface-co Hugging Face Router provides intelligent model routing across Inference Providers, offering OpenAI-compatible API access to open-source models. |
| 7 | 0 | N/A | 138 tok/s | 40.7% |
api-fireworks-ai Fireworks AI provides a cloud platform for running and fine-tuning open-source AI models with optimized inference for production applications. |
| 5 | 0 | N/A | 139 tok/s | 66.7% |
550c-cloud 共绩算力 (550c.cloud) is a shared computing platform providing Ollama-hosted open-source AI model inference via OpenAI-compatible API. |
| 4 | 0 | N/A | 112 tok/s | 63% |