pi-nvidia-nim

NVIDIA NIM API provider extension for pi coding agent - access 100+ models from build.nvidia.com including DeepSeek V4 Flash/Pro, DeepSeek V3.2, Kimi K2.6, MiniMax M2.1, GLM-5, GLM-4.7, Qwen3, Llama 4, and many more.

https://github.com/user-attachments/assets/f44773e4-9bf8-4bb5-a9c0-d5938030701c

Setup

1. Get an NVIDIA NIM API Key

1. Go to build.nvidia.com
2. Sign in or create an account
3. Navigate to any model page and click "Get API Key"
4. Copy your key (starts with nvapi-)

2. Set Your API Key

# Preferred by this extension
export NVIDIA_NIM_API_KEY=nvapi-your-key-here

# Also supported, matching NVIDIA's website examples
export NVIDIA_API_KEY=nvapi-your-key-here

Add one of these to your ~/.bashrc, ~/.zshrc, or shell profile to persist it.

3. Install the Extension

As a pi package (recommended):

pi install git:github.com/xRyul/pi-nvidia-nim

Or load directly:

pi -e /path/to/pi-nvidia-nim

Or copy to your extensions directory:

cp -r pi-nvidia-nim ~/.pi/agent/extensions/pi-nvidia-nim

Usage

Once loaded, NVIDIA NIM models appear in the /model selector under the nvidia-nim provider. You can also:

• Press Ctrl+L to open the model selector and search for nvidia-nim
• Use /scoped-models to pin your favourite NIM models for quick switching

CLI

# Use a specific NIM model directly
pi --provider nvidia-nim --model "deepseek-ai/deepseek-v4-flash"

# With thinking enabled
pi --provider nvidia-nim --model "deepseek-ai/deepseek-v4-flash" --thinking high

# Limit model cycling to NIM models
pi --models "nvidia-nim/*"

Reasoning / Thinking

NVIDIA NIM models use a non-standard chat_template_kwargs parameter to enable thinking, rather than the standard OpenAI reasoning_effort. This extension handles this automatically via a custom streaming wrapper that injects the correct per-model parameters.

How it works

When you change the thinking level in pi (Shift+Tab to cycle), the extension:

1. Maps thinking levels to values each NIM model accepts. For DeepSeek V4, xhigh maps to max; lower enabled levels use high.
2. Injects chat_template_kwargs per model to actually enable thinking:
   • DeepSeek V4: { thinking: true, reasoning_effort: "high" | "max" }
   • DeepSeek V3.x, R1 distills: { thinking: true }
   • GLM-5, GLM-4.7: { enable_thinking: true, clear_thinking: false }
   • Kimi K2.6, K2-thinking: { thinking: true }
   • Qwen3, QwQ: { enable_thinking: true }
3. Explicitly disables thinking when the level is "off" for models that think by default (e.g., GLM-5, GLM-4.7).
4. Uses system role instead of developer for all NIM models - the developer role combined with chat_template_kwargs causes 500 errors on NIM.

Supported thinking levels

pi Level	NIM Mapping	Effect
off	No kwargs (or explicit disable)	No reasoning output
minimal	low, or high for DeepSeek V4	Thinking enabled
low	low, or high for DeepSeek V4	Thinking enabled
medium	medium, or high for DeepSeek V4	Thinking enabled
high	high	Thinking enabled
xhigh	high, or max for DeepSeek V4	Maximum supported thinking

Available Models

The extension ships with curated metadata for 42 featured models. At startup, it also queries the NVIDIA NIM API to discover additional models automatically.

Featured Models

Model	Reasoning	Vision	Context
deepseek-ai/deepseek-v4-flash	✅		1M
deepseek-ai/deepseek-v4-pro	✅		1M
deepseek-ai/deepseek-v3.2	✅		128K
deepseek-ai/deepseek-v3.1	✅		128K
moonshotai/kimi-k2.6	✅		256K
moonshotai/kimi-k2-thinking	✅		128K
minimaxai/minimax-m2.1			1M
z-ai/glm5	✅		128K
z-ai/glm4.7	✅		128K
openai/gpt-oss-120b			128K
qwen/qwen3-coder-480b-a35b-instruct	✅		256K
qwen/qwen3-235b-a22b	✅		128K
meta/llama-4-maverick-17b-128e-instruct			1M
meta/llama-3.1-405b-instruct			128K
meta/llama-3.2-90b-vision-instruct		✅	128K
mistralai/mistral-large-3-675b-instruct-2512			128K
mistralai/devstral-2-123b-instruct-2512			128K
nvidia/llama-3.1-nemotron-ultra-253b-v1	✅		128K
nvidia/llama-3.3-nemotron-super-49b-v1.5	✅		128K
microsoft/phi-4-mini-flash-reasoning	✅		128K
ibm/granite-3.3-8b-instruct			128K

...and 20+ more curated models, plus automatic discovery of new models from the API.

Tool Calling

All major models support OpenAI-compatible tool calling. Tested and confirmed working with DeepSeek V4/V3.2, GLM-5, GLM-4.7, Qwen3, Kimi K2.6, and others.

How It Works

This extension uses pi.registerProvider() to register NVIDIA NIM as a custom provider with a custom streamSimple wrapper around pi's built-in openai-completions streamer.

The custom streamer:

1. Intercepts the request payload via onPayload callback
2. Injects chat_template_kwargs for models that need it to enable thinking
3. Maps unsupported thinking levels to NIM-compatible values (minimal → low; xhigh → high or DeepSeek V4 max)
4. Suppresses reasoning_effort for models that don't respond to it (e.g., DeepSeek without kwargs)
5. Uses the standard OpenAI SSE streaming format - pi already parses reasoning_content and reasoning fields from streaming deltas

Configuration

The only configuration needed is either the NVIDIA_NIM_API_KEY or NVIDIA_API_KEY environment variable. All models on NVIDIA NIM are free during the preview period (with rate limits).

Notes

• All costs are set to $0 since NVIDIA NIM preview models are free (rate-limited)
• Context windows and max tokens are best-effort estimates; some may differ from actual API limits
• If a model isn't in the curated list, it gets a conservative 32K context window and 8K max output tokens
• The extension filters out embedding, reward, safety, and other non-chat models automatically
• Rate limits on free preview keys are relatively strict; you may encounter 429 errors during heavy usage
• MiniMax models use <think> tags inline in content rather than the reasoning_content field

License

MIT