NVIDIA
NVIDIA
Language model · United States ·May 2024

NV-Embed-v1

Language Open Weights
7B
Parameters

About NV-Embed-v1

NV-Embed-v1 is an AI model developed by NVIDIA, in the language category, released in 2024, made available as an open-weights model with 7B params.

On this page you'll find NV-Embed-v1's full specifications. Review provider pricing and benchmark scores below, or compare NV-Embed-v1 head-to-head with other language models.

→ More models by NVIDIA → All language models → AI benchmarks leaderboard

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Announcement ↗

Run NV-Embed-v1 locally — what to buy

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Sized to what NV-Embed-v1 actually needs (~8k context at Q4), not to the biggest GPU: Good = cheapest that runs it, Better = best value, Best = most headroom. Speed is a hardware estimate; anything past ~120 tok/s is shown as instant.

Good
Intel Arc B580 12GB
Consumer GPU · ~$249
~83.8 tok/s
Q4 · fits full context · up to 8k ctx
Runs with: ExLlamaV2, KoboldCpp, LM Studio
See full estimate →
Better
Intel Arc A770 16GB
Consumer GPU · ~$329
~102.9 tok/s
Q4 · fits full context · up to 8k ctx
Runs with: ExLlamaV2, KoboldCpp, LM Studio
See full estimate →
Best
AMD Radeon RX 7800 XT
Consumer GPU · ~$499
~120 tok/s
Q4 · fits full context · up to 8k ctx
Runs with: ExLlamaV2, KoboldCpp, LM Studio
See full estimate →

Software support

·ExLlamaV2 ·KoboldCpp ·LM Studio ·MLX ·Ollama ·SGLang ·TensorRT-LLM ·llama.cpp ·vLLM ?KTransformers ?text-generation-webui

✓ measured · · compatible · — not supported. Informational only — speed is hardware-based.

Consumer GPU
41.1–120+ tok/s
32 options →
Apple
24.9–120+ tok/s
18 options →
Datacenter GPU
120+ tok/s
13 options →

Community

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Frequently asked questions

What is NV-Embed-v1? ▶

NV-Embed-v1 is an AI model developed by NVIDIA, in the language category, released in 2024. It is tracked on GenAIList with its specifications, benchmark scores and provider pricing.

Who created NV-Embed-v1? ▶

NV-Embed-v1 was developed by NVIDIA and released in 2024.

Is NV-Embed-v1 open source or proprietary? ▶

NV-Embed-v1 ships as an open-weights model: you can download and self-host the weights, though the licence may place some restrictions on use.

How much does NV-Embed-v1 cost? ▶

Pricing for NV-Embed-v1 depends on the provider. See the providers table on this page for the latest API rates.

How does NV-Embed-v1 perform on benchmarks? ▶

Benchmark scores for NV-Embed-v1 are listed on this page as they are published. You can compare it head-to-head with other models on the GenAIList compare tool.

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