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description
description
Use Nscale Serverless Inference API with promptfoo for cost-effective AI model evaluation and testing

Nscale

The Nscale provider enables you to use Nscale's Serverless Inference API models with promptfoo. Nscale offers cost-effective AI inference with up to 80% savings compared to other providers, zero rate limits, and no cold starts.

Setup

Set your Nscale service token as an environment variable:

export NSCALE_SERVICE_TOKEN=your_service_token_here

Alternatively, you can add it to your .env file:

NSCALE_SERVICE_TOKEN=your_service_token_here

Obtaining Credentials

You can obtain service tokens by:

  1. Signing up at Nscale
  2. Navigating to your account settings
  3. Going to "Service Tokens" section

Configuration

To use Nscale models in your promptfoo configuration, use the nscale: prefix followed by the model name:

providers:
  - nscale:openai/gpt-oss-120b
  - nscale:meta/llama-3.3-70b-instruct
  - nscale:qwen/qwen-3-235b-a22b-instruct

Model Types

Nscale supports different types of models through specific endpoint formats:

Chat Completion Models (Default)

For chat completion models, you can use either format:

providers:
  - nscale:chat:openai/gpt-oss-120b
  - nscale:openai/gpt-oss-120b # Defaults to chat

Completion Models

For text completion models:

providers:
  - nscale:completion:openai/gpt-oss-20b

Embedding Models

For embedding models:

providers:
  - nscale:embedding:qwen/qwen3-embedding-8b
  - nscale:embeddings:qwen/qwen3-embedding-8b # Alternative format

Nscale offers a wide range of popular AI models:

Text Generation Models

Model Provider Format Use Case
GPT OSS 120B nscale:openai/gpt-oss-120b General-purpose reasoning and tasks
GPT OSS 20B nscale:openai/gpt-oss-20b Lightweight general-purpose model
Qwen 3 235B Instruct nscale:qwen/qwen-3-235b-a22b-instruct Large-scale language understanding
Qwen 3 235B Instruct 2507 nscale:qwen/qwen-3-235b-a22b-instruct-2507 Latest Qwen 3 235B variant
Qwen 3 4B Thinking 2507 nscale:qwen/qwen-3-4b-thinking-2507 Reasoning and thinking tasks
Qwen 3 8B nscale:qwen/qwen-3-8b Mid-size general-purpose model
Qwen 3 14B nscale:qwen/qwen-3-14b Enhanced reasoning capabilities
Qwen 3 32B nscale:qwen/qwen-3-32b Large-scale reasoning and analysis
Qwen 2.5 Coder 3B Instruct nscale:qwen/qwen-2.5-coder-3b-instruct Lightweight code generation
Qwen 2.5 Coder 7B Instruct nscale:qwen/qwen-2.5-coder-7b-instruct Code generation and programming
Qwen 2.5 Coder 32B Instruct nscale:qwen/qwen-2.5-coder-32b-instruct Advanced code generation
Qwen QwQ 32B nscale:qwen/qwq-32b Specialized reasoning model
Llama 3.3 70B Instruct nscale:meta/llama-3.3-70b-instruct High-quality instruction following
Llama 3.1 8B Instruct nscale:meta/llama-3.1-8b-instruct Efficient instruction following
Llama 4 Scout 17B nscale:meta/llama-4-scout-17b-16e-instruct Image-Text-to-Text capabilities
DeepSeek R1 Distill Llama 70B nscale:deepseek/deepseek-r1-distill-llama-70b Efficient reasoning model
DeepSeek R1 Distill Llama 8B nscale:deepseek/deepseek-r1-distill-llama-8b Lightweight reasoning model
DeepSeek R1 Distill Qwen 1.5B nscale:deepseek/deepseek-r1-distill-qwen-1.5b Ultra-lightweight reasoning
DeepSeek R1 Distill Qwen 7B nscale:deepseek/deepseek-r1-distill-qwen-7b Compact reasoning model
DeepSeek R1 Distill Qwen 14B nscale:deepseek/deepseek-r1-distill-qwen-14b Mid-size reasoning model
DeepSeek R1 Distill Qwen 32B nscale:deepseek/deepseek-r1-distill-qwen-32b Large reasoning model
Devstral Small 2505 nscale:mistral/devstral-small-2505 Code generation and development
Mixtral 8x22B Instruct nscale:mistral/mixtral-8x22b-instruct-v0.1 Large mixture-of-experts model

Embedding Models

Model Provider Format Use Case
Qwen 3 Embedding 8B nscale:embedding:Qwen/Qwen3-Embedding-8B Text embeddings and similarity

Text-to-Image Models

Model Provider Format Use Case
Flux.1 Schnell nscale:image:BlackForestLabs/FLUX.1-schnell Fast image generation
Stable Diffusion XL nscale:image:stabilityai/stable-diffusion-xl-base-1.0 High-quality image generation
SDXL Lightning 4-step nscale:image:ByteDance/SDXL-Lightning-4step Ultra-fast image generation
SDXL Lightning 8-step nscale:image:ByteDance/SDXL-Lightning-8step Balanced speed and quality

Configuration Options

Nscale supports standard OpenAI-compatible parameters:

providers:
  - id: nscale:openai/gpt-oss-120b
    config:
      temperature: 0.7
      max_tokens: 1024
      top_p: 0.9
      frequency_penalty: 0.1
      presence_penalty: 0.2
      stop: ['END', 'STOP']
      stream: true

Supported Parameters

  • temperature: Controls randomness (0.0 to 2.0)
  • max_tokens: Maximum number of tokens to generate
  • top_p: Nucleus sampling parameter
  • frequency_penalty: Reduces repetition based on frequency
  • presence_penalty: Reduces repetition based on presence
  • stop: Stop sequences to halt generation
  • stream: Enable streaming responses
  • seed: Deterministic sampling seed

Example Configuration

Here's a complete example configuration:

providers:
  - id: nscale-gpt-oss
    config:
      temperature: 0.7
      max_tokens: 512
  - id: nscale-llama
    config:
      temperature: 0.5
      max_tokens: 1024

prompts:
  - 'Explain {{concept}} in simple terms'
  - 'What are the key benefits of {{concept}}?'

tests:
  - vars:
      concept: quantum computing
    assert:
      - type: contains
        value: 'quantum'
      - type: llm-rubric
        value: 'Explanation should be clear and accurate'

Pricing

Nscale offers highly competitive pricing:

  • Text Generation: Starting from $0.01 input / $0.03 output per 1M tokens
  • Embeddings: $0.04 per 1M tokens
  • Image Generation: Starting from $0.0008 per mega-pixel

For the most current pricing information, visit Nscale's pricing page.

Key Features

  • Cost-Effective: Up to 80% savings compared to other providers
  • Zero Rate Limits: No throttling or request limits
  • No Cold Starts: Instant response times
  • Serverless: No infrastructure management required
  • OpenAI Compatible: Standard API interface
  • Global Availability: Low-latency inference worldwide

Error Handling

The Nscale provider includes built-in error handling for common issues:

  • Network timeouts and retries
  • Rate limiting (though Nscale has zero rate limits)
  • Invalid API key errors
  • Model availability issues

Support

For support with the Nscale provider: